def delete_topic():
"""
Delete the specified topic
"""
if ARG.server:
ARG.server += ':9092'
else:
ARG.server = ','.join(SERVER['Kafka']['broker_list'])
client = KafkaClient(bootstrap_servers=ARG.server)
try:
topic_req = admin.DeleteTopicsRequest_v1(topics=[ARG.topic],
timeout=1000)
future = client.send(client.least_loaded_node(), topic_req)
client.poll(timeout_ms=100, future=future)
result = future.value
LOGGER.debug(result)
error_code = result.topic_error_codes[0][1]
if error_code:
LOGGER.critical('Could not delete topic %s, error code=%d',
ARG.topic, error_code)
sys.exit(error_code)
else:
print("Deleted topic %s" % (ARG.topic))
except KafkaError:
LOGGER.critical("Could not delete topic %s", ARG.topic)
def test_send(conn):
cli = KafkaClient()
try:
cli.send(2, None)
except Errors.NodeNotReadyError:
pass
else:
assert False, 'NodeNotReadyError not raised'
cli._initiate_connect(0)
# ProduceRequest w/ 0 required_acks -> no response
request = ProduceRequest(0, 0, [])
ret = cli.send(0, request)
assert conn.send.called_with(request, expect_response=False)
assert isinstance(ret, Future)
request = MetadataRequest([])
cli.send(0, request)
assert conn.send.called_with(request, expect_response=True)
def test_send(conn):
cli = KafkaClient()
try:
cli.send(2, None)
except Errors.NodeNotReadyError:
pass
else:
assert False, 'NodeNotReadyError not raised'
cli._initiate_connect(0)
# ProduceRequest w/ 0 required_acks -> no response
request = ProduceRequest(0, 0, [])
ret = cli.send(0, request)
assert conn.send.called_with(request, expect_response=False)
assert isinstance(ret, Future)
request = MetadataRequest([])
cli.send(0, request)
assert conn.send.called_with(request, expect_response=True)
def test_send(conn):
cli = KafkaClient()
# Send to unknown node => raises AssertionError
try:
cli.send(2, None)
assert False, 'Exception not raised'
except AssertionError:
pass
# Send to disconnected node => NodeNotReady
conn.state = ConnectionStates.DISCONNECTED
f = cli.send(0, None)
assert f.failed()
assert isinstance(f.exception, Errors.NodeNotReadyError)
conn.state = ConnectionStates.CONNECTED
cli._maybe_connect(0)
# ProduceRequest w/ 0 required_acks -> no response
request = ProduceRequest[0](0, 0, [])
ret = cli.send(0, request)
assert conn.send.called_with(request, expect_response=False)
assert isinstance(ret, Future)
request = MetadataRequest[0]([])
cli.send(0, request)
assert conn.send.called_with(request, expect_response=True)
def test_send(conn):
cli = KafkaClient()
# Send to unknown node => raises AssertionError
try:
cli.send(2, None)
assert False, 'Exception not raised'
except AssertionError:
pass
# Send to disconnected node => NodeNotReady
conn.state = ConnectionStates.DISCONNECTED
f = cli.send(0, None)
assert f.failed()
assert isinstance(f.exception, Errors.NodeNotReadyError)
conn.state = ConnectionStates.CONNECTED
cli._maybe_connect(0)
# ProduceRequest w/ 0 required_acks -> no response
request = ProduceRequest[0](0, 0, [])
ret = cli.send(0, request)
assert conn.send.called_with(request, expect_response=False)
assert isinstance(ret, Future)
request = MetadataRequest[0]([])
cli.send(0, request)
assert conn.send.called_with(request, expect_response=True)
def ensure_topic(topic,
num_partitions,
replication_factor,
logger,
timeout_ms=3000,
brokers='localhost'):
logger.debug('checking kafka for topic ' + topic)
client = KafkaClient(bootstrap_servers=brokers)
if topic not in client.cluster.topics(exclude_internal_topics=True):
logger.debug('creating kafka topic ' + topic)
request = admin.CreateTopicsRequest_v0(
create_topic_requests=[(
topic,
num_partitions,
replication_factor,
[], # Partition assignment
[], # Configs
)],
timeout=timeout_ms)
future = client.send(client.least_loaded_node(), request)
client.poll(timeout_ms=timeout_ms, future=future)
result = future.value
error_code = result.topic_errors[0][1]
# 0: success
# 36: already exists, check topic
if error_code == 0:
logger.debug('kafka topic ' + topic + ' created')
return
elif error_code != 36:
logger.error('error creating kafka topic ' + topic)
raise Exception(
'Unknown error code during creation of topic `{}`: {}'.format(
topic, error_code))
else:
logger.debug('kafka topic ' + topic + ' exists')
class OffsetsFetcherAsync(object):
DEFAULT_CONFIG = {
'session_timeout_ms': 30000,
'heartbeat_interval_ms': 3000,
'retry_backoff_ms': 100,
'api_version': (0, 9),
'metric_group_prefix': ''
}
def __init__(self, **configs):
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
self._client = KafkaClient(**self.config)
self._coordinator_id = None
self.group_id = configs['group_id']
self.topic = configs['topic']
def _ensure_coordinator_known(self):
"""Block until the coordinator for this group is known
(and we have an active connection -- java client uses unsent queue).
"""
while self._coordinator_unknown():
# Prior to 0.8.2 there was no group coordinator
# so we will just pick a node at random and treat
# it as the "coordinator"
if self.config['api_version'] < (0, 8, 2):
self._coordinator_id = self._client.least_loaded_node()
self._client.ready(self._coordinator_id)
continue
future = self._send_group_coordinator_request()
self._client.poll(future=future)
if future.failed():
if isinstance(future.exception,
Errors.GroupCoordinatorNotAvailableError):
continue
elif future.retriable():
metadata_update = self._client.cluster.request_update()
self._client.poll(future=metadata_update)
else:
raise future.exception # pylint: disable-msg=raising-bad-type
def _coordinator_unknown(self):
"""Check if we know who the coordinator is and have an active connection
Side-effect: reset _coordinator_id to None if connection failed
Returns:
bool: True if the coordinator is unknown
"""
if self._coordinator_id is None:
return True
if self._client.is_disconnected(self._coordinator_id):
self._coordinator_dead()
return True
return False
def _coordinator_dead(self, error=None):
"""Mark the current coordinator as dead."""
if self._coordinator_id is not None:
log.warning("Marking the coordinator dead (node %s) for group %s: %s.",
self._coordinator_id, self.group_id, error)
self._coordinator_id = None
def _send_group_coordinator_request(self):
"""Discover the current coordinator for the group.
Returns:
Future: resolves to the node id of the coordinator
"""
node_id = self._client.least_loaded_node()
if node_id is None:
return Future().failure(Errors.NoBrokersAvailable())
log.debug("Sending group coordinator request for group %s to broker %s",
self.group_id, node_id)
request = GroupCoordinatorRequest[0](self.group_id)
future = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_group_coordinator_response, future)
_f.add_errback(self._failed_request, node_id, request, future)
return future
def _handle_group_coordinator_response(self, future, response):
log.debug("Received group coordinator response %s", response)
if not self._coordinator_unknown():
# We already found the coordinator, so ignore the request
log.debug("Coordinator already known -- ignoring metadata response")
future.success(self._coordinator_id)
return
error_type = Errors.for_code(response.error_code)
if error_type is Errors.NoError:
ok = self._client.cluster.add_group_coordinator(self.group_id, response)
if not ok:
# This could happen if coordinator metadata is different
# than broker metadata
future.failure(Errors.IllegalStateError())
return
self._coordinator_id = response.coordinator_id
log.info("Discovered coordinator %s for group %s",
self._coordinator_id, self.group_id)
self._client.ready(self._coordinator_id)
future.success(self._coordinator_id)
elif error_type is Errors.GroupCoordinatorNotAvailableError:
log.debug("Group Coordinator Not Available; retry")
future.failure(error_type())
elif error_type is Errors.GroupAuthorizationFailedError:
error = error_type(self.group_id)
log.error("Group Coordinator Request failed: %s", error)
future.failure(error)
else:
error = error_type()
log.error("Unrecognized failure in Group Coordinator Request: %s",
error)
future.failure(error)
def _failed_request(self, node_id, request, future, error):
log.error('Error sending %s to node %s [%s]',
request.__class__.__name__, node_id, error)
# Marking coordinator dead
# unless the error is caused by internal client pipelining
if not isinstance(error, (Errors.NodeNotReadyError,
Errors.TooManyInFlightRequests)):
self._coordinator_dead()
future.failure(error)
def offsets(self, partitions, timestamp):
"""Fetch a single offset before the given timestamp for the set of partitions.
Blocks until offset is obtained, or a non-retriable exception is raised
Arguments:
partitions (iterable of TopicPartition) The partition that needs fetching offset.
timestamp (int): timestamp for fetching offset. -1 for the latest
available, -2 for the earliest available. Otherwise timestamp
is treated as epoch seconds.
Returns:
dict: TopicPartition and message offsets
"""
retries = 3
while retries > 0:
offsets = {}
for future in self._send_offset_request(partitions, timestamp):
self._client.poll(future=future)
if future.succeeded():
for tp, offset in future.value:
offsets[tp] = offset
continue
if not future.retriable():
raise future.exception # pylint: disable-msg=raising-bad-type
if future.exception.invalid_metadata:
refresh_future = self._client.cluster.request_update()
self._client.poll(future=refresh_future, sleep=True)
log.warning("Got exception %s and kept the loop", future.exception)
if offsets:
return offsets
retries -= 1
log.warning("Retrying the offsets fetch loop (%d retries left)", retries)
log.error("Unsuccessful offsets retrieval")
return {}
def _send_offset_request(self, partitions, timestamp):
"""Fetch a single offset before the given timestamp for the partition.
Arguments:
partitions iterable of TopicPartition: partitions that needs fetching offset
timestamp (int): timestamp for fetching offset
Returns:
list of Future: resolves to the corresponding offset
"""
topic = partitions[0].topic
nodes_per_partitions = {}
for partition in partitions:
node_id = self._client.cluster.leader_for_partition(partition)
if node_id is None:
log.debug("Partition %s is unknown for fetching offset,"
" wait for metadata refresh", partition)
return [Future().failure(Errors.StaleMetadata(partition))]
elif node_id == -1:
log.debug("Leader for partition %s unavailable for fetching offset,"
" wait for metadata refresh", partition)
return [Future().failure(Errors.LeaderNotAvailableError(partition))]
nodes_per_partitions.setdefault(node_id, []).append(partition)
# Client returns a future that only fails on network issues
# so create a separate future and attach a callback to update it
# based on response error codes
futures = []
for node_id, partitions in six.iteritems(nodes_per_partitions):
request = OffsetRequest[0](
-1, [(topic, [(partition.partition, timestamp, 1) for partition in partitions])]
)
future_request = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_offset_response, partitions, future_request)
def errback(e):
log.error("Offset request errback error %s", e)
future_request.failure(e)
_f.add_errback(errback)
futures.append(future_request)
return futures
def _handle_offset_response(self, partitions, future, response):
"""Callback for the response of the list offset call above.
Arguments:
partition (TopicPartition): The partition that was fetched
future (Future): the future to update based on response
response (OffsetResponse): response from the server
Raises:
AssertionError: if response does not match partition
"""
topic, partition_info = response.topics[0]
assert len(response.topics) == 1, (
'OffsetResponse should only be for a single topic')
partition_ids = set([part.partition for part in partitions])
result = []
for pi in partition_info:
part, error_code, offsets = pi
assert topic == partitions[0].topic and part in partition_ids, (
'OffsetResponse partition does not match OffsetRequest partition')
error_type = Errors.for_code(error_code)
if error_type is Errors.NoError:
assert len(offsets) == 1, 'Expected OffsetResponse with one offset'
log.debug("Fetched offset %s for partition %d", offsets[0], part)
result.append((TopicPartition(topic, part), offsets[0]))
elif error_type in (Errors.NotLeaderForPartitionError,
Errors.UnknownTopicOrPartitionError):
log.debug("Attempt to fetch offsets for partition %s failed due"
" to obsolete leadership information, retrying.",
str(partitions))
future.failure(error_type(partitions))
else:
log.warning("Attempt to fetch offsets for partition %s failed due to:"
" %s", partitions, error_type)
future.failure(error_type(partitions))
future.success(result)
def fetch_committed_offsets(self, partitions):
"""Fetch the current committed offsets for specified partitions
Arguments:
partitions (list of TopicPartition): partitions to fetch
Returns:
dict: {TopicPartition: OffsetAndMetadata}
"""
if not partitions:
return {}
while True:
self._ensure_coordinator_known()
# contact coordinator to fetch committed offsets
future = self._send_offset_fetch_request(partitions)
self._client.poll(future=future)
if future.succeeded():
return future.value
if not future.retriable():
raise future.exception # pylint: disable-msg=raising-bad-type
time.sleep(self.config['retry_backoff_ms'] / 1000.0)
def _send_offset_fetch_request(self, partitions):
"""Fetch the committed offsets for a set of partitions.
This is a non-blocking call. The returned future can be polled to get
the actual offsets returned from the broker.
Arguments:
partitions (list of TopicPartition): the partitions to fetch
Returns:
Future: resolves to dict of offsets: {TopicPartition: int}
"""
assert self.config['api_version'] >= (0, 8, 1), 'Unsupported Broker API'
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
if not partitions:
return Future().success({})
elif self._coordinator_unknown():
return Future().failure(Errors.GroupCoordinatorNotAvailableError)
node_id = self._coordinator_id
# Verify node is ready
if not self._client.ready(node_id):
log.debug("Node %s not ready -- failing offset fetch request",
node_id)
return Future().failure(Errors.NodeNotReadyError)
log.debug("Group %s fetching committed offsets for partitions: %s",
self.group_id, partitions)
# construct the request
topic_partitions = collections.defaultdict(set)
for tp in partitions:
topic_partitions[tp.topic].add(tp.partition)
if self.config['api_version'] >= (0, 8, 2):
request = OffsetFetchRequest[1](
self.group_id,
list(topic_partitions.items())
)
else:
request = OffsetFetchRequest[0](
self.group_id,
list(topic_partitions.items())
)
# send the request with a callback
future = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_offset_fetch_response, future)
_f.add_errback(self._failed_request, node_id, request, future)
return future
def _handle_offset_fetch_response(self, future, response):
offsets = {}
for topic, partitions in response.topics:
for partition, offset, metadata, error_code in partitions:
tp = TopicPartition(topic, partition)
error_type = Errors.for_code(error_code)
if error_type is not Errors.NoError:
error = error_type()
log.debug("Group %s failed to fetch offset for partition"
" %s: %s", self.group_id, tp, error)
if error_type is Errors.GroupLoadInProgressError:
# just retry
future.failure(error)
elif error_type is Errors.NotCoordinatorForGroupError:
# re-discover the coordinator and retry
self._coordinator_dead()
future.failure(error)
elif error_type in (Errors.UnknownMemberIdError,
Errors.IllegalGenerationError):
future.failure(error)
elif error_type is Errors.UnknownTopicOrPartitionError:
log.warning("OffsetFetchRequest -- unknown topic %s"
" (have you committed any offsets yet?)",
topic)
continue
else:
log.error("Unknown error fetching offsets for %s: %s",
tp, error)
future.failure(error)
return
elif offset >= 0:
# record the position with the offset
# (-1 indicates no committed offset to fetch)
offsets[tp] = OffsetAndMetadata(offset, metadata)
else:
log.debug("Group %s has no committed offset for partition"
" %s", self.group_id, tp)
future.success(offsets)
def get(self):
topic_partitions = self._client.cluster.partitions_for_topic(self.topic)
if not topic_partitions:
future = self._client.cluster.request_update()
log.info("No partitions available, performing metadata update.")
self._client.poll(future=future)
return {}
partitions = [TopicPartition(self.topic, partition_id) for partition_id in topic_partitions]
offsets = self.offsets(partitions, -1)
committed = self.fetch_committed_offsets(partitions)
lags = {}
for tp, offset in six.iteritems(offsets):
commit_offset = committed[tp] if tp in committed else 0
numerical = commit_offset if isinstance(commit_offset, int) else commit_offset.offset
lag = offset - numerical
pid = tp.partition if isinstance(tp, TopicPartition) else tp
log.debug("Lag for %s (%s): %s, %s, %s", self.topic, pid, offset, commit_offset, lag)
lags[pid] = lag
return lags
class KafkaConsumerLag:
def __init__(self, bootstrap_servers):
self.client = KafkaClient(bootstrap_servers=bootstrap_servers)
self.client.check_version()
def _send(self, broker_id, request, response_type=None):
f = self.client.send(broker_id, request)
response = self.client.poll(future=f)
if response_type:
if response and len(response) > 0:
for r in response:
if isinstance(r, response_type):
return r
else:
if response and len(response) > 0:
return response[0]
return None
def check(self, group_topics=None, discovery=None):
"""
{
"<group>": {
"state": <str>,
"topics": {
"<topic>": {
"consumer_lag": <int>,
"partitions": {
"<partition>": {
"offset_first": <int>,
"offset_consumed": <int>,
"offset_last": <int>,
"lag": <int>
}
}
}
}
}
}
:param persist_groups:
:return: consumer statistics
"""
cluster = self.client.cluster
brokers = cluster.brokers()
# Consumer group ID -> list(topics)
if group_topics is None:
group_topics = {}
if discovery is None:
discovery = True
else:
group_topics = copy.deepcopy(group_topics)
# Set of consumer group IDs
consumer_groups = set(group_topics.iterkeys())
# Set of all known topics
topics = set(itertools.chain(*group_topics.itervalues()))
# Consumer group ID -> coordinating broker
consumer_coordinator = {}
# Coordinating broker - > list(consumer group IDs)
coordinator_consumers = {}
results = {}
for consumer_group in group_topics.iterkeys():
results[consumer_group] = {'state': None, 'topics': {}}
# Ensure connections to all brokers
for broker in brokers:
while not self.client.is_ready(broker.nodeId):
self.client.ready(broker.nodeId)
# Collect all active consumer groups
if discovery:
for broker in brokers:
response = self._send(broker.nodeId, _ListGroupsRequest(), _ListGroupsResponse)
if response:
for group in response.groups:
consumer_groups.add(group[0])
# Identify which broker is coordinating each consumer group
for group in consumer_groups:
response = self._send(next(iter(brokers)).nodeId, _GroupCoordinatorRequest(group), _GroupCoordinatorResponse)
if response:
consumer_coordinator[group] = response.coordinator_id
if response.coordinator_id not in coordinator_consumers:
coordinator_consumers[response.coordinator_id] = []
coordinator_consumers[response.coordinator_id].append(group)
# Populate consumer groups into dict
for group in consumer_groups:
if group not in group_topics:
group_topics[group] = []
# Add groups to results dict
for group, topic_list in group_topics.iteritems():
results[group] = {'state': None, 'topics': {}}
# Identify group information and topics read by each consumer group
for coordinator, consumers in coordinator_consumers.iteritems():
response = self._send(coordinator, _DescribeGroupsRequest(consumers), _DescribeGroupsResponse)
for group in response.groups:
if group[1] in results:
results[group[1]]['state'] = group[2]
# TODO Also include member data?
if discovery:
members = group[5]
for member in members:
try:
assignment = MemberAssignment.decode(member[4])
if assignment:
for partition in assignment.partition_assignment:
topic = partition[0]
# Add topic to topic set
topics.add(topic)
# Add topic to group
group_topics[group[1]].append(topic)
except:
pass
# Add topics to groups in results dict
for group, topic_list in group_topics.iteritems():
for topic in topic_list:
results[group]['topics'][topic] = {'consumer_lag': 0, 'partitions': {}}
# For storing the latest offset for all partitions of all topics
# topic -> partition -> offset
start_offsets = {}
end_offsets = {}
# Identify all the topic partitions that each broker is leader for
# and request next new offset for each partition
for broker, partitions in cluster._broker_partitions.iteritems():
# topic -> List(partition, time, max_offsets)
request_partitions = {}
for tp in partitions:
if tp.topic in topics:
if tp.topic not in request_partitions:
request_partitions[tp.topic] = []
# Time value '-2' is to get the offset for first available message
request_partitions[tp.topic].append((tp.partition, -2, 1))
# List(topic, List(partition, time, max_offsets))
topic_partitions = []
for tp in request_partitions.iteritems():
topic_partitions.append(tp)
# Request partition start offsets
response = self._send(broker, _OffsetRequest(-1, topic_partitions), _OffsetResponse)
if response:
for offset in response.topics:
topic = offset[0]
if topic not in start_offsets:
start_offsets[topic] = {}
for p in offset[1]:
start_offsets[topic][p[0]] = p[2][0]
for tp in topic_partitions:
for i, ptm in enumerate(tp[1]):
# Time value '-1' is to get the offset for next new message
tp[1][i] = (ptm[0], -1, 1)
# Request partition end offsets
response = self._send(broker, _OffsetRequest(-1, topic_partitions), _OffsetResponse)
if response:
for offset in response.topics:
topic = offset[0]
if topic not in end_offsets:
end_offsets[topic] = {}
for p in offset[1]:
end_offsets[topic][p[0]] = p[2][0]
# Populate with offset values
for group, topics in group_topics.iteritems():
coordinator = consumer_coordinator[group]
# topic -> list(partition)
request_partitions = {}
for topic in topics:
results[group]['topics'][topic]['consumer_lag'] = 0
results[group]['topics'][topic]['partitions'] = {}
if topic in start_offsets:
for p in start_offsets[topic]:
results[group]['topics'][topic]['partitions'][p] = {
'offset_first': start_offsets[topic][p],
'offset_last': end_offsets[topic][p],
'offset_consumed': 0,
'lag' : 0}
if topic not in request_partitions:
request_partitions[topic] = []
request_partitions[topic].append(p)
# List(topic -> list(partition))
topic_partitions = []
for tp in request_partitions.iteritems():
topic_partitions.append(tp)
response = self._send(coordinator, _OffsetFetchRequest(group, topic_partitions), _OffsetFetchResponse)
if response:
for offset in response.topics:
topic = offset[0]
offsets = offset[1]
if topic not in results[group]['topics']:
continue
for p_offset in offsets:
partition = p_offset[0]
offset_consumed = p_offset[1]
p_results = results[group]['topics'][topic]['partitions'][partition]
if offset_consumed != -1:
p_results['offset_consumed'] = offset_consumed
p_results['lag'] = p_results['offset_last'] - offset_consumed
else:
p_results['offset_consumed'] = 0
p_results['lag'] = p_results['offset_last'] - p_results['offset_first']
results[group]['topics'][topic]['consumer_lag'] += p_results['lag']
return results
def close(self):
if self.client:
self.client.close()
class KafkaAdminClient(object):
"""A class for administering the Kafka cluster.
Warning:
This is an unstable interface that was recently added and is subject to
change without warning. In particular, many methods currently return
raw protocol tuples. In future releases, we plan to make these into
nicer, more pythonic objects. Unfortunately, this will likely break
those interfaces.
The KafkaAdminClient class will negotiate for the latest version of each message
protocol format supported by both the kafka-python client library and the
Kafka broker. Usage of optional fields from protocol versions that are not
supported by the broker will result in IncompatibleBrokerVersion exceptions.
Use of this class requires a minimum broker version >= 0.10.0.0.
Keyword Arguments:
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the consumer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client. Also
submitted to GroupCoordinator for logging with respect to
consumer group administration. Default: 'kafka-python-{version}'
reconnect_backoff_ms (int): The amount of time in milliseconds to
wait before attempting to reconnect to a given host.
Default: 50.
reconnect_backoff_max_ms (int): The maximum amount of time in
milliseconds to wait when reconnecting to a broker that has
repeatedly failed to connect. If provided, the backoff per host
will increase exponentially for each consecutive connection
failure, up to this maximum. To avoid connection storms, a
randomization factor of 0.2 will be applied to the backoff
resulting in a random range between 20% below and 20% above
the computed value. Default: 1000.
request_timeout_ms (int): Client request timeout in milliseconds.
Default: 30000.
connections_max_idle_ms: Close idle connections after the number of
milliseconds specified by this config. The broker closes idle
connections after connections.max.idle.ms, so this avoids hitting
unexpected socket disconnected errors on the client.
Default: 540000
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
max_in_flight_requests_per_connection (int): Requests are pipelined
to kafka brokers up to this number of maximum requests per
broker connection. Default: 5.
receive_buffer_bytes (int): The size of the TCP receive buffer
(SO_RCVBUF) to use when reading data. Default: None (relies on
system defaults). Java client defaults to 32768.
send_buffer_bytes (int): The size of the TCP send buffer
(SO_SNDBUF) to use when sending data. Default: None (relies on
system defaults). Java client defaults to 131072.
socket_options (list): List of tuple-arguments to socket.setsockopt
to apply to broker connection sockets. Default:
[(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)]
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
security_protocol (str): Protocol used to communicate with brokers.
Valid values are: PLAINTEXT, SSL. Default: PLAINTEXT.
ssl_context (ssl.SSLContext): Pre-configured SSLContext for wrapping
socket connections. If provided, all other ssl_* configurations
will be ignored. Default: None.
ssl_check_hostname (bool): Flag to configure whether SSL handshake
should verify that the certificate matches the broker's hostname.
Default: True.
ssl_cafile (str): Optional filename of CA file to use in certificate
veriication. Default: None.
ssl_certfile (str): Optional filename of file in PEM format containing
the client certificate, as well as any CA certificates needed to
establish the certificate's authenticity. Default: None.
ssl_keyfile (str): Optional filename containing the client private key.
Default: None.
ssl_password (str): Optional password to be used when loading the
certificate chain. Default: None.
ssl_crlfile (str): Optional filename containing the CRL to check for
certificate expiration. By default, no CRL check is done. When
providing a file, only the leaf certificate will be checked against
this CRL. The CRL can only be checked with Python 3.4+ or 2.7.9+.
Default: None.
api_version (tuple): Specify which Kafka API version to use. If set
to None, KafkaClient will attempt to infer the broker version by
probing various APIs. Example: (0, 10, 2). Default: None
api_version_auto_timeout_ms (int): number of milliseconds to throw a
timeout exception from the constructor when checking the broker
api version. Only applies if api_version is None
selector (selectors.BaseSelector): Provide a specific selector
implementation to use for I/O multiplexing.
Default: selectors.DefaultSelector
metrics (kafka.metrics.Metrics): Optionally provide a metrics
instance for capturing network IO stats. Default: None.
metric_group_prefix (str): Prefix for metric names. Default: ''
sasl_mechanism (str): Authentication mechanism when security_protocol
is configured for SASL_PLAINTEXT or SASL_SSL. Valid values are:
PLAIN, GSSAPI, OAUTHBEARER.
sasl_plain_username (str): username for sasl PLAIN authentication.
Required if sasl_mechanism is PLAIN.
sasl_plain_password (str): password for sasl PLAIN authentication.
Required if sasl_mechanism is PLAIN.
sasl_kerberos_service_name (str): Service name to include in GSSAPI
sasl mechanism handshake. Default: 'kafka'
sasl_oauth_token_provider (AbstractTokenProvider): OAuthBearer token provider
instance. (See kafka.oauth.abstract). Default: None
"""
DEFAULT_CONFIG = {
# client configs
'bootstrap_servers': 'localhost',
'client_id': 'kafka-python-' + __version__,
'request_timeout_ms': 30000,
'connections_max_idle_ms': 9 * 60 * 1000,
'reconnect_backoff_ms': 50,
'reconnect_backoff_max_ms': 1000,
'max_in_flight_requests_per_connection': 5,
'receive_buffer_bytes': None,
'send_buffer_bytes': None,
'socket_options': [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)],
'sock_chunk_bytes': 4096, # undocumented experimental option
'sock_chunk_buffer_count': 1000, # undocumented experimental option
'retry_backoff_ms': 100,
'metadata_max_age_ms': 300000,
'security_protocol': 'PLAINTEXT',
'ssl_context': None,
'ssl_check_hostname': True,
'ssl_cafile': None,
'ssl_certfile': None,
'ssl_keyfile': None,
'ssl_password': None,
'ssl_crlfile': None,
'api_version': None,
'api_version_auto_timeout_ms': 2000,
'selector': selectors.DefaultSelector,
'sasl_mechanism': None,
'sasl_plain_username': None,
'sasl_plain_password': None,
'sasl_kerberos_service_name': 'kafka',
'sasl_oauth_token_provider': None,
# metrics configs
'metric_reporters': [],
'metrics_num_samples': 2,
'metrics_sample_window_ms': 30000,
}
def __init__(self, **configs):
log.debug("Starting KafkaAdminClient with configuration: %s", configs)
extra_configs = set(configs).difference(self.DEFAULT_CONFIG)
if extra_configs:
raise KafkaConfigurationError(
"Unrecognized configs: {}".format(extra_configs))
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
# Configure metrics
metrics_tags = {'client-id': self.config['client_id']}
metric_config = MetricConfig(
samples=self.config['metrics_num_samples'],
time_window_ms=self.config['metrics_sample_window_ms'],
tags=metrics_tags)
reporters = [
reporter() for reporter in self.config['metric_reporters']
]
self._metrics = Metrics(metric_config, reporters)
self._client = KafkaClient(metrics=self._metrics,
metric_group_prefix='admin',
**self.config)
# Get auto-discovered version from client if necessary
if self.config['api_version'] is None:
self.config['api_version'] = self._client.config['api_version']
self._closed = False
self._refresh_controller_id()
log.debug("KafkaAdminClient started.")
def close(self):
"""Close the KafkaAdminClient connection to the Kafka broker."""
if not hasattr(self, '_closed') or self._closed:
log.info("KafkaAdminClient already closed.")
return
self._metrics.close()
self._client.close()
self._closed = True
log.debug("KafkaAdminClient is now closed.")
def _matching_api_version(self, operation):
"""Find the latest version of the protocol operation supported by both
this library and the broker.
This resolves to the lesser of either the latest api version this
library supports, or the max version supported by the broker.
:param operation: A list of protocol operation versions from kafka.protocol.
:return: The max matching version number between client and broker.
"""
version = min(
len(operation) - 1,
self._client.get_api_versions()[operation[0].API_KEY][1])
if version < self._client.get_api_versions()[operation[0].API_KEY][0]:
# max library version is less than min broker version. Currently,
# no Kafka versions specify a min msg version. Maybe in the future?
raise IncompatibleBrokerVersion(
"No version of the '{}' Kafka protocol is supported by both the client and broker."
.format(operation.__name__))
return version
def _validate_timeout(self, timeout_ms):
"""Validate the timeout is set or use the configuration default.
:param timeout_ms: The timeout provided by api call, in milliseconds.
:return: The timeout to use for the operation.
"""
return timeout_ms or self.config['request_timeout_ms']
def _refresh_controller_id(self):
"""Determine the Kafka cluster controller."""
version = self._matching_api_version(MetadataRequest)
if 1 <= version <= 6:
request = MetadataRequest[version]()
future = self._send_request_to_node(
self._client.least_loaded_node(), request)
self._wait_for_futures([future])
response = future.value
controller_id = response.controller_id
# verify the controller is new enough to support our requests
controller_version = self._client.check_version(controller_id)
if controller_version < (0, 10, 0):
raise IncompatibleBrokerVersion(
"The controller appears to be running Kafka {}. KafkaAdminClient requires brokers >= 0.10.0.0."
.format(controller_version))
self._controller_id = controller_id
else:
raise UnrecognizedBrokerVersion(
"Kafka Admin interface cannot determine the controller using MetadataRequest_v{}."
.format(version))
def _find_group_coordinator_id(self, group_id):
"""Find the broker node_id of the coordinator of the given group.
Sends a FindCoordinatorRequest message to the cluster. Will block until
the FindCoordinatorResponse is received. Any errors are immediately
raised.
:param group_id: The consumer group ID. This is typically the group
name as a string.
:return: The node_id of the broker that is the coordinator.
"""
# Note: Java may change how this is implemented in KAFKA-6791.
#
# TODO add support for dynamically picking version of
# GroupCoordinatorRequest which was renamed to FindCoordinatorRequest.
# When I experimented with this, GroupCoordinatorResponse_v1 didn't
# match GroupCoordinatorResponse_v0 and I couldn't figure out why.
gc_request = GroupCoordinatorRequest[0](group_id)
future = self._send_request_to_node(self._client.least_loaded_node(),
gc_request)
self._wait_for_futures([future])
gc_response = future.value
# use the extra error checking in add_group_coordinator() rather than
# immediately returning the group coordinator.
success = self._client.cluster.add_group_coordinator(
group_id, gc_response)
if not success:
error_type = Errors.for_code(gc_response.error_code)
assert error_type is not Errors.NoError
# Note: When error_type.retriable, Java will retry... see
# KafkaAdminClient's handleFindCoordinatorError method
raise error_type(
"Could not identify group coordinator for group_id '{}' from response '{}'."
.format(group_id, gc_response))
group_coordinator = self._client.cluster.coordinator_for_group(
group_id)
# will be None if the coordinator was never populated, which should never happen here
assert group_coordinator is not None
# will be -1 if add_group_coordinator() failed... but by this point the
# error should have been raised.
assert group_coordinator != -1
return group_coordinator
def _send_request_to_node(self, node_id, request):
"""Send a Kafka protocol message to a specific broker.
Returns a future that may be polled for status and results.
:param node_id: The broker id to which to send the message.
:param request: The message to send.
:return: A future object that may be polled for status and results.
:exception: The exception if the message could not be sent.
"""
while not self._client.ready(node_id):
# poll until the connection to broker is ready, otherwise send()
# will fail with NodeNotReadyError
self._client.poll()
return self._client.send(node_id, request)
def _send_request_to_controller(self, request):
"""Send a Kafka protocol message to the cluster controller.
Will block until the message result is received.
:param request: The message to send.
:return: The Kafka protocol response for the message.
"""
tries = 2 # in case our cached self._controller_id is outdated
while tries:
tries -= 1
future = self._send_request_to_node(self._controller_id, request)
self._wait_for_futures([future])
response = future.value
# In Java, the error fieldname is inconsistent:
# - CreateTopicsResponse / CreatePartitionsResponse uses topic_errors
# - DeleteTopicsResponse uses topic_error_codes
# So this is a little brittle in that it assumes all responses have
# one of these attributes and that they always unpack into
# (topic, error_code) tuples.
topic_error_tuples = (response.topic_errors if hasattr(
response, 'topic_errors') else response.topic_error_codes)
# Also small py2/py3 compatibility -- py3 can ignore extra values
# during unpack via: for x, y, *rest in list_of_values. py2 cannot.
# So for now we have to map across the list and explicitly drop any
# extra values (usually the error_message)
for topic, error_code in map(lambda e: e[:2], topic_error_tuples):
error_type = Errors.for_code(error_code)
if tries and error_type is NotControllerError:
# No need to inspect the rest of the errors for
# non-retriable errors because NotControllerError should
# either be thrown for all errors or no errors.
self._refresh_controller_id()
break
elif error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'.".format(
request, response))
else:
return response
raise RuntimeError(
"This should never happen, please file a bug with full stacktrace if encountered"
)
@staticmethod
def _convert_new_topic_request(new_topic):
return (
new_topic.name, new_topic.num_partitions,
new_topic.replication_factor, [
(partition_id, replicas) for partition_id, replicas in
new_topic.replica_assignments.items()
],
[(config_key, config_value)
for config_key, config_value in new_topic.topic_configs.items()])
def create_topics(self, new_topics, timeout_ms=None, validate_only=False):
"""Create new topics in the cluster.
:param new_topics: A list of NewTopic objects.
:param timeout_ms: Milliseconds to wait for new topics to be created
before the broker returns.
:param validate_only: If True, don't actually create new topics.
Not supported by all versions. Default: False
:return: Appropriate version of CreateTopicResponse class.
"""
version = self._matching_api_version(CreateTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version == 0:
if validate_only:
raise IncompatibleBrokerVersion(
"validate_only requires CreateTopicsRequest >= v1, which is not supported by Kafka {}."
.format(self.config['api_version']))
request = CreateTopicsRequest[version](create_topic_requests=[
self._convert_new_topic_request(new_topic)
for new_topic in new_topics
],
timeout=timeout_ms)
elif version <= 2:
request = CreateTopicsRequest[version](create_topic_requests=[
self._convert_new_topic_request(new_topic)
for new_topic in new_topics
],
timeout=timeout_ms,
validate_only=validate_only)
else:
raise NotImplementedError(
"Support for CreateTopics v{} has not yet been added to KafkaAdminClient."
.format(version))
# TODO convert structs to a more pythonic interface
# TODO raise exceptions if errors
return self._send_request_to_controller(request)
def delete_topics(self, topics, timeout_ms=None):
"""Delete topics from the cluster.
:param topics: A list of topic name strings.
:param timeout_ms: Milliseconds to wait for topics to be deleted
before the broker returns.
:return: Appropriate version of DeleteTopicsResponse class.
"""
version = self._matching_api_version(DeleteTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version <= 1:
request = DeleteTopicsRequest[version](topics=topics,
timeout=timeout_ms)
response = self._send_request_to_controller(request)
else:
raise NotImplementedError(
"Support for DeleteTopics v{} has not yet been added to KafkaAdminClient."
.format(version))
return response
# list topics functionality is in ClusterMetadata
# Note: if implemented here, send the request to the least_loaded_node()
# describe topics functionality is in ClusterMetadata
# Note: if implemented here, send the request to the controller
# describe cluster functionality is in ClusterMetadata
# Note: if implemented here, send the request to the least_loaded_node()
# describe_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
# create_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
# delete_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
@staticmethod
def _convert_describe_config_resource_request(config_resource):
return (config_resource.resource_type, config_resource.name, [
config_key
for config_key, config_value in config_resource.configs.items()
] if config_resource.configs else None)
def describe_configs(self, config_resources, include_synonyms=False):
"""Fetch configuration parameters for one or more Kafka resources.
:param config_resources: An list of ConfigResource objects.
Any keys in ConfigResource.configs dict will be used to filter the
result. Setting the configs dict to None will get all values. An
empty dict will get zero values (as per Kafka protocol).
:param include_synonyms: If True, return synonyms in response. Not
supported by all versions. Default: False.
:return: Appropriate version of DescribeConfigsResponse class.
"""
version = self._matching_api_version(DescribeConfigsRequest)
if version == 0:
if include_synonyms:
raise IncompatibleBrokerVersion(
"include_synonyms requires DescribeConfigsRequest >= v1, which is not supported by Kafka {}."
.format(self.config['api_version']))
request = DescribeConfigsRequest[version](resources=[
self._convert_describe_config_resource_request(config_resource)
for config_resource in config_resources
])
elif version == 1:
request = DescribeConfigsRequest[version](
resources=[
self._convert_describe_config_resource_request(
config_resource)
for config_resource in config_resources
],
include_synonyms=include_synonyms)
else:
raise NotImplementedError(
"Support for DescribeConfigs v{} has not yet been added to KafkaAdminClient."
.format(version))
future = self._send_request_to_node(self._client.least_loaded_node(),
request)
self._wait_for_futures([future])
return future.value
@staticmethod
def _convert_alter_config_resource_request(config_resource):
return (config_resource.resource_type, config_resource.name, [
(config_key, config_value)
for config_key, config_value in config_resource.configs.items()
])
def alter_configs(self, config_resources):
"""Alter configuration parameters of one or more Kafka resources.
Warning:
This is currently broken for BROKER resources because those must be
sent to that specific broker, versus this always picks the
least-loaded node. See the comment in the source code for details.
We would happily accept a PR fixing this.
:param config_resources: A list of ConfigResource objects.
:return: Appropriate version of AlterConfigsResponse class.
"""
version = self._matching_api_version(AlterConfigsRequest)
if version == 0:
request = AlterConfigsRequest[version](resources=[
self._convert_alter_config_resource_request(config_resource)
for config_resource in config_resources
])
else:
raise NotImplementedError(
"Support for AlterConfigs v{} has not yet been added to KafkaAdminClient."
.format(version))
# TODO the Java client has the note:
# // We must make a separate AlterConfigs request for every BROKER resource we want to alter
# // and send the request to that specific broker. Other resources are grouped together into
# // a single request that may be sent to any broker.
#
# So this is currently broken as it always sends to the least_loaded_node()
future = self._send_request_to_node(self._client.least_loaded_node(),
request)
self._wait_for_futures([future])
return future.value
# alter replica logs dir protocol not yet implemented
# Note: have to lookup the broker with the replica assignment and send the request to that broker
# describe log dirs protocol not yet implemented
# Note: have to lookup the broker with the replica assignment and send the request to that broker
@staticmethod
def _convert_create_partitions_request(topic_name, new_partitions):
return (topic_name, (new_partitions.total_count,
new_partitions.new_assignments))
def create_partitions(self,
topic_partitions,
timeout_ms=None,
validate_only=False):
"""Create additional partitions for an existing topic.
:param topic_partitions: A map of topic name strings to NewPartition objects.
:param timeout_ms: Milliseconds to wait for new partitions to be
created before the broker returns.
:param validate_only: If True, don't actually create new partitions.
Default: False
:return: Appropriate version of CreatePartitionsResponse class.
"""
version = self._matching_api_version(CreatePartitionsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version == 0:
request = CreatePartitionsRequest[version](
topic_partitions=[
self._convert_create_partitions_request(
topic_name, new_partitions)
for topic_name, new_partitions in topic_partitions.items()
],
timeout=timeout_ms,
validate_only=validate_only)
else:
raise NotImplementedError(
"Support for CreatePartitions v{} has not yet been added to KafkaAdminClient."
.format(version))
return self._send_request_to_controller(request)
# delete records protocol not yet implemented
# Note: send the request to the partition leaders
# create delegation token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# renew delegation token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# expire delegation_token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# describe delegation_token protocol not yet implemented
# Note: send the request to the least_loaded_node()
def describe_consumer_groups(self, group_ids, group_coordinator_id=None):
"""Describe a set of consumer groups.
Any errors are immediately raised.
:param group_ids: A list of consumer group IDs. These are typically the
group names as strings.
:param group_coordinator_id: The node_id of the groups' coordinator
broker. If set to None, it will query the cluster for each group to
find that group's coordinator. Explicitly specifying this can be
useful for avoiding extra network round trips if you already know
the group coordinator. This is only useful when all the group_ids
have the same coordinator, otherwise it will error. Default: None.
:return: A list of group descriptions. For now the group descriptions
are the raw results from the DescribeGroupsResponse. Long-term, we
plan to change this to return namedtuples as well as decoding the
partition assignments.
"""
group_descriptions = []
futures = []
version = self._matching_api_version(DescribeGroupsRequest)
for group_id in group_ids:
if group_coordinator_id is not None:
this_groups_coordinator_id = group_coordinator_id
else:
this_groups_coordinator_id = self._find_group_coordinator_id(
group_id)
if version <= 1:
# Note: KAFKA-6788 A potential optimization is to group the
# request per coordinator and send one request with a list of
# all consumer groups. Java still hasn't implemented this
# because the error checking is hard to get right when some
# groups error and others don't.
request = DescribeGroupsRequest[version](groups=(group_id, ))
futures.append(
self._send_request_to_node(this_groups_coordinator_id,
request))
else:
raise NotImplementedError(
"Support for DescribeGroups v{} has not yet been added to KafkaAdminClient."
.format(version))
self._wait_for_futures(futures)
for future in futures:
response = future.value
assert len(response.groups) == 1
# TODO need to implement converting the response tuple into
# a more accessible interface like a namedtuple and then stop
# hardcoding tuple indices here. Several Java examples,
# including KafkaAdminClient.java
group_description = response.groups[0]
error_code = group_description[0]
error_type = Errors.for_code(error_code)
# Java has the note: KAFKA-6789, we can retry based on the error code
if error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'.".format(
request, response))
# TODO Java checks the group protocol type, and if consumer
# (ConsumerProtocol.PROTOCOL_TYPE) or empty string, it decodes
# the members' partition assignments... that hasn't yet been
# implemented here so just return the raw struct results
group_descriptions.append(group_description)
return group_descriptions
def list_consumer_groups(self, broker_ids=None):
"""List all consumer groups known to the cluster.
This returns a list of Consumer Group tuples. The tuples are
composed of the consumer group name and the consumer group protocol
type.
Only consumer groups that store their offsets in Kafka are returned.
The protocol type will be an empty string for groups created using
Kafka < 0.9 APIs because, although they store their offsets in Kafka,
they don't use Kafka for group coordination. For groups created using
Kafka >= 0.9, the protocol type will typically be "consumer".
As soon as any error is encountered, it is immediately raised.
:param broker_ids: A list of broker node_ids to query for consumer
groups. If set to None, will query all brokers in the cluster.
Explicitly specifying broker(s) can be useful for determining which
consumer groups are coordinated by those broker(s). Default: None
:return list: List of tuples of Consumer Groups.
:exception GroupCoordinatorNotAvailableError: The coordinator is not
available, so cannot process requests.
:exception GroupLoadInProgressError: The coordinator is loading and
hence can't process requests.
"""
# While we return a list, internally use a set to prevent duplicates
# because if a group coordinator fails after being queried, and its
# consumer groups move to new brokers that haven't yet been queried,
# then the same group could be returned by multiple brokers.
consumer_groups = set()
futures = []
if broker_ids is None:
broker_ids = [
broker.nodeId for broker in self._client.cluster.brokers()
]
version = self._matching_api_version(ListGroupsRequest)
if version <= 2:
request = ListGroupsRequest[version]()
for broker_id in broker_ids:
futures.append(self._send_request_to_node(broker_id, request))
self._wait_for_futures(futures)
for future in futures:
response = future.value
error_type = Errors.for_code(response.error_code)
if error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'.".format(
request, response))
consumer_groups.update(response.groups)
else:
raise NotImplementedError(
"Support for ListGroups v{} has not yet been added to KafkaAdminClient."
.format(version))
return list(consumer_groups)
def list_consumer_group_offsets(self,
group_id,
group_coordinator_id=None,
partitions=None):
"""Fetch Consumer Group Offsets.
Note:
This does not verify that the group_id or partitions actually exist
in the cluster.
As soon as any error is encountered, it is immediately raised.
:param group_id: The consumer group id name for which to fetch offsets.
:param group_coordinator_id: The node_id of the group's coordinator
broker. If set to None, will query the cluster to find the group
coordinator. Explicitly specifying this can be useful to prevent
that extra network round trip if you already know the group
coordinator. Default: None.
:param partitions: A list of TopicPartitions for which to fetch
offsets. On brokers >= 0.10.2, this can be set to None to fetch all
known offsets for the consumer group. Default: None.
:return dictionary: A dictionary with TopicPartition keys and
OffsetAndMetada values. Partitions that are not specified and for
which the group_id does not have a recorded offset are omitted. An
offset value of `-1` indicates the group_id has no offset for that
TopicPartition. A `-1` can only happen for partitions that are
explicitly specified.
"""
group_offsets_listing = {}
if group_coordinator_id is None:
group_coordinator_id = self._find_group_coordinator_id(group_id)
version = self._matching_api_version(OffsetFetchRequest)
if version <= 3:
if partitions is None:
if version <= 1:
raise ValueError(
"""OffsetFetchRequest_v{} requires specifying the
partitions for which to fetch offsets. Omitting the
partitions is only supported on brokers >= 0.10.2.
For details, see KIP-88.""".format(version))
topics_partitions = None
else:
# transform from [TopicPartition("t1", 1), TopicPartition("t1", 2)] to [("t1", [1, 2])]
topics_partitions_dict = defaultdict(set)
for topic, partition in partitions:
topics_partitions_dict[topic].add(partition)
topics_partitions = list(six.iteritems(topics_partitions_dict))
request = OffsetFetchRequest[version](group_id, topics_partitions)
future = self._send_request_to_node(group_coordinator_id, request)
self._wait_for_futures([future])
response = future.value
if version > 1: # OffsetFetchResponse_v1 lacks a top-level error_code
error_type = Errors.for_code(response.error_code)
if error_type is not Errors.NoError:
# optionally we could retry if error_type.retriable
raise error_type(
"Request '{}' failed with response '{}'.".format(
request, response))
# transform response into a dictionary with TopicPartition keys and
# OffsetAndMetada values--this is what the Java AdminClient returns
for topic, partitions in response.topics:
for partition, offset, metadata, error_code in partitions:
error_type = Errors.for_code(error_code)
if error_type is not Errors.NoError:
raise error_type(
"Unable to fetch offsets for group_id {}, topic {}, partition {}"
.format(group_id, topic, partition))
group_offsets_listing[TopicPartition(
topic,
partition)] = OffsetAndMetadata(offset, metadata)
else:
raise NotImplementedError(
"Support for OffsetFetch v{} has not yet been added to KafkaAdminClient."
.format(version))
return group_offsets_listing
# delete groups protocol not yet implemented
# Note: send the request to the group's coordinator.
def _wait_for_futures(self, futures):
while not all(future.succeeded() for future in futures):
for future in futures:
self._client.poll(future=future)
if future.failed():
raise future.exception # pylint: disable-msg=raising-bad-type
class KafkaConsumerLag:
def __init__(self, bootstrap_servers):
self.client = KafkaClient(bootstrap_servers=bootstrap_servers)
self.client.check_version()
def _send(self, broker_id, request, response_type=None):
f = self.client.send(broker_id, request)
response = self.client.poll(future=f)
if response_type:
if response and len(response) > 0:
for r in response:
if isinstance(r, response_type):
return r
else:
if response and len(response) > 0:
return response[0]
return None
def check(self, group_topics=None, discovery=None):
"""
{
"<group>": {
"state": <str>,
"topics": {
"<topic>": {
"consumer_lag": <int>,
"partitions": {
"<partition>": {
"offset_first": <int>,
"offset_consumed": <int>,
"offset_last": <int>,
"lag": <int>
}
}
}
}
}
}
:param persist_groups:
:return: consumer statistics
"""
cluster = self.client.cluster
brokers = cluster.brokers()
# Consumer group ID -> list(topics)
if group_topics is None:
group_topics = {}
if discovery is None:
discovery = True
else:
group_topics = copy.deepcopy(group_topics)
# Set of consumer group IDs
consumer_groups = set(group_topics.iterkeys())
# Set of all known topics
topics = set(itertools.chain(*group_topics.itervalues()))
# Consumer group ID -> coordinating broker
consumer_coordinator = {}
# Coordinating broker - > list(consumer group IDs)
coordinator_consumers = {}
results = {}
for consumer_group in group_topics.iterkeys():
results[consumer_group] = {'state': None, 'topics': {}}
# Ensure connections to all brokers
for broker in brokers:
while not self.client.is_ready(broker.nodeId):
self.client.ready(broker.nodeId)
# Collect all active consumer groups
if discovery:
for broker in brokers:
response = self._send(broker.nodeId, _ListGroupsRequest(),
_ListGroupsResponse)
if response:
for group in response.groups:
consumer_groups.add(group[0])
# Identify which broker is coordinating each consumer group
for group in consumer_groups:
response = self._send(
next(iter(brokers)).nodeId, _GroupCoordinatorRequest(group),
_GroupCoordinatorResponse)
if response:
consumer_coordinator[group] = response.coordinator_id
if response.coordinator_id not in coordinator_consumers:
coordinator_consumers[response.coordinator_id] = []
coordinator_consumers[response.coordinator_id].append(group)
# Populate consumer groups into dict
for group in consumer_groups:
if group not in group_topics:
group_topics[group] = []
# Add groups to results dict
for group, topic_list in group_topics.iteritems():
results[group] = {'state': None, 'topics': {}}
# Identify group information and topics read by each consumer group
for coordinator, consumers in coordinator_consumers.iteritems():
response = self._send(coordinator,
_DescribeGroupsRequest(consumers),
_DescribeGroupsResponse)
for group in response.groups:
if group[1] in results:
results[group[1]]['state'] = group[2]
# TODO Also include member data?
if discovery:
members = group[5]
for member in members:
try:
assignment = MemberAssignment.decode(member[4])
if assignment:
for partition in assignment.partition_assignment:
topic = partition[0]
# Add topic to topic set
topics.add(topic)
# Add topic to group
group_topics[group[1]].append(topic)
except:
pass
# Add topics to groups in results dict
for group, topic_list in group_topics.iteritems():
for topic in topic_list:
results[group]['topics'][topic] = {
'consumer_lag': 0,
'partitions': {}
}
# For storing the latest offset for all partitions of all topics
# topic -> partition -> offset
start_offsets = {}
end_offsets = {}
# Identify all the topic partitions that each broker is leader for
# and request next new offset for each partition
for broker, partitions in cluster._broker_partitions.iteritems():
# topic -> List(partition, time, max_offsets)
request_partitions = {}
for tp in partitions:
if tp.topic in topics:
if tp.topic not in request_partitions:
request_partitions[tp.topic] = []
# Time value '-2' is to get the offset for first available message
request_partitions[tp.topic].append((tp.partition, -2, 1))
# List(topic, List(partition, time, max_offsets))
topic_partitions = []
for tp in request_partitions.iteritems():
topic_partitions.append(tp)
# Request partition start offsets
response = self._send(broker, _OffsetRequest(-1, topic_partitions),
_OffsetResponse)
if response:
for offset in response.topics:
topic = offset[0]
if topic not in start_offsets:
start_offsets[topic] = {}
for p in offset[1]:
start_offsets[topic][p[0]] = p[2][0]
for tp in topic_partitions:
for i, ptm in enumerate(tp[1]):
# Time value '-1' is to get the offset for next new message
tp[1][i] = (ptm[0], -1, 1)
# Request partition end offsets
response = self._send(broker, _OffsetRequest(-1, topic_partitions),
_OffsetResponse)
if response:
for offset in response.topics:
topic = offset[0]
if topic not in end_offsets:
end_offsets[topic] = {}
for p in offset[1]:
end_offsets[topic][p[0]] = p[2][0]
# Populate with offset values
for group, topics in group_topics.iteritems():
coordinator = consumer_coordinator[group]
# topic -> list(partition)
request_partitions = {}
for topic in topics:
results[group]['topics'][topic]['consumer_lag'] = 0
results[group]['topics'][topic]['partitions'] = {}
if topic in start_offsets:
for p in start_offsets[topic]:
results[group]['topics'][topic]['partitions'][p] = {
'offset_first': start_offsets[topic][p],
'offset_last': end_offsets[topic][p],
'offset_consumed': 0,
'lag': 0
}
if topic not in request_partitions:
request_partitions[topic] = []
request_partitions[topic].append(p)
# List(topic -> list(partition))
topic_partitions = []
for tp in request_partitions.iteritems():
topic_partitions.append(tp)
response = self._send(coordinator,
_OffsetFetchRequest(group, topic_partitions),
_OffsetFetchResponse)
if response:
for offset in response.topics:
topic = offset[0]
offsets = offset[1]
if topic not in results[group]['topics']:
continue
for p_offset in offsets:
partition = p_offset[0]
offset_consumed = p_offset[1]
p_results = results[group]['topics'][topic][
'partitions'][partition]
if offset_consumed != -1:
p_results['offset_consumed'] = offset_consumed
p_results['lag'] = p_results[
'offset_last'] - offset_consumed
else:
p_results['offset_consumed'] = 0
p_results['lag'] = p_results[
'offset_last'] - p_results['offset_first']
results[group]['topics'][topic][
'consumer_lag'] += p_results['lag']
return results
def close(self):
if self.client:
self.client.close()
class KafkaAdmin(object):
"""An class for administering the kafka cluster.
The KafkaAdmin class will negotiate for the latest version of each message protocol format supported
by both the kafka-python client library and the kafka broker. Usage of optional fields from protocol
versions that are not supported by the broker will result in UnsupportedVersionError exceptions.
Use of this class requires a minimum broker version >= 0.10.0.0.
Keyword Arguments:
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the consumer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client. Also
submitted to GroupCoordinator for logging with respect to
consumer group administration. Default: 'kafka-python-{version}'
reconnect_backoff_ms (int): The amount of time in milliseconds to
wait before attempting to reconnect to a given host.
Default: 50.
reconnect_backoff_max_ms (int): The maximum amount of time in
milliseconds to wait when reconnecting to a broker that has
repeatedly failed to connect. If provided, the backoff per host
will increase exponentially for each consecutive connection
failure, up to this maximum. To avoid connection storms, a
randomization factor of 0.2 will be applied to the backoff
resulting in a random range between 20% below and 20% above
the computed value. Default: 1000.
request_timeout_ms (int): Client request timeout in milliseconds.
Default: 30000.
connections_max_idle_ms: Close idle connections after the number of
milliseconds specified by this config. The broker closes idle
connections after connections.max.idle.ms, so this avoids hitting
unexpected socket disconnected errors on the client.
Default: 540000
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
max_in_flight_requests_per_connection (int): Requests are pipelined
to kafka brokers up to this number of maximum requests per
broker connection. Default: 5.
receive_buffer_bytes (int): The size of the TCP receive buffer
(SO_RCVBUF) to use when reading data. Default: None (relies on
system defaults). Java client defaults to 32768.
send_buffer_bytes (int): The size of the TCP send buffer
(SO_SNDBUF) to use when sending data. Default: None (relies on
system defaults). Java client defaults to 131072.
socket_options (list): List of tuple-arguments to socket.setsockopt
to apply to broker connection sockets. Default:
[(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)]
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
security_protocol (str): Protocol used to communicate with brokers.
Valid values are: PLAINTEXT, SSL. Default: PLAINTEXT.
ssl_context (ssl.SSLContext): Pre-configured SSLContext for wrapping
socket connections. If provided, all other ssl_* configurations
will be ignored. Default: None.
ssl_check_hostname (bool): Flag to configure whether SSL handshake
should verify that the certificate matches the broker's hostname.
Default: True.
ssl_cafile (str): Optional filename of CA file to use in certificate
veriication. Default: None.
ssl_certfile (str): Optional filename of file in PEM format containing
the client certificate, as well as any CA certificates needed to
establish the certificate's authenticity. Default: None.
ssl_keyfile (str): Optional filename containing the client private key.
Default: None.
ssl_password (str): Optional password to be used when loading the
certificate chain. Default: None.
ssl_crlfile (str): Optional filename containing the CRL to check for
certificate expiration. By default, no CRL check is done. When
providing a file, only the leaf certificate will be checked against
this CRL. The CRL can only be checked with Python 3.4+ or 2.7.9+.
Default: None.
api_version (tuple): Specify which Kafka API version to use. If set
to None, KafkaClient will attempt to infer the broker version by
probing various APIs. Example: (0, 10, 2). Default: None
api_version_auto_timeout_ms (int): number of milliseconds to throw a
timeout exception from the constructor when checking the broker
api version. Only applies if api_version is None
selector (selectors.BaseSelector): Provide a specific selector
implementation to use for I/O multiplexing.
Default: selectors.DefaultSelector
metrics (kafka.metrics.Metrics): Optionally provide a metrics
instance for capturing network IO stats. Default: None.
metric_group_prefix (str): Prefix for metric names. Default: ''
sasl_mechanism (str): string picking sasl mechanism when security_protocol
is SASL_PLAINTEXT or SASL_SSL. Currently only PLAIN is supported.
Default: None
sasl_plain_username (str): username for sasl PLAIN authentication.
Default: None
sasl_plain_password (str): password for sasl PLAIN authentication.
Default: None
sasl_kerberos_service_name (str): Service name to include in GSSAPI
sasl mechanism handshake. Default: 'kafka'
"""
DEFAULT_CONFIG = {
# client configs
'bootstrap_servers': 'localhost',
'client_id': 'kafka-python-' + __version__,
'request_timeout_ms': 30000,
'connections_max_idle_ms': 9 * 60 * 1000,
'reconnect_backoff_ms': 50,
'reconnect_backoff_max_ms': 1000,
'max_in_flight_requests_per_connection': 5,
'receive_buffer_bytes': None,
'send_buffer_bytes': None,
'socket_options': [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)],
'sock_chunk_bytes': 4096, # undocumented experimental option
'sock_chunk_buffer_count': 1000, # undocumented experimental option
'retry_backoff_ms': 100,
'metadata_max_age_ms': 300000,
'security_protocol': 'PLAINTEXT',
'ssl_context': None,
'ssl_check_hostname': True,
'ssl_cafile': None,
'ssl_certfile': None,
'ssl_keyfile': None,
'ssl_password': None,
'ssl_crlfile': None,
'api_version': None,
'api_version_auto_timeout_ms': 2000,
'selector': selectors.DefaultSelector,
'sasl_mechanism': None,
'sasl_plain_username': None,
'sasl_plain_password': None,
'sasl_kerberos_service_name': 'kafka',
# metrics configs
'metric_reporters': [],
'metrics_num_samples': 2,
'metrics_sample_window_ms': 30000,
}
def __init__(self, **configs):
log.debug("Starting Kafka administration interface")
extra_configs = set(configs).difference(self.DEFAULT_CONFIG)
if extra_configs:
raise KafkaConfigurationError("Unrecognized configs: %s" %
extra_configs)
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
# api_version was previously a str. accept old format for now
if isinstance(self.config['api_version'], str):
deprecated = self.config['api_version']
if deprecated == 'auto':
self.config['api_version'] = None
else:
self.config['api_version'] = tuple(
map(int, deprecated.split('.')))
log.warning(
'use api_version=%s [tuple] -- "%s" as str is deprecated',
str(self.config['api_version']), deprecated)
# Configure metrics
metrics_tags = {'client-id': self.config['client_id']}
metric_config = MetricConfig(
samples=self.config['metrics_num_samples'],
time_window_ms=self.config['metrics_sample_window_ms'],
tags=metrics_tags)
reporters = [
reporter() for reporter in self.config['metric_reporters']
]
self._metrics = Metrics(metric_config, reporters)
self._client = KafkaClient(metrics=self._metrics,
metric_group_prefix='admin',
**self.config)
# Get auto-discovered version from client if necessary
if self.config['api_version'] is None:
self.config['api_version'] = self._client.config['api_version']
self._closed = False
self._refresh_controller_id()
log.debug('Kafka administration interface started')
def close(self):
"""Close the administration connection to the kafka broker"""
if not hasattr(self, '_closed') or self._closed:
log.info('Kafka administration interface already closed')
return
self._metrics.close()
self._client.close()
self._closed = True
log.debug('Kafka administartion interface has closed')
def _matching_api_version(self, operation):
"""Find matching api version, the lesser of either the latest api version the library supports, or
the max version supported by the broker
:param operation: An operation array from kafka.protocol
:return: The max matching version number between client and broker
"""
version = min(
len(operation) - 1,
self._client.get_api_versions()[operation[0].API_KEY][1])
if version < self._client.get_api_versions()[operation[0].API_KEY][0]:
# max library version is less than min broker version. Not sure any brokers
# actually set a min version greater than 0 right now, tho. But maybe in the future?
raise UnsupportedVersionError(
"Could not find matching protocol version for {}".format(
operation.__name__))
return version
def _validate_timeout(self, timeout_ms):
"""Validate the timeout is set or use the configuration default
:param timeout_ms: The timeout provided by api call, in milliseconds
:return: The timeout to use for the operation
"""
return timeout_ms or self.config['request_timeout_ms']
def _refresh_controller_id(self):
"""Determine the kafka cluster controller
"""
response = self._send_request_to_node(self._client.least_loaded_node(),
MetadataRequest[1]([]))
self._controller_id = response.controller_id
version = self._client.check_version(self._controller_id)
if version < (0, 10, 0):
raise UnsupportedVersionError(
"Kafka Admin interface not supported for cluster controller version {} < 0.10.0.0"
.format(version))
def _send_request_to_node(self, node, request):
"""Send a kafka protocol message to a specific broker. Will block until the message result is received.
:param node: The broker id to which to send the message
:param request: The message to send
:return: The kafka protocol response for the message
:exception: The exception if the message could not be sent
"""
while not self._client.ready(node):
# connection to broker not ready, poll until it is or send will fail with NodeNotReadyError
self._client.poll()
future = self._client.send(node, request)
self._client.poll(future=future)
if future.succeeded():
return future.value
else:
raise future.exception # pylint: disable-msg=raising-bad-type
def _send(self, request):
"""Send a kafka protocol message to the cluster controller. Will block until the message result is received.
:param request: The message to send
:return The kafka protocol response for the message
:exception NodeNotReadyError: If the controller connection can't be established
"""
remaining_tries = 2
while remaining_tries > 0:
remaining_tries = remaining_tries - 1
try:
return self._send_request_to_node(self._controller_id, request)
except (NotControllerError, KafkaConnectionError) as e:
# controller changed? refresh it
self._refresh_controller_id()
raise NodeNotReadyError(self._controller_id)
@staticmethod
def _convert_new_topic_request(new_topic):
return (
new_topic.name, new_topic.num_partitions,
new_topic.replication_factor, [
(partition_id, replicas) for partition_id, replicas in
new_topic.replica_assignments.items()
],
[(config_key, config_value)
for config_key, config_value in new_topic.topic_configs.items()])
def create_topics(self, new_topics, timeout_ms=None, validate_only=None):
"""Create new topics in the cluster.
:param new_topics: Array of NewTopic objects
:param timeout_ms: Milliseconds to wait for new topics to be created before broker returns
:param validate_only: If True, don't actually create new topics. Not supported by all versions.
:return: Appropriate version of CreateTopicResponse class
"""
version = self._matching_api_version(CreateTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version == 0:
if validate_only:
raise UnsupportedVersionError(
"validate_only not supported on cluster version {}".format(
self.config['api_version']))
request = CreateTopicsRequest[version](create_topic_requests=[
self._convert_new_topic_request(new_topic)
for new_topic in new_topics
],
timeout=timeout_ms)
elif version <= 2:
validate_only = validate_only or False
request = CreateTopicsRequest[version](create_topic_requests=[
self._convert_new_topic_request(new_topic)
for new_topic in new_topics
],
timeout=timeout_ms,
validate_only=validate_only)
else:
raise UnsupportedVersionError(
"missing implementation of CreateTopics for library supported version {}"
.format(version))
return self._send(request)
def delete_topics(self, topics, timeout_ms=None):
"""Delete topics from the cluster
:param topics: Array of topic name strings
:param timeout_ms: Milliseconds to wait for topics to be deleted before broker returns
:return: Appropriate version of DeleteTopicsResponse class
"""
version = self._matching_api_version(DeleteTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version <= 1:
request = DeleteTopicsRequest[version](topics=topics,
timeout=timeout_ms)
else:
raise UnsupportedVersionError(
"missing implementation of DeleteTopics for library supported version {}"
.format(version))
return self._send(request)
# list topics functionality is in ClusterMetadata
# describe topics functionality is in ClusterMetadata
# describe cluster functionality is in ClusterMetadata
# describe_acls protocol not implemented
# create_acls protocol not implemented
# delete_acls protocol not implemented
@staticmethod
def _convert_describe_config_resource_request(config_resource):
return (config_resource.resource_type, config_resource.name, [
config_key
for config_key, config_value in config_resource.configs.items()
] if config_resource.configs else None)
def describe_configs(self, config_resources, include_synonyms=None):
"""Fetch configuration parameters for one or more kafka resources.
:param config_resources: An array of ConfigResource objects.
Any keys in ConfigResource.configs dict will be used to filter the result. The configs dict should be None
to get all values. An empty dict will get zero values (as per kafka protocol).
:param include_synonyms: If True, return synonyms in response. Not supported by all versions.
:return: Appropriate version of DescribeConfigsResponse class
"""
version = self._matching_api_version(DescribeConfigsRequest)
if version == 0:
if include_synonyms:
raise UnsupportedVersionError(
"include_synonyms not supported on cluster version {}".
format(self.config['api_version']))
request = DescribeConfigsRequest[version](resources=[
self._convert_describe_config_resource_request(config_resource)
for config_resource in config_resources
])
elif version <= 1:
include_synonyms = include_synonyms or False
request = DescribeConfigsRequest[version](
resources=[
self._convert_describe_config_resource_request(
config_resource)
for config_resource in config_resources
],
include_synonyms=include_synonyms)
else:
raise UnsupportedVersionError(
"missing implementation of DescribeConfigs for library supported version {}"
.format(version))
return self._send(request)
@staticmethod
def _convert_alter_config_resource_request(config_resource):
return (config_resource.resource_type, config_resource.name, [
(config_key, config_value)
for config_key, config_value in config_resource.configs.items()
])
def alter_configs(self, config_resources):
"""Alter configuration parameters of one or more kafka resources.
:param config_resources: An array of ConfigResource objects.
:return: Appropriate version of AlterConfigsResponse class
"""
version = self._matching_api_version(AlterConfigsRequest)
if version == 0:
request = AlterConfigsRequest[version](resources=[
self._convert_alter_config_resource_request(config_resource)
for config_resource in config_resources
])
else:
raise UnsupportedVersionError(
"missing implementation of AlterConfigs for library supported version {}"
.format(version))
return self._send(request)
# alter replica logs dir protocol not implemented
# describe log dirs protocol not implemented
@staticmethod
def _convert_create_partitions_request(topic_name, new_partitions):
return (topic_name, (new_partitions.total_count,
new_partitions.new_assignments))
def create_partitions(self,
topic_partitions,
timeout_ms=None,
validate_only=None):
"""Create additional partitions for an existing topic.
:param topic_partitions: A map of topic name strings to NewPartition objects
:param timeout_ms: Milliseconds to wait for new partitions to be created before broker returns
:param validate_only: If True, don't actually create new partitions.
:return: Appropriate version of CreatePartitionsResponse class
"""
version = self._matching_api_version(CreatePartitionsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
validate_only = validate_only or False
if version == 0:
request = CreatePartitionsRequest[version](
topic_partitions=[
self._convert_create_partitions_request(
topic_name, new_partitions)
for topic_name, new_partitions in topic_partitions.items()
],
timeout=timeout_ms,
validate_only=validate_only)
else:
raise UnsupportedVersionError(
"missing implementation of CreatePartitions for library supported version {}"
.format(version))
return self._send(request)
# delete records protocol not implemented
# create delegation token protocol not implemented
# renew delegation token protocol not implemented
# expire delegation_token protocol not implemented
# describe delegation_token protocol not implemented
def describe_consumer_groups(self, group_ids):
"""Describe a set of consumer groups.
:param group_ids: A list of consumer group id names
:return: Appropriate version of DescribeGroupsResponse class
"""
version = self._matching_api_version(DescribeGroupsRequest)
if version <= 1:
request = DescribeGroupsRequest[version](groups=group_ids)
else:
raise UnsupportedVersionError(
"missing implementation of DescribeGroups for library supported version {}"
.format(version))
return self._send(request)
def list_consumer_groups(self):
"""List all consumer groups known to the cluster.
:return: Appropriate version of ListGroupsResponse class
"""
version = self._matching_api_version(ListGroupsRequest)
if version <= 1:
request = ListGroupsRequest[version]()
else:
raise UnsupportedVersionError(
"missing implementation of ListGroups for library supported version {}"
.format(version))
return self._send(request)
class KafkaManager:
"""
A class used to interact with Kafka and Zookeeper
and easily retrive useful information
"""
MAX_RETRY = 10
MAX_POLL_RETRIES = 3
MAX_ZK_RETRIES = 5
TOPIC_RESOURCE_ID = 2
DEFAULT_TIMEOUT = 15000
SUCCESS_CODE = 0
ZK_REASSIGN_NODE = '/admin/reassign_partitions'
ZK_TOPIC_PARTITION_NODE = '/brokers/topics/'
ZK_TOPIC_CONFIGURATION_NODE = '/config/topics/'
# Not used yet.
ZK_TOPIC_DELETION_NODE = '/admin/delete_topics/'
def __init__(self, module, **configs):
self.module = module
self.zk_client = None
self.client = KafkaClient(**configs)
self.refresh()
def init_zk_client(self, **configs):
"""
Zookeeper client initialization
"""
self.zk_client = KazooClient(**configs)
self.zk_client.start()
def close_zk_client(self):
"""
Closes Zookeeper client
"""
self.zk_client.stop()
def close(self):
"""
Closes Kafka client
"""
self.client.close()
def refresh(self):
"""
Refresh topics state
"""
fut = self.client.cluster.request_update()
self.client.poll(future=fut)
if not fut.succeeded():
self.close()
self.module.fail_json(
msg='Error while updating topic state from Kafka server: %s.' %
fut.exception)
def create_topic(self,
name,
partitions,
replica_factor,
replica_assignment=[],
config_entries=[],
timeout=None):
"""
Creates a topic
Usable for Kafka version >= 0.10.1
"""
if timeout is None:
timeout = self.DEFAULT_TIMEOUT
request = CreateTopicsRequest_v0(create_topic_requests=[
(name, partitions, replica_factor, replica_assignment,
config_entries)
],
timeout=timeout)
response = self.send_request_and_get_response(request)
for topic, error_code in response.topic_errors:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while creating topic %s. '
'Error key is %s, %s.' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
def delete_topic(self, name, timeout=None):
"""
Deletes a topic
Usable for Kafka version >= 0.10.1
Need to know which broker is controller for topic
"""
if timeout is None:
timeout = self.DEFAULT_TIMEOUT
request = DeleteTopicsRequest_v0(topics=[name], timeout=timeout)
response = self.send_request_and_get_response(request)
for topic, error_code in response.topic_error_codes:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while deleting topic %s. '
'Error key is: %s, %s. '
'Is option \'delete.topic.enable\' set to true on '
' your Kafka server?' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
@staticmethod
def _convert_create_acls_resource_request_v0(acl_resource):
if acl_resource.operation == ACLOperation.ANY:
raise IllegalArgumentError("operation must not be ANY")
if acl_resource.permission_type == ACLPermissionType.ANY:
raise IllegalArgumentError("permission_type must not be ANY")
return (acl_resource.resource_type, acl_resource.name,
acl_resource.principal, acl_resource.host,
acl_resource.operation, acl_resource.permission_type)
@staticmethod
def _convert_create_acls_resource_request_v1(acl_resource):
if acl_resource.operation == ACLOperation.ANY:
raise IllegalArgumentError("operation must not be ANY")
if acl_resource.permission_type == ACLPermissionType.ANY:
raise IllegalArgumentError("permission_type must not be ANY")
return (acl_resource.resource_type, acl_resource.name,
acl_resource.pattern_type, acl_resource.principal,
acl_resource.host, acl_resource.operation,
acl_resource.permission_type)
@staticmethod
def _convert_delete_acls_resource_request_v0(acl_resource):
return (acl_resource.resource_type, acl_resource.name,
acl_resource.principal, acl_resource.host,
acl_resource.operation, acl_resource.permission_type)
@staticmethod
def _convert_delete_acls_resource_request_v1(acl_resource):
return (acl_resource.resource_type, acl_resource.name,
acl_resource.pattern_type, acl_resource.principal,
acl_resource.host, acl_resource.operation,
acl_resource.permission_type)
def describe_acls(self, acl_resource, api_version):
"""Describe a set of ACLs
"""
if api_version < parse_version('2.0.0'):
request = DescribeAclsRequest_v0(
resource_type=acl_resource.resource_type,
resource_name=acl_resource.name,
principal=acl_resource.principal,
host=acl_resource.host,
operation=acl_resource.operation,
permission_type=acl_resource.permission_type)
else:
request = DescribeAclsRequest_v1(
resource_type=acl_resource.resource_type,
resource_name=acl_resource.name,
resource_pattern_type_filter=acl_resource.pattern_type,
principal=acl_resource.principal,
host=acl_resource.host,
operation=acl_resource.operation,
permission_type=acl_resource.permission_type)
response = self.send_request_and_get_response(request)
if response.error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while describing ACL %s. '
'Error %s: %s.' %
(acl_resource, response.error_code, response.error_message))
return response.resources
def create_acls(self, acl_resources, api_version):
"""Create a set of ACLs"""
if api_version < parse_version('2.0.0'):
request = CreateAclsRequest_v0(creations=[
self._convert_create_acls_resource_request_v0(acl_resource)
for acl_resource in acl_resources
])
else:
request = CreateAclsRequest_v1(creations=[
self._convert_create_acls_resource_request_v1(acl_resource)
for acl_resource in acl_resources
])
response = self.send_request_and_get_response(request)
for error_code, error_message in response.creation_responses:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while creating ACL %s. '
'Error %s: %s.' %
(acl_resources, error_code, error_message))
def delete_acls(self, acl_resources, api_version):
"""Delete a set of ACLSs"""
if api_version < parse_version('2.0.0'):
request = DeleteAclsRequest_v0(filters=[
self._convert_delete_acls_resource_request_v0(acl_resource)
for acl_resource in acl_resources
])
else:
request = DeleteAclsRequest_v1(filters=[
self._convert_delete_acls_resource_request_v1(acl_resource)
for acl_resource in acl_resources
])
response = self.send_request_and_get_response(request)
for error_code, error_message, _ in response.filter_responses:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while deleting ACL %s. '
'Error %s: %s.' %
(acl_resources, error_code, error_message))
def send_request_and_get_response(self, request):
"""
Sends a Kafka protocol request and returns
the associated response
"""
try:
node_id = self.get_controller()
except UndefinedController:
self.module.fail_json(
msg='Cannot determine a controller for your current Kafka '
'server. Is your Kafka server running and available on '
'\'%s\' with security protocol \'%s\'?' %
(self.client.config['bootstrap_servers'],
self.client.config['security_protocol']))
except Exception as e:
self.module.fail_json(
msg='Cannot determine a controller for your current Kafka '
'server. Is your Kafka server running and available on '
'\'%s\' with security protocol \'%s\'? Are you using the '
'library versions from given \'requirements.txt\'? '
'Exception was: %s' %
(self.client.config['bootstrap_servers'],
self.client.config['security_protocol'], e))
if self.connection_check(node_id):
future = self.client.send(node_id, request)
self.client.poll(future=future)
if future.succeeded():
return future.value
else:
self.close()
self.module.fail_json(
msg='Error while sending request %s to Kafka server: %s.' %
(request, future.exception))
else:
self.close()
self.module.fail_json(
msg='Connection is not ready, please check your client '
'and server configurations.')
def get_controller(self):
"""
Returns the current controller
"""
if self.client.cluster.controller is not None:
node_id, _host, _port, _rack = self.client.cluster.controller
return node_id
else:
raise UndefinedController(
'Cant get a controller for this cluster.')
def get_controller_id_for_topic(self, topic_name):
"""
Returns current controller for topic
"""
request = MetadataRequest_v1(topics=[topic_name])
response = self.send_request_and_get_response(request)
return response.controller_id
def get_config_for_topic(self, topic_name, config_names):
"""
Returns responses with configuration
Usable with Kafka version >= 0.11.0
"""
request = DescribeConfigsRequest_v0(resources=[(self.TOPIC_RESOURCE_ID,
topic_name,
config_names)])
return self.send_request_and_get_response(request)
def get_responses_from_client(self, connection_sleep=1):
"""
Obtains response from server using poll()
It may need some times to get the response, so we had some retries
"""
retries = 0
if self.get_awaiting_request() > 0:
while retries < self.MAX_POLL_RETRIES:
resp = self.client.poll()
if resp:
return resp
time.sleep(connection_sleep)
retries += 1
self.close()
self.module.fail_json(
msg='Error while getting responses : no response to request '
'was obtained, please check your client and server '
'configurations.')
else:
self.close()
self.module.fail_json(
msg='No pending request, please check your client and server '
'configurations.')
def get_topics(self):
"""
Returns the topics list
"""
return self.client.cluster.topics()
def get_total_partitions_for_topic(self, topic):
"""
Returns the number of partitions for topic
"""
return len(self.client.cluster.partitions_for_topic(topic))
def get_partitions_for_topic(self, topic):
"""
Returns all partitions for topic, with information
TODO do not use private property anymore
"""
return self.client.cluster._partitions[topic]
def get_total_brokers(self):
"""
Returns number of brokers available
"""
return len(self.client.cluster.brokers())
def get_brokers(self):
"""
Returns all brokers
"""
return self.client.cluster.brokers()
def get_api_version(self):
"""
Returns Kafka server version
"""
major, minor, patch = self.client.config['api_version']
return '%s.%s.%s' % (major, minor, patch)
def get_awaiting_request(self):
"""
Returns the number of requests currently in the queue
"""
return self.client.in_flight_request_count()
def connection_check(self, node_id, connection_sleep=0.1):
"""
Checks that connection with broker is OK and that it is possible to
send requests
Since the maybe_connect() function used in ready() is 'async', we
need to manually call the poll() function to establish the connection
to the node
"""
retries = 0
if not self.client.ready(node_id):
while retries < self.MAX_RETRY:
self.client.poll()
if self.client.ready(node_id):
return True
time.sleep(connection_sleep)
retries += 1
return False
return True
def is_topic_configuration_need_update(self, topic_name, topic_conf):
"""
Checks whether topic's options need to be updated or not.
Since the DescribeConfigsRequest does not give all current
configuration entries for a topic, we need to use Zookeeper.
Requires zk connection.
"""
current_config, _zk_stats = self.zk_client.get(
self.ZK_TOPIC_CONFIGURATION_NODE + topic_name)
current_config = json.loads(current_config)['config']
if len(topic_conf) != len(current_config.keys()):
return True
else:
for conf_name, conf_value in topic_conf:
if (conf_name not in current_config.keys()
or str(conf_value) != str(current_config[conf_name])):
return True
return False
def is_topic_partitions_need_update(self, topic_name, partitions):
"""
Checks whether topic's partitions need to be updated or not.
"""
total_partitions = self.get_total_partitions_for_topic(topic_name)
need_update = False
if partitions != total_partitions:
if partitions > total_partitions:
# increasing partition number
need_update = True
else:
# decreasing partition number, which is not possible
self.close()
self.module.fail_json(
msg='Can\'t update \'%s\' topic partition from %s to %s :'
'only increase is possible.' %
(topic_name, total_partitions, partitions))
return need_update
def is_topic_replication_need_update(self, topic_name, replica_factor):
"""
Checks whether a topic replica needs to be updated or not.
"""
need_update = False
for _id, part in self.get_partitions_for_topic(topic_name).items():
_topic, _partition, _leader, replicas, _isr, _error = part
if len(replicas) != replica_factor:
need_update = True
return need_update
def update_topic_partitions(self, topic_name, partitions):
"""
Updates the topic partitions
Usable for Kafka version >= 1.0.0
Requires to be the sended to the current controller of the Kafka
cluster.
The request requires to precise the total number of partitions and
broker assignment for each new partition without forgeting replica.
See NewPartitions class for explanations
apache/kafka/clients/admin/NewPartitions.java#L53
"""
brokers = []
for node_id, _, _, _ in self.get_brokers():
brokers.append(int(node_id))
brokers_iterator = itertools.cycle(brokers)
topic, _, _, replicas, _, _ = (
self.get_partitions_for_topic(topic_name)[0])
total_replica = len(replicas)
old_partition = self.get_total_partitions_for_topic(topic_name)
assignments = []
for _new_partition in range(partitions - old_partition):
assignment = []
for _replica in range(total_replica):
assignment.append(next(brokers_iterator))
assignments.append(assignment)
request = CreatePartitionsRequest_v0(topic_partitions=[
(topic_name, (partitions, assignments))
],
timeout=self.DEFAULT_TIMEOUT,
validate_only=False)
response = self.send_request_and_get_response(request)
for topic, error_code, _error_message in response.topic_errors:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while updating topic \'%s\' partitions. '
'Error key is %s, %s. Request was %s.' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description,
str(request)))
self.refresh()
def update_topic_configuration(self, topic_name, topic_conf):
"""
Updates the topic configuration
Usable for Kafka version >= 0.11.0
Requires to be the sended to the current controller of the Kafka
cluster.
"""
request = AlterConfigsRequest_v0(resources=[(self.TOPIC_RESOURCE_ID,
topic_name, topic_conf)],
validate_only=False)
response = self.send_request_and_get_response(request)
for error_code, _, _, resource_name in response.resources:
if error_code != self.SUCCESS_CODE:
self.close()
self.module.fail_json(
msg='Error while updating topic \'%s\' configuration. '
'Error key is %s, %s' %
(resource_name, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
self.refresh()
def get_assignment_for_replica_factor_update(self, topic_name,
replica_factor):
"""
Generates a json assignment based on replica_factor given to update
replicas for a topic.
Uses all brokers available and distributes them as replicas using
a round robin method.
"""
all_replicas = []
assign = {'partitions': [], 'version': 1}
if replica_factor > self.get_total_brokers():
self.close()
self.close_zk_client()
self.module.fail_json(
msg='Error while updating topic \'%s\' replication factor : '
'replication factor \'%s\' is more than available brokers '
'\'%s\'' %
(topic_name, replica_factor, self.get_total_brokers()))
else:
for node_id, _, _, _ in self.get_brokers():
all_replicas.append(node_id)
brokers_iterator = itertools.cycle(all_replicas)
for _, part in self.get_partitions_for_topic(topic_name).items():
_, partition, _, _, _, _ = part
assign_tmp = {
'topic': topic_name,
'partition': partition,
'replicas': []
}
for _i in range(replica_factor):
assign_tmp['replicas'].append(next(brokers_iterator))
assign['partitions'].append(assign_tmp)
return bytes(str(json.dumps(assign)).encode('ascii'))
def get_assignment_for_partition_update(self, topic_name, partitions):
"""
Generates a json assignment based on number of partitions given to
update partitions for a topic.
Uses all brokers available and distributes them among partitions
using a round robin method.
"""
all_brokers = []
assign = {'partitions': {}, 'version': 1}
_, _, _, replicas, _, _ = self.get_partitions_for_topic(topic_name)[0]
total_replica = len(replicas)
for node_id, _host, _port, _rack in self.get_brokers():
all_brokers.append(node_id)
brokers_iterator = itertools.cycle(all_brokers)
for i in range(partitions):
assign_tmp = []
for _j in range(total_replica):
assign_tmp.append(next(brokers_iterator))
assign['partitions'][str(i)] = assign_tmp
return bytes(str(json.dumps(assign)).encode('ascii'))
def wait_for_znode_assignment(self, zk_sleep_time, zk_max_retries):
"""
Wait for the reassignment znode to be consumed by Kafka.
Raises `ReassignPartitionsTimeout` if `zk_max_retries` is reached.
"""
retries = 0
while (self.zk_client.exists(self.ZK_REASSIGN_NODE)
and retries < zk_max_retries):
retries += 1
time.sleep(zk_sleep_time)
if retries >= zk_max_retries:
raise ReassignPartitionsTimeout(
'The znode %s, is still present after %s tries, giving up.'
'Consider increasing your `zookeeper_max_retries` and/or '
'`zookeeper_sleep_time` parameters and check your cluster.',
self.ZK_REASSIGN_NODE, retries)
def update_admin_assignment(self, json_assignment, zk_sleep_time,
zk_max_retries):
"""
Updates the topic replica factor using a json assignment
Cf core/src/main/scala/kafka/admin/ReassignPartitionsCommand.scala#L580
1 - Send AlterReplicaLogDirsRequest to allow broker to create replica in
the right log dir later if the replica has not been created yet.
2 - Create reassignment znode so that controller will send
LeaderAndIsrRequest to create replica in the broker
def path = "/admin/reassign_partitions" ->
zk.create("/admin/reassign_partitions", b"a value")
case class ReplicaAssignment(
@BeanProperty @JsonProperty("topic") topic: String,
@BeanProperty @JsonProperty("partition") partition: Int,
@BeanProperty @JsonProperty("replicas") replicas: java.util.List[Int])
3 - Send AlterReplicaLogDirsRequest again to make sure broker will start
to move replica to the specified log directory.
It may take some time for controller to create replica in the broker
Retry if the replica has not been created.
It may be possible that the node '/admin/reassign_partitions' is already
there for another topic. That's why we need to check for its existence
and wait for its consumption if it is already present.
Requires zk connection.
"""
try:
self.wait_for_znode_assignment(zk_sleep_time, zk_max_retries)
self.zk_client.create(self.ZK_REASSIGN_NODE, json_assignment)
self.wait_for_znode_assignment(zk_sleep_time, zk_max_retries)
except ReassignPartitionsTimeout as e:
self.close()
self.close_zk_client()
self.module.fail_json(msg=str(e))
self.refresh()
def update_topic_assignment(self, json_assignment, zknode):
"""
Updates the topic partition assignment using a json assignment
Used when Kafka version < 1.0.0
Requires zk connection.
"""
if not self.zk_client.exists(zknode):
self.close()
self.close_zk_client()
self.module.fail_json(
msg='Error while updating assignment: zk node %s missing. '
'Is the topic name correct?' % (zknode))
self.zk_client.set(zknode, json_assignment)
self.refresh()
class KafkaManager:
"""
A class used to interact with Kafka and Zookeeper
and easily retrive useful information
"""
MAX_RETRY = 10
MAX_POLL_RETRIES = 3
MAX_ZK_RETRIES = 5
TOPIC_RESOURCE_ID = 2
DEFAULT_TIMEOUT = 15000
SUCCESS_CODE = 0
ZK_REASSIGN_NODE = '/admin/reassign_partitions'
ZK_TOPIC_PARTITION_NODE = '/brokers/topics/'
ZK_TOPIC_CONFIGURATION_NODE = '/config/topics/'
# Not used yet.
ZK_TOPIC_DELETION_NODE = '/admin/delete_topics/'
def __init__(self, **configs):
self.zk_client = None
self.zk_configuration = None
self.zookeeper_sleep_time = 5
self.zookeeper_max_retries = 5
self.kafka_sleep_time = 5
self.kafka_max_retries = 5
self.client = KafkaClient(**configs)
self.refresh()
def init_zk_client(self):
"""
Zookeeper client initialization
"""
if (self.zk_configuration is None
or self.zk_configuration['hosts'] == ''):
raise MissingConfiguration(
'\'zookeeper\', parameter is needed when '
'parameter \'state\' is \'present\' for resource '
'\'topic\'.')
try:
self.zk_client = KazooClient(**self.zk_configuration)
self.zk_client.start()
except Exception as e:
raise ZookeeperBroken(
msg='Error while initializing Zookeeper client : '
'%s. Is your Zookeeper server available and '
'running on \'%s\'?' % (e, self.zk_configuration['hosts']))
def close_zk_client(self):
"""
Closes Zookeeper client
"""
self.zk_client.stop()
def close_kafka_client(self):
"""
Closes Kafka client
"""
self.client.close()
def close(self):
"""
Closes any available client
"""
self.close_kafka_client()
if self.zk_client is not None:
self.close_zk_client()
def refresh(self):
"""
Refresh topics state
"""
fut = self.client.cluster.request_update()
self.client.poll(future=fut)
if not fut.succeeded():
raise UnableToRefreshState(
'Error while updating topic state from Kafka server: %s.' %
fut.exception)
def create_topic(self,
name,
partitions,
replica_factor,
replica_assignment=[],
config_entries=[],
timeout=None):
"""
Creates a topic
Usable for Kafka version >= 0.10.1
"""
if timeout is None:
timeout = self.DEFAULT_TIMEOUT
request = CreateTopicsRequest_v0(create_topic_requests=[
(name, partitions, replica_factor, replica_assignment,
config_entries)
],
timeout=timeout)
response = self.send_request_and_get_response(request)
for topic, error_code in response.topic_errors:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while creating topic %s. '
'Error key is %s, %s.' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
def delete_topic(self, name, timeout=None):
"""
Deletes a topic
Usable for Kafka version >= 0.10.1
Need to know which broker is controller for topic
"""
if timeout is None:
timeout = self.DEFAULT_TIMEOUT
request = DeleteTopicsRequest_v0(topics=[name], timeout=timeout)
response = self.send_request_and_get_response(request)
for topic, error_code in response.topic_error_codes:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while deleting topic %s. Error key is: %s, %s. '
'Is option \'delete.topic.enable\' set to true on '
' your Kafka server?' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
@staticmethod
def _convert_create_acls_resource_request_v0(acl_resource):
if acl_resource.operation == ACLOperation.ANY:
raise IllegalArgumentError("operation must not be ANY")
if acl_resource.permission_type == ACLPermissionType.ANY:
raise IllegalArgumentError("permission_type must not be ANY")
return (acl_resource.resource_type, acl_resource.name,
acl_resource.principal, acl_resource.host,
acl_resource.operation, acl_resource.permission_type)
@staticmethod
def _convert_create_acls_resource_request_v1(acl_resource):
if acl_resource.operation == ACLOperation.ANY:
raise IllegalArgumentError("operation must not be ANY")
if acl_resource.permission_type == ACLPermissionType.ANY:
raise IllegalArgumentError("permission_type must not be ANY")
return (acl_resource.resource_type, acl_resource.name,
acl_resource.pattern_type, acl_resource.principal,
acl_resource.host, acl_resource.operation,
acl_resource.permission_type)
@staticmethod
def _convert_delete_acls_resource_request_v0(acl_resource):
return (acl_resource.resource_type, acl_resource.name,
acl_resource.principal, acl_resource.host,
acl_resource.operation, acl_resource.permission_type)
@staticmethod
def _convert_delete_acls_resource_request_v1(acl_resource):
return (acl_resource.resource_type, acl_resource.name,
acl_resource.pattern_type, acl_resource.principal,
acl_resource.host, acl_resource.operation,
acl_resource.permission_type)
def describe_acls(self, acl_resource, api_version):
"""Describe a set of ACLs
"""
if api_version < parse_version('2.0.0'):
request = DescribeAclsRequest_v0(
resource_type=acl_resource.resource_type,
resource_name=acl_resource.name,
principal=acl_resource.principal,
host=acl_resource.host,
operation=acl_resource.operation,
permission_type=acl_resource.permission_type)
else:
request = DescribeAclsRequest_v1(
resource_type=acl_resource.resource_type,
resource_name=acl_resource.name,
resource_pattern_type_filter=acl_resource.pattern_type,
principal=acl_resource.principal,
host=acl_resource.host,
operation=acl_resource.operation,
permission_type=acl_resource.permission_type)
response = self.send_request_and_get_response(request)
if response.error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while describing ACL %s. Error %s: %s.' %
(acl_resource, response.error_code, response.error_message))
return response.resources
def create_acls(self, acl_resources, api_version):
"""Create a set of ACLs"""
if api_version < parse_version('2.0.0'):
request = CreateAclsRequest_v0(creations=[
self._convert_create_acls_resource_request_v0(acl_resource)
for acl_resource in acl_resources
])
else:
request = CreateAclsRequest_v1(creations=[
self._convert_create_acls_resource_request_v1(acl_resource)
for acl_resource in acl_resources
])
response = self.send_request_and_get_response(request)
for error_code, error_message in response.creation_responses:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while creating ACL %s. Error %s: %s.' %
(acl_resources, error_code, error_message))
def delete_acls(self, acl_resources, api_version):
"""Delete a set of ACLSs"""
if api_version < parse_version('2.0.0'):
request = DeleteAclsRequest_v0(filters=[
self._convert_delete_acls_resource_request_v0(acl_resource)
for acl_resource in acl_resources
])
else:
request = DeleteAclsRequest_v1(filters=[
self._convert_delete_acls_resource_request_v1(acl_resource)
for acl_resource in acl_resources
])
response = self.send_request_and_get_response(request)
for error_code, error_message, _ in response.filter_responses:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while deleting ACL %s. Error %s: %s.' %
(acl_resources, error_code, error_message))
def send_request_and_get_response(self, request, node_id=None):
"""
Sends a Kafka protocol request and returns
the associated response
"""
if node_id is None:
try:
node_id = self.get_controller()
except UndefinedController:
raise
except Exception as e:
raise KafkaManagerError(
'Cannot determine a controller for your current Kafka '
'server. Is your Kafka server running and available on '
'\'%s\' with security protocol \'%s\'? Are you using the '
'library versions from given \'requirements.txt\'? '
'Exception was: %s' %
(self.client.config['bootstrap_servers'],
self.client.config['security_protocol'], e))
if self.connection_check(node_id):
future = self.client.send(node_id, request)
self.client.poll(future=future)
if future.succeeded():
return future.value
else:
raise KafkaManagerError(
'Error while sending request %s to Kafka server: %s.' %
(request, future.exception))
else:
raise KafkaManagerError(
'Connection is not ready, please check your client '
'and server configurations.')
def get_controller(self):
"""
Returns the current controller
"""
if self.client.cluster.controller is not None:
node_id, _host, _port, _rack = self.client.cluster.controller
return node_id
else:
raise UndefinedController(
'Cannot determine a controller for your current Kafka '
'server. Is your Kafka server running and available on '
'\'%s\' with security protocol \'%s\'?' %
(self.client.config['bootstrap_servers'],
self.client.config['security_protocol']))
def get_config_for_topic(self, topic_name, config_names):
"""
Returns responses with configuration
Usable with Kafka version >= 0.11.0
"""
current_config = {}
if parse_version(self.get_api_version()) < parse_version('1.1.0'):
request = DescribeConfigsRequest_v0(
resources=[(self.TOPIC_RESOURCE_ID, topic_name, config_names)])
kafka_config = self.send_request_and_get_response(request)
for error_code, _, _, _, config_entries in kafka_config.resources:
for (config_names, config_values, _, is_default,
_) in config_entries:
if not is_default:
current_config[config_names] = config_values
else:
request = DescribeConfigsRequest_v1(
resources=[(self.TOPIC_RESOURCE_ID, topic_name, config_names)])
kafka_config = self.send_request_and_get_response(request)
for error_code, _, _, _, config_entries in kafka_config.resources:
for (config_names, config_values, _, config_source, _,
_) in config_entries:
# Dynamic topic config
if config_source == 1:
current_config[config_names] = config_values
return current_config
def get_topics(self):
"""
Returns the topics list
"""
return self.client.cluster.topics()
def get_total_partitions_for_topic(self, topic):
"""
Returns the number of partitions for topic
"""
return len(self.client.cluster.partitions_for_topic(topic))
def get_partitions_for_topic(self, topic):
"""
Returns all partitions for topic, with information
TODO do not use private property anymore
"""
return self.client.cluster._partitions[topic]
def get_total_brokers(self):
"""
Returns number of brokers available
"""
return len(self.client.cluster.brokers())
def get_brokers(self):
"""
Returns all brokers
"""
return self.client.cluster.brokers()
def get_api_version(self):
"""
Returns Kafka server version
"""
major, minor, patch = self.client.config['api_version']
return '%s.%s.%s' % (major, minor, patch)
def connection_check(self, node_id, connection_sleep=0.1):
"""
Checks that connection with broker is OK and that it is possible to
send requests
Since the maybe_connect() function used in ready() is 'async', we
need to manually call the poll() function to establish the connection
to the node
"""
retries = 0
if not self.client.ready(node_id):
while retries < self.MAX_RETRY:
self.client.poll()
if self.client.ready(node_id):
return True
time.sleep(connection_sleep)
retries += 1
return False
return True
def is_topic_configuration_need_update(self, topic_name, topic_conf):
"""
Checks whether topic's options need to be updated or not.
Since the DescribeConfigsRequest does not give all current
configuration entries for a topic, we need to use Zookeeper.
Requires zk connection.
"""
current_config = self.get_config_for_topic(topic_name, None)
if len(topic_conf) != len(current_config.keys()):
return True
else:
for conf_name, conf_value in topic_conf:
if (conf_name not in current_config.keys()
or str(conf_value) != str(current_config[conf_name])):
return True
return False
def is_topic_partitions_need_update(self, topic_name, partitions):
"""
Checks whether topic's partitions need to be updated or not.
"""
total_partitions = self.get_total_partitions_for_topic(topic_name)
need_update = False
if partitions != total_partitions:
if partitions > total_partitions:
# increasing partition number
need_update = True
else:
# decreasing partition number, which is not possible
raise KafkaManagerError(
'Can\'t update \'%s\' topic partition from %s to %s :'
'only increase is possible.' %
(topic_name, total_partitions, partitions))
return need_update
def is_topic_replication_need_update(self, topic_name, replica_factor):
"""
Checks whether a topic replica needs to be updated or not.
"""
need_update = False
for _id, part in self.get_partitions_for_topic(topic_name).items():
_topic, _partition, _leader, replicas, _isr, _error = part
if len(replicas) != replica_factor:
need_update = True
return need_update
def update_topic_partitions(self, topic_name, partitions):
"""
Updates the topic partitions
Usable for Kafka version >= 1.0.0
Requires to be the sended to the current controller of the Kafka
cluster.
The request requires to precise the total number of partitions and
broker assignment for each new partition without forgeting replica.
See NewPartitions class for explanations
apache/kafka/clients/admin/NewPartitions.java#L53
"""
brokers = []
for node_id, _, _, _ in self.get_brokers():
brokers.append(int(node_id))
brokers_iterator = itertools.cycle(brokers)
topic, _, _, replicas, _, _ = (
self.get_partitions_for_topic(topic_name)[0])
total_replica = len(replicas)
old_partition = self.get_total_partitions_for_topic(topic_name)
assignments = []
for _new_partition in range(partitions - old_partition):
assignment = []
for _replica in range(total_replica):
assignment.append(next(brokers_iterator))
assignments.append(assignment)
request = CreatePartitionsRequest_v0(topic_partitions=[
(topic_name, (partitions, assignments))
],
timeout=self.DEFAULT_TIMEOUT,
validate_only=False)
response = self.send_request_and_get_response(request)
for topic, error_code, _error_message in response.topic_errors:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while updating topic \'%s\' partitions. '
'Error key is %s, %s. Request was %s.' %
(topic, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description, request))
self.refresh()
def update_topic_configuration(self, topic_name, topic_conf):
"""
Updates the topic configuration
Usable for Kafka version >= 0.11.0
Requires to be the sended to the current controller of the Kafka
cluster.
"""
request = AlterConfigsRequest_v0(resources=[(self.TOPIC_RESOURCE_ID,
topic_name, topic_conf)],
validate_only=False)
response = self.send_request_and_get_response(request)
for error_code, _, _, resource_name in response.resources:
if error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while updating topic \'%s\' configuration. '
'Error key is %s, %s' %
(resource_name, kafka.errors.for_code(error_code).message,
kafka.errors.for_code(error_code).description))
self.refresh()
def get_assignment_for_replica_factor_update(self, topic_name,
replica_factor):
"""
Generates a json assignment based on replica_factor given to update
replicas for a topic.
Uses all brokers available and distributes them as replicas using
a round robin method.
"""
all_replicas = []
partitions = []
if replica_factor > self.get_total_brokers():
raise KafkaManagerError(
'Error while updating topic \'%s\' replication factor : '
'replication factor \'%s\' is more than available brokers '
'\'%s\'' %
(topic_name, replica_factor, self.get_total_brokers()))
else:
for node_id, _, _, _ in self.get_brokers():
all_replicas.append(node_id)
brokers_iterator = itertools.cycle(all_replicas)
for _, part in self.get_partitions_for_topic(topic_name).items():
_, partition, _, _, _, _ = part
replicas = []
for _i in range(replica_factor):
replicas.append(next(brokers_iterator))
assign_tmp = (partition, replicas, {})
partitions.append(assign_tmp)
return [(topic_name, partitions, {})]
def get_assignment_for_replica_factor_update_with_zk(
self, topic_name, replica_factor):
"""
Generates a json assignment based on replica_factor given to update
replicas for a topic.
Uses all brokers available and distributes them as replicas using
a round robin method.
"""
all_replicas = []
assign = {'partitions': [], 'version': 1}
if replica_factor > self.get_total_brokers():
raise KafkaManagerError(
'Error while updating topic \'%s\' replication factor : '
'replication factor \'%s\' is more than available brokers '
'\'%s\'' %
(topic_name, replica_factor, self.get_total_brokers()))
else:
for node_id, _, _, _ in self.get_brokers():
all_replicas.append(node_id)
brokers_iterator = itertools.cycle(all_replicas)
for _, part in self.get_partitions_for_topic(topic_name).items():
_, partition, _, _, _, _ = part
assign_tmp = {
'topic': topic_name,
'partition': partition,
'replicas': []
}
for _i in range(replica_factor):
assign_tmp['replicas'].append(next(brokers_iterator))
assign['partitions'].append(assign_tmp)
return bytes(str(json.dumps(assign)).encode('ascii'))
def get_assignment_for_partition_update(self, topic_name, partitions):
"""
Generates a json assignment based on number of partitions given to
update partitions for a topic.
Uses all brokers available and distributes them among partitions
using a round robin method.
"""
all_brokers = []
assign = {'partitions': {}, 'version': 1}
_, _, _, replicas, _, _ = self.get_partitions_for_topic(topic_name)[0]
total_replica = len(replicas)
for node_id, _host, _port, _rack in self.get_brokers():
all_brokers.append(node_id)
brokers_iterator = itertools.cycle(all_brokers)
for i in range(partitions):
assign_tmp = []
for _j in range(total_replica):
assign_tmp.append(next(brokers_iterator))
assign['partitions'][str(i)] = assign_tmp
return bytes(str(json.dumps(assign)).encode('ascii'))
def wait_for_partition_assignement(self):
"""
wait until all assignements is done.
"""
retries = 0
assignement_done = False
while (not assignement_done and retries < self.kafka_max_retries):
request = ListPartitionReassignmentsRequest_v0(timeout_ms=60000,
topics=None,
tags={})
response = self.send_request_and_get_response(request)
if len(response.topics) == 0:
break
retries += 1
time.sleep(self.kafka_sleep_time)
if retries >= self.kafka_max_retries:
raise ReassignPartitionsTimeout(
'Reassignement, is still in progress after %s tries,'
'giving up. Consider increasing your `kafka_max_retries`'
'and/or `kafka_sleep_time` parameters and check your'
'cluster.', retries)
def wait_for_znode_assignment(self):
"""
Wait for the reassignment znode to be consumed by Kafka.
Raises `ReassignPartitionsTimeout` if `zk_max_retries` is reached.
"""
retries = 0
while (self.zk_client.exists(self.ZK_REASSIGN_NODE)
and retries < self.zookeeper_max_retries):
retries += 1
time.sleep(self.zookeeper_sleep_time)
if retries >= self.zookeeper_max_retries:
raise ReassignPartitionsTimeout(
'The znode %s, is still present after %s tries, giving up.'
'Consider increasing your `zookeeper_max_retries` and/or '
'`zookeeper_sleep_time` parameters and check your cluster.',
self.ZK_REASSIGN_NODE, retries)
def update_admin_assignment(self, name, replica_factor):
"""
Updates the topic replica factor using a json assignment
Cf core/src/main/scala/kafka/admin/ReassignPartitionsCommand.scala#L580
1 - Send AlterReplicaLogDirsRequest to allow broker to create replica in
the right log dir later if the replica has not been created yet.
2 - Create reassignment znode so that controller will send
LeaderAndIsrRequest to create replica in the broker
def path = "/admin/reassign_partitions" ->
zk.create("/admin/reassign_partitions", b"a value")
case class ReplicaAssignment(
@BeanProperty @JsonProperty("topic") topic: String,
@BeanProperty @JsonProperty("partition") partition: Int,
@BeanProperty @JsonProperty("replicas") replicas: java.util.List[Int])
3 - Send AlterReplicaLogDirsRequest again to make sure broker will start
to move replica to the specified log directory.
It may take some time for controller to create replica in the broker
Retry if the replica has not been created.
It may be possible that the node '/admin/reassign_partitions' is already
there for another topic. That's why we need to check for its existence
and wait for its consumption if it is already present.
Requires zk connection.
"""
if (parse_version(self.get_api_version()) >= parse_version('2.4.0')):
assign = self.get_assignment_for_replica_factor_update(
name, replica_factor)
request = AlterPartitionReassignmentsRequest_v0(timeout_ms=60000,
topics=assign,
tags={})
self.wait_for_partition_assignement()
self.send_request_and_get_response(request)
self.wait_for_partition_assignement()
elif self.zk_configuration is not None:
try:
json_assignment = (
self.get_assignment_for_replica_factor_update_with_zk(
name, replica_factor))
self.init_zk_client()
self.wait_for_znode_assignment()
self.zk_client.create(self.ZK_REASSIGN_NODE, json_assignment)
self.wait_for_znode_assignment()
finally:
self.close_zk_client()
else:
raise KafkaManagerError(
'Zookeeper is mandatory for partition assignment when \
using Kafka <= 2.4.0.')
self.refresh()
def update_topic_assignment(self, json_assignment, zknode):
"""
Updates the topic partition assignment using a json assignment
Used when Kafka version < 1.0.0
Requires zk connection.
"""
try:
self.init_zk_client()
if not self.zk_client.exists(zknode):
raise KafkaManagerError(
'Error while updating assignment: zk node %s missing. '
'Is the topic name correct?' % (zknode))
self.zk_client.set(zknode, json_assignment)
self.refresh()
finally:
self.close_zk_client()
@staticmethod
def generate_consumer_groups_for_broker(broker, response):
"""
From a `broker` and `response` generate a list of consumer groups
"""
consumer_groups = {}
for err, gid, gstate, prot_type, prot, _members in response.groups:
members = {}
for mid, cid, chost, mdata, assign in _members:
mdata = ProtocolMetadata.decode(mdata)
assign = MemberAssignment.decode(assign)
assignment = {}
for t, p in assign.assignment:
assignment[t] = p
members[mid] = {
'client_id': cid,
'client_host': chost,
'member_metadata': {
'version': mdata.version,
'subscription': mdata.subscription,
'user_data': mdata.user_data.decode('utf-8')
},
'member_assignment': {
'version': assign.version,
'assignment': assignment,
'user_data': assign.user_data.decode('utf-8')
}
}
group = {
'error_code': err,
'group_state': gstate,
'members': members,
'protocol_type': prot_type,
'protocol': prot,
'coordinator': {
'host': broker.host,
'nodeId': broker.nodeId,
'port': broker.port,
'rack': broker.rack
}
}
consumer_groups[gid] = group
return consumer_groups
def get_consumer_groups_resource(self):
"""
Return a dict object containing information about consumer groups and
following this structure:
{
"AWESOME_consumer_group_1607465801": {
"coordinator": {
"host": "172.17.0.9",
"nodeId": 1001,
"port": 9092,
"rack": null
},
"error_code": 0,
"group_state": "Empty",
"members": {},
"protocol": "",
"protocol_type": "consumer"
},
"AWESOME_consumer_group_1607466258": {
"coordinator": {
"host": "172.17.0.10",
"nodeId": 1002,
"port": 9092,
"rack": null
},
"error_code": 0,
"group_state": "Stable",
"members": {
"kafka-python-2.0.1-e5500fee-8df9-4f37-bcd7-788522a1c382": {
"client_host": "/172.17.0.1",
"client_id": "kafka-python-2.0.1",
"member_assignment": {
"assignment": {
"test_1607465755": [
0
]
},
"user_data": "",
"version": 0
},
"member_metadata": {
"subscription": [
"test_1607465755"
],
"user_data": "",
"version": 0
}
}
},
"protocol": "range",
"protocol_type": "consumer"
}
}
"""
consumer_groups = {}
for broker in self.get_brokers():
request = ListGroupsRequest_v2()
response = self.send_request_and_get_response(
request, node_id=broker.nodeId)
if response.error_code != self.SUCCESS_CODE:
raise KafkaManagerError(
'Error while list consumer groups of %s. '
'Error key is %s, %s.' %
(broker.nodeId, kafka.errors.for_code(
response.error_code).message,
kafka.errors.for_code(response.error_code).description))
if response.groups:
request = DescribeGroupsRequest_v0(groups=tuple(
[group for group, protocol in response.groups]))
response = self.send_request_and_get_response(
request, node_id=broker.nodeId)
consumer_groups.update(
self.generate_consumer_groups_for_broker(broker, response))
return consumer_groups
def get_brokers_resource(self):
"""
Return a dict object containing information about brokers and
following this structure:
{
"1001": {
"host": "172.17.0.9",
"nodeId": 1001,
"port": 9092,
"rack": null
},
"1002": {
"host": "172.17.0.10",
"nodeId": 1002,
"port": 9092,
"rack": null
}
}
"""
brokers = {}
for broker in self.get_brokers():
brokers[broker.nodeId] = broker._asdict()
return brokers
def get_topics_resource(self):
"""
Return a dict object containing information about topics and partitions,
and following this structure:
{
"test_1600378061": {
"0": {
"isr": [
1002
],
"leader": 1002,
"replicas": [
1002
]
}
}
}
"""
topics = {}
for topic in self.get_topics():
topics[topic] = {}
partitions = self.get_partitions_for_topic(topic)
for partition, metadata in partitions.items():
_, _, leader, replicas, isr, _ = metadata
topics[topic][partition] = {
'leader': leader,
'replicas': replicas,
'isr': isr
}
return topics
@property
def resource_to_func(self):
return {
'topic': self.get_topics_resource,
'broker': self.get_brokers_resource,
'consumer_group': self.get_consumer_groups_resource
}
def get_resource(self, resource):
if resource not in self.resource_to_func:
raise ValueError('Unexpected resource "%s"' % resource)
return self.resource_to_func[resource]()
def ensure_topic(self, name, options, partitions, replica_factor):
changed = False
warn = None
if self.is_topic_configuration_need_update(name, options):
self.update_topic_configuration(name, options)
changed = True
if partitions > 0 and replica_factor > 0:
# partitions and replica_factor are set
if self.is_topic_replication_need_update(name, replica_factor):
self.update_admin_assignment(name, replica_factor)
changed = True
if self.is_topic_partitions_need_update(name, partitions):
cur_version = parse_version(self.get_api_version())
if cur_version < parse_version('1.0.0'):
json_assignment = (
self.get_assignment_for_partition_update(
name, partitions))
zknode = '/brokers/topics/%s' % name
self.update_topic_assignment(json_assignment, zknode)
else:
self.update_topic_partitions(name, partitions)
changed = True
else:
# 0 or "default" (-1)
warn = ("Current values of 'partitions' (%s) and "
"'replica_factor' (%s) does not let this lib to "
"perform any action related to partitions and "
"replication. SKIPPING." % (partitions, replica_factor))
return changed, warn
class AdminClient(object):
DEFAULT_CONFIG = {
'bootstrap_servers': 'localhost',
}
DELETE_TIMEOUT = 1000
CREATE_TIMEOUT = 1000
ALTER_TIMEOUT = 1000
def __init__(self, **configs):
# Only check for extra config keys in top-level class
extra_configs = set(configs).difference(self.DEFAULT_CONFIG)
if extra_configs:
raise KafkaConfigurationError("Unrecognized configs: %s" %
extra_configs)
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
self._client = KafkaClient(**self.config)
def _get_controller_id(self):
"""Get the cluster controller
"""
node_id = self._client.least_loaded_node()
m = MetadataRequest[1](topics=[])
future = self._client.send(node_id, m)
self._client.poll(future=future)
response = future.value
return response.controller_id
def brokers(self):
""" Get all brokers """
return self._client.cluster.brokers()
def topics(self, exclude_internal_topics=True):
"""Get all topics the user is authorized to view.
Returns:
dict: {topic (str): [PartitionMetadata]}
"""
cluster = self._client.cluster
if self._client._metadata_refresh_in_progress and self._client._topics:
future = cluster.request_update()
self._client.poll(future=future)
stash = cluster.need_all_topic_metadata
cluster.need_all_topic_metadata = True
future = cluster.request_update()
self._client.poll(future=future)
cluster.need_all_topic_metadata = stash
_topics = []
# FIXME: this should be part of ClusterMetadata class
for topic, partitions in cluster._partitions.items():
if exclude_internal_topics and topic in cluster.internal_topics:
continue
_topics.append(Topic(topic, partitions.values()))
return _topics
def describe_topic(self, topic):
""" Get all details about a topic, like current offsets for its partitions
Returns: Topic or None
"""
cluster = self._client.cluster
if topic not in cluster.topics():
# Refresh metadata
self.topics()
if topic in cluster.topics():
topic = Topic(topic, cluster._partitions[topic].values())
else:
return None
# Describe offsets
for partition in topic.partitions:
offsets = self.partition_offset(partition)
partition.set_offset(offsets)
return topic
def partition_offset(self, partition):
"""
Get the latest offset for a given topic partition
"""
partition_timestamp = (partition.partition, -1)
request = OffsetRequest[1](replica_id=-1,
topics=[
(partition.topic, [partition_timestamp
]),
])
future = self._client.send(partition.leader, request)
self._client.poll(future=future)
response = future.value
topic = response.topics[0]
return topic[-1][0][-1]
def consumer_groups(self):
"""Get all consumer groups known to the cluster
Returns:
list: [Group]
"""
groups = {}
for broker in self._client.cluster.brokers():
request = ListGroupsRequest[0]()
future = self._client.send(broker.nodeId, request)
self._client.poll(future=future)
response = future.value
if response:
for g in response.groups:
group = g[0]
groups[group] = Group(group, broker.nodeId)
else:
log.error("No response for ListGroupsRequest")
return list(groups.values())
def describe_consumer_group(self, group):
"""
Describe a consumer group
Returns: Group
"""
groups = self.consumer_groups()
if group not in groups:
return None
group = groups[group]
request = DescribeGroupsRequest[-1](groups=[group])
future = self._client.send(group.coordinator_id, request)
self._client.poll(future=future)
response = future.value
group.set_metadata(response.groups[0])
return group
def consumer_offset_info(self, consumer):
""" Fetch and configure the consumed offset information for a given consumer group
"""
all_topics = self.topics()
topics_request = [(topic.name, [p.partition for p in topic.partitions])
for topic in all_topics]
o = OffsetFetchRequest[1](consumer_group=consumer.name,
topics=topics_request)
future = self._client.send(consumer.coordinator_id, o)
self._client.poll(future=future)
response = future.value
for r in response.topics:
topic_name, offsets = r
if any((o[1] != -1) for o in offsets):
topic_info = self.describe_topic(topic_name)
for o in offsets:
if o[1] == -1:
continue
partition = o[0]
offset = o[1]
consumer.set_offset(topic_name, partition, offset,
topic_info.get_offset(partition))
return consumer
def create_topic(self, name, partitions, replication_factor):
""" Create a new topic
"""
node_id = self._get_controller_id()
cc = CreateTopicsRequest[0](
create_topic_requests=[
(name, partitions, replication_factor, [], []),
],
timeout=self.CREATE_TIMEOUT,
)
future = self._client.send(node_id, cc)
self._client.poll(future=future)
response = future.value
error = response.topic_error_codes and response.topic_error_codes[
0] and response.topic_error_codes[0][1]
if error == 0:
return True
else:
log.error('controler: {} create topic error: {}'.format(
node_id, error))
return False
def delete_topic(self, name):
""" Delete a topic """
node_id = self._get_controller_id()
d = DeleteTopicsRequest[0](topics=[name], timeout=self.DELETE_TIMEOUT)
future = self._client.send(node_id, d)
self._client.poll(future=future)
response = future.value
error = response.topic_error_codes and response.topic_error_codes[
0] and response.topic_error_codes[0][1]
if error == 0:
return True
else:
log.error('controler: {} delete topic error: {}'.format(
node_id, error))
return False
def alter_topic(self, topic_name, partitions):
""" Add partitions """
node_id = self._get_controller_id()
a = CreatePartitionsRequest[0](
topic_partitions=[(topic_name, (partitions, None))],
timeout=self.ALTER_TIMEOUT,
validate_only=False,
)
future = self._client.send(node_id, a)
self._client.poll(future=future)
response = future.value
error = response.topic_errors and response.topic_errors[
0] and response.topic_errors[0][1]
if error == 0:
return True
else:
log.error('controler: {} alter topic error: {}'.format(
node_id, error))
return False
class KafkaManager(object):
"""
Easier access to Kafka information
"""
TOPIC_RESOURCE_ID = 2
MAX_POLL_RETRIES = 3
MAX_RETRY = 10
SUCCESS_CODE = 0
def __init__(self, **configs):
self.client = KafkaClient(**configs)
self.refresh()
def refresh(self):
"""
Refresh topics state
"""
fut = self.client.cluster.request_update()
self.client.poll(future=fut)
if not fut.succeeded():
self.close()
self.module.fail_json(
msg='Error while updating topic state from Kafka server: %s.' %
fut.exception)
def close(self):
"""
Closes the client. Must be called once
the client is not used anymore.
"""
self.client.close()
def get_controller(self):
"""
Return the current controller for cluster.
"""
node_id, _host, _port, _rack = self.client.cluster.controller
return node_id
def get_topics(self):
"""
Returns the topics list
"""
return self.client.cluster.topics()
def get_total_partitions_for_topic(self, topic):
"""
Returns the number of partitions for topic
"""
return len(self.client.cluster.partitions_for_topic(topic))
def get_partitions_metadata_for_topic(self, topic):
"""
Returns set of partition for topic
"""
return self.client.cluster._partitions[topic]
def get_config_for_topic(self, topic_name, config_name):
"""
Returns value for config_name topic option
"""
request = DescribeConfigsRequestV0(resources=[(self.TOPIC_RESOURCE_ID,
topic_name,
config_name)])
response = self.send_request_and_get_response(request)
for err_code, err_message, _, _, config_entries in response.resources:
if err_code != self.SUCCESS_CODE:
raise Exception(err_message)
for _, value, _, _, _ in config_entries:
return value
@staticmethod
def _map_to_quota_resources(entries):
return [{
'entity': [{
'entity_type': entity['entity_type'],
'entity_name': entity['entity_name']
} for entity in entry['entity']],
'quotas':
{quota['name']: quota['value']
for quota in entry['values']}
} for entry in entries]
def describe_quotas(self):
request = DescribeClientQuotasRequest_v0(components=[])
response = self.send_request_and_get_response(request)
if response.error_code != 0:
raise []
return self._map_to_quota_resources(response.to_object()['entries'])
def describe_acls(self, acl_resource):
"""Describe a set of ACLs
"""
request = DescribeAclsRequest_v0(
resource_type=acl_resource['resource_type'],
resource_name=acl_resource['name'],
principal=acl_resource['principal'],
host=acl_resource['host'],
operation=acl_resource['operation'],
permission_type=acl_resource['permission_type'])
response = self.send_request_and_get_response(request)
if response.error_code == self.SUCCESS_CODE:
return response.resources
return None
def connection_check(self, node_id, connection_sleep=1):
"""
Checks that connection with broker is OK and that it is possible
to send requests
Since the _maybe_connect() function used in ready() is 'async',
we need to manually call it several time to make the connection
"""
retries = 0
if not self.client.ready(node_id):
while retries < self.MAX_RETRY:
self.client.poll()
if self.client.ready(node_id):
return True
time.sleep(connection_sleep)
retries += 1
return False
return True
def send_request_and_get_response(self, request):
"""
Send requet and get associated response
"""
try:
node_id = self.get_controller()
except Exception:
raise
if self.connection_check(node_id):
future = self.client.send(node_id, request)
self.client.poll(future=future)
if future.succeeded():
return future.value
else:
raise future.exception
return None
class KafkaConsumerGroups:
kafka_brokers = None
client = None
timeout = None
security_protocol = None
sasl_mechanism = None
sasl_plain_username = None
sasl_plain_password = None
ssl_certfile = None
ssl_keyfile = None
ssl_context = None
def __init__(self,
kafka_brokers,
security_protocol,
sasl_mechanism,
sasl_plain_username,
sasl_plain_password,
ssl_context,
timeout=5000):
self.kafka_brokers = kafka_brokers
self.security_protocol = security_protocol
self.sasl_mechanism = sasl_mechanism
self.sasl_plain_username = sasl_plain_username
self.sasl_plain_password = sasl_plain_password
self.ssl_context = ssl_context
self.timeout = timeout
self.client = KafkaClient(bootstrap_servers=kafka_brokers,
security_protocol=security_protocol,
sasl_mechanism=sasl_mechanism,
sasl_plain_username=sasl_plain_username,
sasl_plain_password=sasl_plain_password,
ssl_context=ssl_context,
timeout=timeout)
self.lag_topics_found = []
self.lag_total = 0
def list(self):
list_groups_request = admin.ListGroupsRequest_v0(timeout=self.timeout)
kafka_broker_ids = [
broker.nodeId for broker in self.client.cluster.brokers()
]
consumers_grp = {}
for broker_id in kafka_broker_ids:
current_of_tries = 0
max_of_tries = 5
data_from_node = False
while not data_from_node and current_of_tries <= max_of_tries:
future = self.client.send(broker_id, list_groups_request)
self.client.poll(timeout_ms=self.timeout, future=future)
if future.value is not None:
result = future.value.groups
for i in result:
consumers_grp.update({i[0]: broker_id})
data_from_node = True
else:
current_of_tries += 1
time.sleep(0.5)
return consumers_grp
def get_members(self, node_id, group_name):
describe_groups_request = admin.DescribeGroupsRequest_v0(
groups=[(group_name)])
future = self.client.send(node_id, describe_groups_request)
self.client.poll(timeout_ms=self.timeout, future=future)
(error_code, group_id, state, protocol_type, protocol,
members) = future.value.groups[0]
if error_code != 0:
print(
"Kafka API - RET admin.DescribeGroupsRequest, error_code={}, group_id={}, state={}, protocol_type={}, protocol={}, members_count={}"
.format(error_code, group_id, state, protocol_type, protocol,
len(members)))
exit(1)
lmembers = []
for member in members:
(member_id, client_id, client_host, member_metadata,
member_assignment) = member
lmembers.append({
'member_id': member_id,
'client_id': client_id,
'client_host': client_host
})
return lmembers
def describe(self, node_id, group_name):
describe_groups_request = admin.DescribeGroupsRequest_v0(
groups=[(group_name)])
future = self.client.send(node_id, describe_groups_request)
self.client.poll(timeout_ms=self.timeout, future=future)
(error_code, group_id, state, protocol_type, protocol,
members) = future.value.groups[0]
if error_code != 0:
print(
"Kafka API - RET admin.DescribeGroupsRequest, error_code={}, group_id={}, state={}, protocol_type={}, protocol={}, members_count={}"
.format(error_code, group_id, state, protocol_type, protocol,
len(members)))
exit(1)
metadata_consumer_group = {
'id': group_name,
'state': state,
'topics': [],
'lag': 0,
'members': []
}
if len(members) != 0:
for member in members:
(member_id, client_id, client_host, member_metadata,
member_assignment) = member
member_topics_assignment = []
for (topic, partitions) in MemberAssignment.decode(
member_assignment).assignment:
member_topics_assignment.append(topic)
metadata_consumer_group['members'].append({
'member_id':
member_id,
'client_id':
client_id,
'client_host':
client_host,
'topic':
member_topics_assignment
})
metadata_consumer_group['topics'] += member_topics_assignment
(lag_total, topics_found) = self.get_lag_by_topic_list(
group_name, topics=metadata_consumer_group['topics'])
metadata_consumer_group[
'lag'] = metadata_consumer_group['lag'] + lag_total
else:
all_topics = self.client.cluster.topics()
while '__consumer_offsets' in all_topics:
all_topics.remove('__consumer_offsets')
(lag_total,
topics_found) = self.get_lag_by_topic_list(group_name,
topics=all_topics)
metadata_consumer_group[
'lag'] = metadata_consumer_group['lag'] + lag_total
metadata_consumer_group['topics'] = topics_found
return metadata_consumer_group
def get_lag_by_topic_list(self, group_name, topics):
self.lag_topics_found = []
self.lag_total = 0
topics = list(topics)
no_threads = 16
batches = [
topics[i:i + no_threads] for i in range(0, len(topics), no_threads)
]
for batch_topics in batches:
threads = []
for topic in batch_topics:
t = threading.Thread(target=self.get_lag_by_topic,
args=(
group_name,
topic,
))
threads.append(t)
t.start()
for t in threads:
if t.isAlive():
t.join()
return self.lag_total, list(set(self.lag_topics_found))
def get_lag_by_topic(self, group_name, topic):
consumer = KafkaConsumer(bootstrap_servers=self.kafka_brokers,
group_id=group_name,
security_protocol=self.security_protocol,
sasl_mechanism=self.sasl_mechanism,
sasl_plain_username=self.sasl_plain_username,
sasl_plain_password=self.sasl_plain_password,
ssl_context=self.ssl_context)
partitions_per_topic = consumer.partitions_for_topic(topic)
for partition in partitions_per_topic:
tp = TopicPartition(topic, partition)
consumer.assign([tp])
committed = consumer.committed(tp)
consumer.seek_to_end(tp)
last_offset = consumer.position(tp)
if committed is not None and int(
committed) and last_offset is not None and int(
last_offset):
self.lag_topics_found.append(topic)
self.lag_total += (last_offset - committed)
consumer.close(autocommit=False)
return
class OffsetsFetcherAsync(object):
DEFAULT_CONFIG = {
'session_timeout_ms': 30000,
'heartbeat_interval_ms': 3000,
'retry_backoff_ms': 100,
'api_version': (0, 9),
'metric_group_prefix': ''
}
def __init__(self, **configs):
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
self._client = KafkaClient(**self.config)
self._coordinator_id = None
self.group_id = configs['group_id']
self.topic = configs['topic']
def _ensure_coordinator_known(self):
"""Block until the coordinator for this group is known
(and we have an active connection -- java client uses unsent queue).
"""
while self._coordinator_unknown():
# Prior to 0.8.2 there was no group coordinator
# so we will just pick a node at random and treat
# it as the "coordinator"
if self.config['api_version'] < (0, 8, 2):
self._coordinator_id = self._client.least_loaded_node()
self._client.ready(self._coordinator_id)
continue
future = self._send_group_coordinator_request()
self._client.poll(future=future)
if future.failed():
if isinstance(future.exception,
Errors.GroupCoordinatorNotAvailableError):
continue
elif future.retriable():
metadata_update = self._client.cluster.request_update()
self._client.poll(future=metadata_update)
else:
raise future.exception # pylint: disable-msg=raising-bad-type
def _coordinator_unknown(self):
"""Check if we know who the coordinator is and have an active connection
Side-effect: reset _coordinator_id to None if connection failed
Returns:
bool: True if the coordinator is unknown
"""
if self._coordinator_id is None:
return True
if self._client.is_disconnected(self._coordinator_id):
self._coordinator_dead()
return True
return False
def _coordinator_dead(self, error=None):
"""Mark the current coordinator as dead."""
if self._coordinator_id is not None:
log.warning("Marking the coordinator dead (node %s) for group %s: %s.",
self._coordinator_id, self.group_id, error)
self._coordinator_id = None
def _send_group_coordinator_request(self):
"""Discover the current coordinator for the group.
Returns:
Future: resolves to the node id of the coordinator
"""
node_id = self._client.least_loaded_node()
if node_id is None:
return Future().failure(Errors.NoBrokersAvailable())
log.debug("Sending group coordinator request for group %s to broker %s",
self.group_id, node_id)
request = GroupCoordinatorRequest[0](self.group_id)
future = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_group_coordinator_response, future)
_f.add_errback(self._failed_request, node_id, request, future)
return future
def _handle_group_coordinator_response(self, future, response):
log.debug("Received group coordinator response %s", response)
if not self._coordinator_unknown():
# We already found the coordinator, so ignore the request
log.debug("Coordinator already known -- ignoring metadata response")
future.success(self._coordinator_id)
return
error_type = Errors.for_code(response.error_code)
if error_type is Errors.NoError:
ok = self._client.cluster.add_group_coordinator(self.group_id, response)
if not ok:
# This could happen if coordinator metadata is different
# than broker metadata
future.failure(Errors.IllegalStateError())
return
self._coordinator_id = response.coordinator_id
log.info("Discovered coordinator %s for group %s",
self._coordinator_id, self.group_id)
self._client.ready(self._coordinator_id)
future.success(self._coordinator_id)
elif error_type is Errors.GroupCoordinatorNotAvailableError:
log.debug("Group Coordinator Not Available; retry")
future.failure(error_type())
elif error_type is Errors.GroupAuthorizationFailedError:
error = error_type(self.group_id)
log.error("Group Coordinator Request failed: %s", error)
future.failure(error)
else:
error = error_type()
log.error("Unrecognized failure in Group Coordinator Request: %s",
error)
future.failure(error)
def _failed_request(self, node_id, request, future, error):
log.error('Error sending %s to node %s [%s]',
request.__class__.__name__, node_id, error)
# Marking coordinator dead
# unless the error is caused by internal client pipelining
if not isinstance(error, (Errors.NodeNotReadyError,
Errors.TooManyInFlightRequests)):
self._coordinator_dead()
future.failure(error)
def offsets(self, partitions, timestamp):
"""Fetch a single offset before the given timestamp for the set of partitions.
Blocks until offset is obtained, or a non-retriable exception is raised
Arguments:
partitions (iterable of TopicPartition) The partition that needs fetching offset.
timestamp (int): timestamp for fetching offset. -1 for the latest
available, -2 for the earliest available. Otherwise timestamp
is treated as epoch seconds.
Returns:
dict: TopicPartition and message offsets
"""
retries = 3
while retries > 0:
offsets = {}
for future in self._send_offset_request(partitions, timestamp):
self._client.poll(future=future)
if future.succeeded():
for tp, offset in future.value:
offsets[tp] = offset
continue
if not future.retriable():
raise future.exception # pylint: disable-msg=raising-bad-type
if future.exception.invalid_metadata:
refresh_future = self._client.cluster.request_update()
self._client.poll(future=refresh_future)
log.warning("Got exception %s and kept the loop", future.exception)
if offsets:
return offsets
retries -= 1
log.warning("Retrying the offsets fetch loop (%d retries left)", retries)
log.error("Unsuccessful offsets retrieval")
return {}
def _send_offset_request(self, partitions, timestamp):
"""Fetch a single offset before the given timestamp for the partition.
Arguments:
partitions iterable of TopicPartition: partitions that needs fetching offset
timestamp (int): timestamp for fetching offset
Returns:
list of Future: resolves to the corresponding offset
"""
topic = partitions[0].topic
nodes_per_partitions = {}
for partition in partitions:
node_id = self._client.cluster.leader_for_partition(partition)
if node_id is None:
log.debug("Partition %s is unknown for fetching offset,"
" wait for metadata refresh", partition)
return [Future().failure(Errors.StaleMetadata(partition))]
elif node_id == -1:
log.debug("Leader for partition %s unavailable for fetching offset,"
" wait for metadata refresh", partition)
return [Future().failure(Errors.LeaderNotAvailableError(partition))]
nodes_per_partitions.setdefault(node_id, []).append(partition)
# Client returns a future that only fails on network issues
# so create a separate future and attach a callback to update it
# based on response error codes
futures = []
for node_id, partitions in six.iteritems(nodes_per_partitions):
request = OffsetRequest[0](
-1, [(topic, [(partition.partition, timestamp, 1) for partition in partitions])]
)
future_request = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_offset_response, partitions, future_request)
def errback(e):
log.error("Offset request errback error %s", e)
future_request.failure(e)
_f.add_errback(errback)
futures.append(future_request)
return futures
def _handle_offset_response(self, partitions, future, response):
"""Callback for the response of the list offset call above.
Arguments:
partition (TopicPartition): The partition that was fetched
future (Future): the future to update based on response
response (OffsetResponse): response from the server
Raises:
AssertionError: if response does not match partition
"""
topic, partition_info = response.topics[0]
assert len(response.topics) == 1, (
'OffsetResponse should only be for a single topic')
partition_ids = set([part.partition for part in partitions])
result = []
for pi in partition_info:
part, error_code, offsets = pi
assert topic == partitions[0].topic and part in partition_ids, (
'OffsetResponse partition does not match OffsetRequest partition')
error_type = Errors.for_code(error_code)
if error_type is Errors.NoError:
assert len(offsets) == 1, 'Expected OffsetResponse with one offset'
log.debug("Fetched offset %s for partition %d", offsets[0], part)
result.append((TopicPartition(topic, part), offsets[0]))
elif error_type in (Errors.NotLeaderForPartitionError,
Errors.UnknownTopicOrPartitionError):
log.debug("Attempt to fetch offsets for partition %s failed due"
" to obsolete leadership information, retrying.",
str(partitions))
future.failure(error_type(partitions))
else:
log.warning("Attempt to fetch offsets for partition %s failed due to:"
" %s", partitions, error_type)
future.failure(error_type(partitions))
future.success(result)
def fetch_committed_offsets(self, partitions):
"""Fetch the current committed offsets for specified partitions
Arguments:
partitions (list of TopicPartition): partitions to fetch
Returns:
dict: {TopicPartition: OffsetAndMetadata}
"""
if not partitions:
return {}
while True:
self._ensure_coordinator_known()
# contact coordinator to fetch committed offsets
future = self._send_offset_fetch_request(partitions)
self._client.poll(future=future)
if future.succeeded():
return future.value
if not future.retriable():
raise future.exception # pylint: disable-msg=raising-bad-type
time.sleep(self.config['retry_backoff_ms'] / 1000.0)
def _send_offset_fetch_request(self, partitions):
"""Fetch the committed offsets for a set of partitions.
This is a non-blocking call. The returned future can be polled to get
the actual offsets returned from the broker.
Arguments:
partitions (list of TopicPartition): the partitions to fetch
Returns:
Future: resolves to dict of offsets: {TopicPartition: int}
"""
assert self.config['api_version'] >= (0, 8, 1), 'Unsupported Broker API'
assert all(map(lambda k: isinstance(k, TopicPartition), partitions))
if not partitions:
return Future().success({})
elif self._coordinator_unknown():
return Future().failure(Errors.GroupCoordinatorNotAvailableError)
node_id = self._coordinator_id
# Verify node is ready
if not self._client.ready(node_id):
log.debug("Node %s not ready -- failing offset fetch request",
node_id)
return Future().failure(Errors.NodeNotReadyError)
log.debug("Group %s fetching committed offsets for partitions: %s",
self.group_id, partitions)
# construct the request
topic_partitions = collections.defaultdict(set)
for tp in partitions:
topic_partitions[tp.topic].add(tp.partition)
if self.config['api_version'] >= (0, 8, 2):
request = OffsetFetchRequest[1](
self.group_id,
list(topic_partitions.items())
)
else:
request = OffsetFetchRequest[0](
self.group_id,
list(topic_partitions.items())
)
# send the request with a callback
future = Future()
_f = self._client.send(node_id, request)
_f.add_callback(self._handle_offset_fetch_response, future)
_f.add_errback(self._failed_request, node_id, request, future)
return future
def _handle_offset_fetch_response(self, future, response):
offsets = {}
for topic, partitions in response.topics:
for partition, offset, metadata, error_code in partitions:
tp = TopicPartition(topic, partition)
error_type = Errors.for_code(error_code)
if error_type is not Errors.NoError:
error = error_type()
log.debug("Group %s failed to fetch offset for partition"
" %s: %s", self.group_id, tp, error)
if error_type is Errors.GroupLoadInProgressError:
# just retry
future.failure(error)
elif error_type is Errors.NotCoordinatorForGroupError:
# re-discover the coordinator and retry
self._coordinator_dead()
future.failure(error)
elif error_type in (Errors.UnknownMemberIdError,
Errors.IllegalGenerationError):
future.failure(error)
elif error_type is Errors.UnknownTopicOrPartitionError:
log.warning("OffsetFetchRequest -- unknown topic %s"
" (have you committed any offsets yet?)",
topic)
continue
else:
log.error("Unknown error fetching offsets for %s: %s",
tp, error)
future.failure(error)
return
elif offset >= 0:
# record the position with the offset
# (-1 indicates no committed offset to fetch)
offsets[tp] = OffsetAndMetadata(offset, metadata)
else:
log.debug("Group %s has no committed offset for partition"
" %s", self.group_id, tp)
future.success(offsets)
def get(self):
topic_partitions = self._client.cluster.partitions_for_topic(self.topic)
if not topic_partitions:
future = self._client.cluster.request_update()
log.info("No partitions available, performing metadata update.")
self._client.poll(future=future)
return {}
partitions = [TopicPartition(self.topic, partition_id) for partition_id in topic_partitions]
offsets = self.offsets(partitions, -1)
committed = self.fetch_committed_offsets(partitions)
lags = {}
for tp, offset in six.iteritems(offsets):
commit_offset = committed[tp] if tp in committed else 0
numerical = commit_offset if isinstance(commit_offset, int) else commit_offset.offset
lag = offset - numerical
pid = tp.partition if isinstance(tp, TopicPartition) else tp
log.debug("Lag for %s (%s): %s, %s, %s", self.topic, pid, offset, commit_offset, lag)
lags[pid] = lag
return lags
class KafkaAdminClient(object):
"""A class for administering the Kafka cluster.
Warning:
This is an unstable interface that was recently added and is subject to
change without warning. In particular, many methods currently return
raw protocol tuples. In future releases, we plan to make these into
nicer, more pythonic objects. Unfortunately, this will likely break
those interfaces.
The KafkaAdminClient class will negotiate for the latest version of each message
protocol format supported by both the kafka-python client library and the
Kafka broker. Usage of optional fields from protocol versions that are not
supported by the broker will result in IncompatibleBrokerVersion exceptions.
Use of this class requires a minimum broker version >= 0.10.0.0.
Keyword Arguments:
bootstrap_servers: 'host[:port]' string (or list of 'host[:port]'
strings) that the consumer should contact to bootstrap initial
cluster metadata. This does not have to be the full node list.
It just needs to have at least one broker that will respond to a
Metadata API Request. Default port is 9092. If no servers are
specified, will default to localhost:9092.
client_id (str): a name for this client. This string is passed in
each request to servers and can be used to identify specific
server-side log entries that correspond to this client. Also
submitted to GroupCoordinator for logging with respect to
consumer group administration. Default: 'kafka-python-{version}'
reconnect_backoff_ms (int): The amount of time in milliseconds to
wait before attempting to reconnect to a given host.
Default: 50.
reconnect_backoff_max_ms (int): The maximum amount of time in
milliseconds to wait when reconnecting to a broker that has
repeatedly failed to connect. If provided, the backoff per host
will increase exponentially for each consecutive connection
failure, up to this maximum. To avoid connection storms, a
randomization factor of 0.2 will be applied to the backoff
resulting in a random range between 20% below and 20% above
the computed value. Default: 1000.
request_timeout_ms (int): Client request timeout in milliseconds.
Default: 30000.
connections_max_idle_ms: Close idle connections after the number of
milliseconds specified by this config. The broker closes idle
connections after connections.max.idle.ms, so this avoids hitting
unexpected socket disconnected errors on the client.
Default: 540000
retry_backoff_ms (int): Milliseconds to backoff when retrying on
errors. Default: 100.
max_in_flight_requests_per_connection (int): Requests are pipelined
to kafka brokers up to this number of maximum requests per
broker connection. Default: 5.
receive_buffer_bytes (int): The size of the TCP receive buffer
(SO_RCVBUF) to use when reading data. Default: None (relies on
system defaults). Java client defaults to 32768.
send_buffer_bytes (int): The size of the TCP send buffer
(SO_SNDBUF) to use when sending data. Default: None (relies on
system defaults). Java client defaults to 131072.
socket_options (list): List of tuple-arguments to socket.setsockopt
to apply to broker connection sockets. Default:
[(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)]
metadata_max_age_ms (int): The period of time in milliseconds after
which we force a refresh of metadata even if we haven't seen any
partition leadership changes to proactively discover any new
brokers or partitions. Default: 300000
security_protocol (str): Protocol used to communicate with brokers.
Valid values are: PLAINTEXT, SSL. Default: PLAINTEXT.
ssl_context (ssl.SSLContext): Pre-configured SSLContext for wrapping
socket connections. If provided, all other ssl_* configurations
will be ignored. Default: None.
ssl_check_hostname (bool): Flag to configure whether SSL handshake
should verify that the certificate matches the broker's hostname.
Default: True.
ssl_cafile (str): Optional filename of CA file to use in certificate
veriication. Default: None.
ssl_certfile (str): Optional filename of file in PEM format containing
the client certificate, as well as any CA certificates needed to
establish the certificate's authenticity. Default: None.
ssl_keyfile (str): Optional filename containing the client private key.
Default: None.
ssl_password (str): Optional password to be used when loading the
certificate chain. Default: None.
ssl_crlfile (str): Optional filename containing the CRL to check for
certificate expiration. By default, no CRL check is done. When
providing a file, only the leaf certificate will be checked against
this CRL. The CRL can only be checked with Python 3.4+ or 2.7.9+.
Default: None.
api_version (tuple): Specify which Kafka API version to use. If set
to None, KafkaClient will attempt to infer the broker version by
probing various APIs. Example: (0, 10, 2). Default: None
api_version_auto_timeout_ms (int): number of milliseconds to throw a
timeout exception from the constructor when checking the broker
api version. Only applies if api_version is None
selector (selectors.BaseSelector): Provide a specific selector
implementation to use for I/O multiplexing.
Default: selectors.DefaultSelector
metrics (kafka.metrics.Metrics): Optionally provide a metrics
instance for capturing network IO stats. Default: None.
metric_group_prefix (str): Prefix for metric names. Default: ''
sasl_mechanism (str): Authentication mechanism when security_protocol
is configured for SASL_PLAINTEXT or SASL_SSL. Valid values are:
PLAIN, GSSAPI, OAUTHBEARER.
sasl_plain_username (str): username for sasl PLAIN authentication.
Required if sasl_mechanism is PLAIN.
sasl_plain_password (str): password for sasl PLAIN authentication.
Required if sasl_mechanism is PLAIN.
sasl_kerberos_service_name (str): Service name to include in GSSAPI
sasl mechanism handshake. Default: 'kafka'
sasl_oauth_token_provider (AbstractTokenProvider): OAuthBearer token provider
instance. (See kafka.oauth.abstract). Default: None
"""
DEFAULT_CONFIG = {
# client configs
'bootstrap_servers': 'localhost',
'client_id': 'kafka-python-' + __version__,
'request_timeout_ms': 30000,
'connections_max_idle_ms': 9 * 60 * 1000,
'reconnect_backoff_ms': 50,
'reconnect_backoff_max_ms': 1000,
'max_in_flight_requests_per_connection': 5,
'receive_buffer_bytes': None,
'send_buffer_bytes': None,
'socket_options': [(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)],
'sock_chunk_bytes': 4096, # undocumented experimental option
'sock_chunk_buffer_count': 1000, # undocumented experimental option
'retry_backoff_ms': 100,
'metadata_max_age_ms': 300000,
'security_protocol': 'PLAINTEXT',
'ssl_context': None,
'ssl_check_hostname': True,
'ssl_cafile': None,
'ssl_certfile': None,
'ssl_keyfile': None,
'ssl_password': None,
'ssl_crlfile': None,
'api_version': None,
'api_version_auto_timeout_ms': 2000,
'selector': selectors.DefaultSelector,
'sasl_mechanism': None,
'sasl_plain_username': None,
'sasl_plain_password': None,
'sasl_kerberos_service_name': 'kafka',
'sasl_oauth_token_provider': None,
# metrics configs
'metric_reporters': [],
'metrics_num_samples': 2,
'metrics_sample_window_ms': 30000,
}
def __init__(self, **configs):
log.debug("Starting KafkaAdminClient with configuration: %s", configs)
extra_configs = set(configs).difference(self.DEFAULT_CONFIG)
if extra_configs:
raise KafkaConfigurationError("Unrecognized configs: {}".format(extra_configs))
self.config = copy.copy(self.DEFAULT_CONFIG)
self.config.update(configs)
# Configure metrics
metrics_tags = {'client-id': self.config['client_id']}
metric_config = MetricConfig(samples=self.config['metrics_num_samples'],
time_window_ms=self.config['metrics_sample_window_ms'],
tags=metrics_tags)
reporters = [reporter() for reporter in self.config['metric_reporters']]
self._metrics = Metrics(metric_config, reporters)
self._client = KafkaClient(metrics=self._metrics,
metric_group_prefix='admin',
**self.config)
# Get auto-discovered version from client if necessary
if self.config['api_version'] is None:
self.config['api_version'] = self._client.config['api_version']
self._closed = False
self._refresh_controller_id()
log.debug("KafkaAdminClient started.")
def close(self):
"""Close the KafkaAdminClient connection to the Kafka broker."""
if not hasattr(self, '_closed') or self._closed:
log.info("KafkaAdminClient already closed.")
return
self._metrics.close()
self._client.close()
self._closed = True
log.debug("KafkaAdminClient is now closed.")
def _matching_api_version(self, operation):
"""Find the latest version of the protocol operation supported by both
this library and the broker.
This resolves to the lesser of either the latest api version this
library supports, or the max version supported by the broker.
:param operation: A list of protocol operation versions from kafka.protocol.
:return: The max matching version number between client and broker.
"""
version = min(len(operation) - 1,
self._client.get_api_versions()[operation[0].API_KEY][1])
if version < self._client.get_api_versions()[operation[0].API_KEY][0]:
# max library version is less than min broker version. Currently,
# no Kafka versions specify a min msg version. Maybe in the future?
raise IncompatibleBrokerVersion(
"No version of the '{}' Kafka protocol is supported by both the client and broker."
.format(operation.__name__))
return version
def _validate_timeout(self, timeout_ms):
"""Validate the timeout is set or use the configuration default.
:param timeout_ms: The timeout provided by api call, in milliseconds.
:return: The timeout to use for the operation.
"""
return timeout_ms or self.config['request_timeout_ms']
def _refresh_controller_id(self):
"""Determine the Kafka cluster controller."""
version = self._matching_api_version(MetadataRequest)
if 1 <= version <= 6:
request = MetadataRequest[version]()
response = self._send_request_to_node(self._client.least_loaded_node(), request)
controller_id = response.controller_id
# verify the controller is new enough to support our requests
controller_version = self._client.check_version(controller_id)
if controller_version < (0, 10, 0):
raise IncompatibleBrokerVersion(
"The controller appears to be running Kafka {}. KafkaAdminClient requires brokers >= 0.10.0.0."
.format(controller_version))
self._controller_id = controller_id
else:
raise UnrecognizedBrokerVersion(
"Kafka Admin interface cannot determine the controller using MetadataRequest_v{}."
.format(version))
def _find_group_coordinator_id(self, group_id):
"""Find the broker node_id of the coordinator of the given group.
Sends a FindCoordinatorRequest message to the cluster. Will block until
the FindCoordinatorResponse is received. Any errors are immediately
raised.
:param group_id: The consumer group ID. This is typically the group
name as a string.
:return: The node_id of the broker that is the coordinator.
"""
# Note: Java may change how this is implemented in KAFKA-6791.
#
# TODO add support for dynamically picking version of
# GroupCoordinatorRequest which was renamed to FindCoordinatorRequest.
# When I experimented with this, GroupCoordinatorResponse_v1 didn't
# match GroupCoordinatorResponse_v0 and I couldn't figure out why.
gc_request = GroupCoordinatorRequest[0](group_id)
gc_response = self._send_request_to_node(self._client.least_loaded_node(), gc_request)
# use the extra error checking in add_group_coordinator() rather than
# immediately returning the group coordinator.
success = self._client.cluster.add_group_coordinator(group_id, gc_response)
if not success:
error_type = Errors.for_code(gc_response.error_code)
assert error_type is not Errors.NoError
# Note: When error_type.retriable, Java will retry... see
# KafkaAdminClient's handleFindCoordinatorError method
raise error_type(
"Could not identify group coordinator for group_id '{}' from response '{}'."
.format(group_id, gc_response))
group_coordinator = self._client.cluster.coordinator_for_group(group_id)
# will be None if the coordinator was never populated, which should never happen here
assert group_coordinator is not None
# will be -1 if add_group_coordinator() failed... but by this point the
# error should have been raised.
assert group_coordinator != -1
return group_coordinator
def _send_request_to_node(self, node_id, request):
"""Send a Kafka protocol message to a specific broker.
Will block until the message result is received.
:param node_id: The broker id to which to send the message.
:param request: The message to send.
:return: The Kafka protocol response for the message.
:exception: The exception if the message could not be sent.
"""
while not self._client.ready(node_id):
# poll until the connection to broker is ready, otherwise send()
# will fail with NodeNotReadyError
self._client.poll()
future = self._client.send(node_id, request)
self._client.poll(future=future)
if future.succeeded():
return future.value
else:
raise future.exception # pylint: disable-msg=raising-bad-type
def _send_request_to_controller(self, request):
"""Send a Kafka protocol message to the cluster controller.
Will block until the message result is received.
:param request: The message to send.
:return: The Kafka protocol response for the message.
"""
tries = 2 # in case our cached self._controller_id is outdated
while tries:
tries -= 1
response = self._send_request_to_node(self._controller_id, request)
# In Java, the error fieldname is inconsistent:
# - CreateTopicsResponse / CreatePartitionsResponse uses topic_errors
# - DeleteTopicsResponse uses topic_error_codes
# So this is a little brittle in that it assumes all responses have
# one of these attributes and that they always unpack into
# (topic, error_code) tuples.
topic_error_tuples = (response.topic_errors if hasattr(response, 'topic_errors')
else response.topic_error_codes)
# Also small py2/py3 compatibility -- py3 can ignore extra values
# during unpack via: for x, y, *rest in list_of_values. py2 cannot.
# So for now we have to map across the list and explicitly drop any
# extra values (usually the error_message)
for topic, error_code in map(lambda e: e[:2], topic_error_tuples):
error_type = Errors.for_code(error_code)
if tries and error_type is NotControllerError:
# No need to inspect the rest of the errors for
# non-retriable errors because NotControllerError should
# either be thrown for all errors or no errors.
self._refresh_controller_id()
break
elif error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'."
.format(request, response))
else:
return response
raise RuntimeError("This should never happen, please file a bug with full stacktrace if encountered")
@staticmethod
def _convert_new_topic_request(new_topic):
return (
new_topic.name,
new_topic.num_partitions,
new_topic.replication_factor,
[
(partition_id, replicas) for partition_id, replicas in new_topic.replica_assignments.items()
],
[
(config_key, config_value) for config_key, config_value in new_topic.topic_configs.items()
]
)
def create_topics(self, new_topics, timeout_ms=None, validate_only=False):
"""Create new topics in the cluster.
:param new_topics: A list of NewTopic objects.
:param timeout_ms: Milliseconds to wait for new topics to be created
before the broker returns.
:param validate_only: If True, don't actually create new topics.
Not supported by all versions. Default: False
:return: Appropriate version of CreateTopicResponse class.
"""
version = self._matching_api_version(CreateTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version == 0:
if validate_only:
raise IncompatibleBrokerVersion(
"validate_only requires CreateTopicsRequest >= v1, which is not supported by Kafka {}."
.format(self.config['api_version']))
request = CreateTopicsRequest[version](
create_topic_requests=[self._convert_new_topic_request(new_topic) for new_topic in new_topics],
timeout=timeout_ms
)
elif version <= 2:
request = CreateTopicsRequest[version](
create_topic_requests=[self._convert_new_topic_request(new_topic) for new_topic in new_topics],
timeout=timeout_ms,
validate_only=validate_only
)
else:
raise NotImplementedError(
"Support for CreateTopics v{} has not yet been added to KafkaAdminClient."
.format(version))
# TODO convert structs to a more pythonic interface
# TODO raise exceptions if errors
return self._send_request_to_controller(request)
def delete_topics(self, topics, timeout_ms=None):
"""Delete topics from the cluster.
:param topics: A list of topic name strings.
:param timeout_ms: Milliseconds to wait for topics to be deleted
before the broker returns.
:return: Appropriate version of DeleteTopicsResponse class.
"""
version = self._matching_api_version(DeleteTopicsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version <= 1:
request = DeleteTopicsRequest[version](
topics=topics,
timeout=timeout_ms
)
response = self._send_request_to_controller(request)
else:
raise NotImplementedError(
"Support for DeleteTopics v{} has not yet been added to KafkaAdminClient."
.format(version))
return response
# list topics functionality is in ClusterMetadata
# Note: if implemented here, send the request to the least_loaded_node()
# describe topics functionality is in ClusterMetadata
# Note: if implemented here, send the request to the controller
# describe cluster functionality is in ClusterMetadata
# Note: if implemented here, send the request to the least_loaded_node()
# describe_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
# create_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
# delete_acls protocol not yet implemented
# Note: send the request to the least_loaded_node()
@staticmethod
def _convert_describe_config_resource_request(config_resource):
return (
config_resource.resource_type,
config_resource.name,
[
config_key for config_key, config_value in config_resource.configs.items()
] if config_resource.configs else None
)
def describe_configs(self, config_resources, include_synonyms=False):
"""Fetch configuration parameters for one or more Kafka resources.
:param config_resources: An list of ConfigResource objects.
Any keys in ConfigResource.configs dict will be used to filter the
result. Setting the configs dict to None will get all values. An
empty dict will get zero values (as per Kafka protocol).
:param include_synonyms: If True, return synonyms in response. Not
supported by all versions. Default: False.
:return: Appropriate version of DescribeConfigsResponse class.
"""
version = self._matching_api_version(DescribeConfigsRequest)
if version == 0:
if include_synonyms:
raise IncompatibleBrokerVersion(
"include_synonyms requires DescribeConfigsRequest >= v1, which is not supported by Kafka {}."
.format(self.config['api_version']))
request = DescribeConfigsRequest[version](
resources=[self._convert_describe_config_resource_request(config_resource) for config_resource in config_resources]
)
elif version == 1:
request = DescribeConfigsRequest[version](
resources=[self._convert_describe_config_resource_request(config_resource) for config_resource in config_resources],
include_synonyms=include_synonyms
)
else:
raise NotImplementedError(
"Support for DescribeConfigs v{} has not yet been added to KafkaAdminClient."
.format(version))
return self._send_request_to_node(self._client.least_loaded_node(), request)
@staticmethod
def _convert_alter_config_resource_request(config_resource):
return (
config_resource.resource_type,
config_resource.name,
[
(config_key, config_value) for config_key, config_value in config_resource.configs.items()
]
)
def alter_configs(self, config_resources):
"""Alter configuration parameters of one or more Kafka resources.
Warning:
This is currently broken for BROKER resources because those must be
sent to that specific broker, versus this always picks the
least-loaded node. See the comment in the source code for details.
We would happily accept a PR fixing this.
:param config_resources: A list of ConfigResource objects.
:return: Appropriate version of AlterConfigsResponse class.
"""
version = self._matching_api_version(AlterConfigsRequest)
if version == 0:
request = AlterConfigsRequest[version](
resources=[self._convert_alter_config_resource_request(config_resource) for config_resource in config_resources]
)
else:
raise NotImplementedError(
"Support for AlterConfigs v{} has not yet been added to KafkaAdminClient."
.format(version))
# TODO the Java client has the note:
# // We must make a separate AlterConfigs request for every BROKER resource we want to alter
# // and send the request to that specific broker. Other resources are grouped together into
# // a single request that may be sent to any broker.
#
# So this is currently broken as it always sends to the least_loaded_node()
return self._send_request_to_node(self._client.least_loaded_node(), request)
# alter replica logs dir protocol not yet implemented
# Note: have to lookup the broker with the replica assignment and send the request to that broker
# describe log dirs protocol not yet implemented
# Note: have to lookup the broker with the replica assignment and send the request to that broker
@staticmethod
def _convert_create_partitions_request(topic_name, new_partitions):
return (
topic_name,
(
new_partitions.total_count,
new_partitions.new_assignments
)
)
def create_partitions(self, topic_partitions, timeout_ms=None, validate_only=False):
"""Create additional partitions for an existing topic.
:param topic_partitions: A map of topic name strings to NewPartition objects.
:param timeout_ms: Milliseconds to wait for new partitions to be
created before the broker returns.
:param validate_only: If True, don't actually create new partitions.
Default: False
:return: Appropriate version of CreatePartitionsResponse class.
"""
version = self._matching_api_version(CreatePartitionsRequest)
timeout_ms = self._validate_timeout(timeout_ms)
if version == 0:
request = CreatePartitionsRequest[version](
topic_partitions=[self._convert_create_partitions_request(topic_name, new_partitions) for topic_name, new_partitions in topic_partitions.items()],
timeout=timeout_ms,
validate_only=validate_only
)
else:
raise NotImplementedError(
"Support for CreatePartitions v{} has not yet been added to KafkaAdminClient."
.format(version))
return self._send_request_to_controller(request)
# delete records protocol not yet implemented
# Note: send the request to the partition leaders
# create delegation token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# renew delegation token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# expire delegation_token protocol not yet implemented
# Note: send the request to the least_loaded_node()
# describe delegation_token protocol not yet implemented
# Note: send the request to the least_loaded_node()
def describe_consumer_groups(self, group_ids, group_coordinator_id=None):
"""Describe a set of consumer groups.
Any errors are immediately raised.
:param group_ids: A list of consumer group IDs. These are typically the
group names as strings.
:param group_coordinator_id: The node_id of the groups' coordinator
broker. If set to None, it will query the cluster for each group to
find that group's coordinator. Explicitly specifying this can be
useful for avoiding extra network round trips if you already know
the group coordinator. This is only useful when all the group_ids
have the same coordinator, otherwise it will error. Default: None.
:return: A list of group descriptions. For now the group descriptions
are the raw results from the DescribeGroupsResponse. Long-term, we
plan to change this to return namedtuples as well as decoding the
partition assignments.
"""
group_descriptions = []
version = self._matching_api_version(DescribeGroupsRequest)
for group_id in group_ids:
if group_coordinator_id is not None:
this_groups_coordinator_id = group_coordinator_id
else:
this_groups_coordinator_id = self._find_group_coordinator_id(group_id)
if version <= 1:
# Note: KAFKA-6788 A potential optimization is to group the
# request per coordinator and send one request with a list of
# all consumer groups. Java still hasn't implemented this
# because the error checking is hard to get right when some
# groups error and others don't.
request = DescribeGroupsRequest[version](groups=(group_id,))
response = self._send_request_to_node(this_groups_coordinator_id, request)
assert len(response.groups) == 1
# TODO need to implement converting the response tuple into
# a more accessible interface like a namedtuple and then stop
# hardcoding tuple indices here. Several Java examples,
# including KafkaAdminClient.java
group_description = response.groups[0]
error_code = group_description[0]
error_type = Errors.for_code(error_code)
# Java has the note: KAFKA-6789, we can retry based on the error code
if error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'."
.format(request, response))
# TODO Java checks the group protocol type, and if consumer
# (ConsumerProtocol.PROTOCOL_TYPE) or empty string, it decodes
# the members' partition assignments... that hasn't yet been
# implemented here so just return the raw struct results
group_descriptions.append(group_description)
else:
raise NotImplementedError(
"Support for DescribeGroups v{} has not yet been added to KafkaAdminClient."
.format(version))
return group_descriptions
def list_consumer_groups(self, broker_ids=None):
"""List all consumer groups known to the cluster.
This returns a list of Consumer Group tuples. The tuples are
composed of the consumer group name and the consumer group protocol
type.
Only consumer groups that store their offsets in Kafka are returned.
The protocol type will be an empty string for groups created using
Kafka < 0.9 APIs because, although they store their offsets in Kafka,
they don't use Kafka for group coordination. For groups created using
Kafka >= 0.9, the protocol type will typically be "consumer".
As soon as any error is encountered, it is immediately raised.
:param broker_ids: A list of broker node_ids to query for consumer
groups. If set to None, will query all brokers in the cluster.
Explicitly specifying broker(s) can be useful for determining which
consumer groups are coordinated by those broker(s). Default: None
:return list: List of tuples of Consumer Groups.
:exception GroupCoordinatorNotAvailableError: The coordinator is not
available, so cannot process requests.
:exception GroupLoadInProgressError: The coordinator is loading and
hence can't process requests.
"""
# While we return a list, internally use a set to prevent duplicates
# because if a group coordinator fails after being queried, and its
# consumer groups move to new brokers that haven't yet been queried,
# then the same group could be returned by multiple brokers.
consumer_groups = set()
if broker_ids is None:
broker_ids = [broker.nodeId for broker in self._client.cluster.brokers()]
version = self._matching_api_version(ListGroupsRequest)
if version <= 2:
request = ListGroupsRequest[version]()
for broker_id in broker_ids:
response = self._send_request_to_node(broker_id, request)
error_type = Errors.for_code(response.error_code)
if error_type is not Errors.NoError:
raise error_type(
"Request '{}' failed with response '{}'."
.format(request, response))
consumer_groups.update(response.groups)
else:
raise NotImplementedError(
"Support for ListGroups v{} has not yet been added to KafkaAdminClient."
.format(version))
return list(consumer_groups)
def list_consumer_group_offsets(self, group_id, group_coordinator_id=None,
partitions=None):
"""Fetch Consumer Group Offsets.
Note:
This does not verify that the group_id or partitions actually exist
in the cluster.
As soon as any error is encountered, it is immediately raised.
:param group_id: The consumer group id name for which to fetch offsets.
:param group_coordinator_id: The node_id of the group's coordinator
broker. If set to None, will query the cluster to find the group
coordinator. Explicitly specifying this can be useful to prevent
that extra network round trip if you already know the group
coordinator. Default: None.
:param partitions: A list of TopicPartitions for which to fetch
offsets. On brokers >= 0.10.2, this can be set to None to fetch all
known offsets for the consumer group. Default: None.
:return dictionary: A dictionary with TopicPartition keys and
OffsetAndMetada values. Partitions that are not specified and for
which the group_id does not have a recorded offset are omitted. An
offset value of `-1` indicates the group_id has no offset for that
TopicPartition. A `-1` can only happen for partitions that are
explicitly specified.
"""
group_offsets_listing = {}
if group_coordinator_id is None:
group_coordinator_id = self._find_group_coordinator_id(group_id)
version = self._matching_api_version(OffsetFetchRequest)
if version <= 3:
if partitions is None:
if version <= 1:
raise ValueError(
"""OffsetFetchRequest_v{} requires specifying the
partitions for which to fetch offsets. Omitting the
partitions is only supported on brokers >= 0.10.2.
For details, see KIP-88.""".format(version))
topics_partitions = None
else:
# transform from [TopicPartition("t1", 1), TopicPartition("t1", 2)] to [("t1", [1, 2])]
topics_partitions_dict = defaultdict(set)
for topic, partition in partitions:
topics_partitions_dict[topic].add(partition)
topics_partitions = list(six.iteritems(topics_partitions_dict))
request = OffsetFetchRequest[version](group_id, topics_partitions)
response = self._send_request_to_node(group_coordinator_id, request)
if version > 1: # OffsetFetchResponse_v1 lacks a top-level error_code
error_type = Errors.for_code(response.error_code)
if error_type is not Errors.NoError:
# optionally we could retry if error_type.retriable
raise error_type(
"Request '{}' failed with response '{}'."
.format(request, response))
# transform response into a dictionary with TopicPartition keys and
# OffsetAndMetada values--this is what the Java AdminClient returns
for topic, partitions in response.topics:
for partition, offset, metadata, error_code in partitions:
error_type = Errors.for_code(error_code)
if error_type is not Errors.NoError:
raise error_type(
"Unable to fetch offsets for group_id {}, topic {}, partition {}"
.format(group_id, topic, partition))
group_offsets_listing[TopicPartition(topic, partition)] = OffsetAndMetadata(offset, metadata)
else:
raise NotImplementedError(
"Support for OffsetFetch v{} has not yet been added to KafkaAdminClient."
.format(version))
return group_offsets_listing
