def test_null(self):
"""
The null case where we are never exceeding the limit, but
are repeatedly creating+destroying connections.
"""
self.redpanda.set_cluster_config({"kafka_connections_max": 6})
metrics = [
MetricCheck(self.logger, self.redpanda, n, REJECTED_METRIC, {},
sum) for n in self.redpanda.nodes
]
producer = RpkProducer(self.test_context,
self.redpanda,
self.topic,
msg_size=16384,
msg_count=1,
quiet=True,
produce_timeout=5)
for n in range(0, 100):
producer.start()
producer.wait()
assert all([
m.evaluate([(REJECTED_METRIC, lambda a, b: b == a)])
for m in metrics
])
def test_node_resize(self):
# Create a topic and write some data to make sure the cluster
# is all up & initialized, and that subsequent checks are happening
# with some partitions actually assigned to shards.
self._client.create_topic(
TopicSpec(name="test", partition_count=10, replication_factor=3))
producer = RpkProducer(context=self.test_context,
redpanda=self.redpanda,
topic="test",
msg_size=4096,
msg_count=1000,
acks=-1)
producer.start()
producer.wait()
# Choose one node from the cluster to exercise checks on.
target_node = self.redpanda.nodes[0]
# Attempt to decrease CPU count relative to initial: redpanda should fail to start
self._restart_with_num_cpus(node=target_node,
num_cpus=self.INITIAL_NUM_CPUS - 1,
expect_fail=True)
# Increase CPU count: redpanda should accept this
self._restart_with_num_cpus(node=target_node,
num_cpus=self.INITIAL_NUM_CPUS + 1,
expect_fail=False)
# Now decrease back to original core count: this should fail, because we previously
# increased so the original core count is now below the high water mark
self._restart_with_num_cpus(node=target_node,
num_cpus=self.INITIAL_NUM_CPUS,
expect_fail=True)
def stress_test(self):
for i in range(10):
spec = TopicSpec(partition_count=2,
cleanup_policy=TopicSpec.CLEANUP_COMPACT)
topic_name = spec.name
self.client().create_topic(spec)
producer = RpkProducer(self.test_context, self.redpanda,
topic_name, 1024, 100000)
producer.start()
metrics = [
MetricCheck(self.logger, self.redpanda, n,
'vectorized_storage_log_compacted_segment_total',
{}, sum) for n in self.redpanda.nodes
]
def check_compaction():
return all([
m.evaluate([
('vectorized_storage_log_compacted_segment_total',
lambda a, b: b > 3)
]) for m in metrics
])
wait_until(check_compaction,
timeout_sec=120,
backoff_sec=5,
err_msg="Segments were not compacted")
self.client().delete_topic(topic_name)
try:
producer.stop()
except:
# Should ignore exception form rpk
pass
producer.free()
def topic_storage_purged():
storage = self.redpanda.storage()
return all(
map(lambda n: topic_name not in n.ns["kafka"].topics,
storage.nodes))
try:
wait_until(lambda: topic_storage_purged(),
timeout_sec=60,
backoff_sec=2,
err_msg="Topic storage was not removed")
except:
# On errors, dump listing of the storage location
for node in self.redpanda.nodes:
self.logger.error(f"Storage listing on {node.name}:")
for line in node.account.ssh_capture(
f"find {self.redpanda.DATA_DIR}"):
self.logger.error(line.strip())
raise
def _produce(self, topic, msg_cnt):
wait_until(lambda: self._all_have_leaders(topic), 20, backoff_sec=2)
producer = RpkProducer(self.test_context,
self.redpanda,
topic,
16384,
msg_cnt,
acks=-1)
producer.start()
producer.wait()
producer.free()
def test_exceed_broker_limit(self):
self.redpanda.set_cluster_config({"kafka_connections_max": 6})
metrics = [
MetricCheck(self.logger, self.redpanda, n, REJECTED_METRIC, {},
sum) for n in self.redpanda.nodes
]
# I happen to know that an `rpk topic consume` occupies three
# connections. So after opening two consumers, I should find
# that a producer cannot get in.
consumers = [
RpkConsumer(self.test_context, self.redpanda, self.topic),
RpkConsumer(self.test_context, self.redpanda, self.topic),
]
for c in consumers:
c.start()
producer = RpkProducer(self.test_context,
self.redpanda,
self.topic,
msg_size=16384,
msg_count=1,
produce_timeout=5)
producer.start()
try:
producer.wait()
except Exception:
# This is a non-specific exception because ducktape re-raises in wait()
# as a bare Exception
pass
else:
raise RuntimeError("Producer should have failed")
for c in consumers:
c.stop()
c.wait()
assert any([
m.evaluate([(REJECTED_METRIC, lambda a, b: b > a)])
for m in metrics
])
def test_sarama_consumergroup(self):
count = 10 if self.scale.local else 5000
sarama_example = SaramaExamples.SaramaConsumerGroup(
self.redpanda, self.topic, count)
example = ExampleRunner(self._ctx,
sarama_example,
timeout_sec=self._timeout)
producer = RpkProducer(self._ctx,
self.redpanda,
self.topic,
4,
count,
acks=-1,
printable=True)
def until_partitions():
storage = self.redpanda.storage()
return len(list(storage.partitions("kafka", self.topic))) == 3
# Must wait for the paritions to materialize or else
# kaf may try to produce during leadership election.
# This results in a skipped record since kaf doesn't auto-retry.
wait_until(until_partitions,
timeout_sec=30,
backoff_sec=2,
err_msg="Expected partition did not materialize")
# Run the producer and wait for the worker
# threads to finish producing
producer.start()
producer.wait()
# Start the example
example.start()
# Wait until the example is OK to terminate
wait_until(example.condition_met,
timeout_sec=self._timeout,
backoff_sec=1)
def transfer_all_leaders():
partitions = rpk.describe_topic(topic)
for p in partitions:
replicas = set(p.replicas)
replicas.remove(p.leader)
target = random.choice(list(replicas))
admin.partition_transfer_leadership("kafka", topic, p.id,
target)
wait_until(lambda: wait_for_leader(p.id, target),
timeout_sec=30,
backoff_sec=1)
msg_cnt = 100
producer = RpkProducer(self.test_context,
self.redpanda,
topic,
16384,
msg_cnt,
acks=-1)
producer.start()
producer.wait()
producer.free()
def test_leadership_transfer(self):
rpk = RpkTool(self.redpanda)
topics = list(filter(lambda x: x.partition_count > 1, self.topics))
group = "g0"
producers = []
for topic in topics:
producer = RpkProducer(self._ctx,
self.redpanda,
topic.name,
msg_size=5,
msg_count=1000)
producer.start()
producers.append(producer)
consumers = []
for topic in topics:
consumer = RpkConsumer(self._ctx,
self.redpanda,
topic.name,
group=group)
consumer.start()
consumers.append(consumer)
# Wait until cluster starts producing metrics
wait_until(
lambda: self.redpanda.metrics_sample("kafka_group_offset") != None,
timeout_sec=30,
backoff_sec=5)
admin = Admin(redpanda=self.redpanda)
def get_offset_with_node_from_metric(group):
metric = self.redpanda.metrics_sample("kafka_group_offset")
if metric is None:
return None
metric = metric.label_filter(dict(group=group))
return metric.samples
def get_group_leader():
return admin.get_partitions(namespace="kafka_internal",
topic="group",
partition=0)['leader_id']
def check_metric_from_node(node):
metrics_offsets = get_offset_with_node_from_metric(group)
if metrics_offsets == None:
return False
return all([
metric.node.account.hostname == node.account.hostname
for metric in metrics_offsets
])
def transfer_completed(new_leader_node):
return self.redpanda.nodes[get_group_leader() - 1].account.hostname \
== new_leader_node.account.hostname
leader_node = self.redpanda.nodes[get_group_leader() - 1]
check_metric_from_node(leader_node)
# Check transfer leadership to another node
for i in range(3):
new_leader_node = random.choice(
list(filter(lambda x: x != leader_node, self.redpanda.nodes)))
admin.transfer_leadership_to(
namespace="kafka_internal",
topic="group",
partition=0,
target=self.redpanda.idx(new_leader_node))
wait_until(lambda: transfer_completed(new_leader_node) and
check_metric_from_node(new_leader_node),
timeout_sec=30,
backoff_sec=5)
leader_node = new_leader_node
# Check transfer leadership to same node
admin.transfer_leadership_to(namespace="kafka_internal",
topic="group",
partition=0,
target=self.redpanda.idx(leader_node))
wait_until(lambda: transfer_completed(leader_node) and
check_metric_from_node(leader_node),
timeout_sec=30,
backoff_sec=5)
for host in producers + consumers:
host.stop()
host.free()
class ConsumerGroupTest(RedpandaTest):
def __init__(self, test_ctx, *args, **kwargs):
self._ctx = test_ctx
self.producer = None
super(ConsumerGroupTest, self).__init__(
test_ctx,
num_brokers=3,
*args,
# disable leader balancer to make sure that group will not be realoaded because of leadership changes
extra_rp_conf={"enable_leader_balancer": False},
**kwargs)
def make_consumer_properties(base_properties, instance_id=None):
properties = {}
properties.update(base_properties)
if instance_id:
properties['group.instance.id'] = instance_id
return properties
def create_consumer(self,
topic,
group,
instance_id=None,
consumer_properties={}):
return KafkaCliConsumer(
self.test_context,
self.redpanda,
topic=topic,
group=group,
from_beginning=True,
formatter_properties={
'print.value': 'false',
'print.key': 'false',
'print.partition': 'true',
'print.offset': 'true',
},
consumer_properties=ConsumerGroupTest.make_consumer_properties(
consumer_properties, instance_id))
def create_consumers(self,
consumer_count,
topic,
group,
static_members,
consumer_properties={}):
consumers = []
for i in range(0, consumer_count):
instance_id = f"panda-consumer-{i}" if static_members else None
consumers.append(
self.create_consumer(topic,
group=group,
instance_id=instance_id,
consumer_properties=consumer_properties))
for c in consumers:
c.start()
return consumers
def consumed_at_least(consumers, count):
return all([len(c._messages) > count for c in consumers])
def validate_group_state(self, group, expected_state, static_members):
rpk = RpkTool(self.redpanda)
# validate group state
rpk_group = rpk.group_describe(group)
assert rpk_group.members == 2
assert rpk_group.state == expected_state
for p in rpk_group.partitions:
if static_members:
assert 'panda-consumer' in p.instance_id
else:
assert p.instance_id is None
def setup_producer(self, p_cnt):
# create topic
self.topic_spec = TopicSpec(partition_count=p_cnt,
replication_factor=3)
self.client().create_topic(specs=self.topic_spec)
# produce some messages to the topic
self.producer = RpkProducer(self._ctx, self.redpanda,
self.topic_spec.name, 128, 5000, -1)
self.producer.start()
@cluster(num_nodes=6)
@parametrize(static_members=True)
@parametrize(static_members=False)
def test_basic_group_join(self, static_members):
"""
Test validating that consumers are able to join the group and consume topic
"""
self.setup_producer(20)
group = 'test-gr-1'
# use 2 consumers
consumers = self.create_consumers(2,
self.topic_spec.name,
group,
static_members=static_members)
# wait for some messages
wait_until(lambda: ConsumerGroupTest.consumed_at_least(consumers, 50),
30, 2)
self.validate_group_state(group,
expected_state="Stable",
static_members=static_members)
self.producer.wait()
self.producer.free()
for c in consumers:
c.stop()
c.wait()
c.free()
@cluster(num_nodes=6)
def test_mixed_consumers_join(self):
"""
Test validating that dynamic and static consumers may exists in the same group
"""
self.setup_producer(20)
group = 'test-gr-1'
consumers = []
consumers.append(
self.create_consumer(self.topic_spec.name, group,
"panda-instance"))
consumers.append(
self.create_consumer(self.topic_spec.name, group, None))
for c in consumers:
c.start()
# wait for some messages
wait_until(lambda: ConsumerGroupTest.consumed_at_least(consumers, 50),
30, 2)
rpk = RpkTool(self.redpanda)
# validate group state
rpk_group = rpk.group_describe(group)
assert rpk_group.members == 2
assert rpk_group.state == "Stable"
static_members = set()
dynamic_members = set()
for p in rpk_group.partitions:
if p.instance_id:
static_members.add(p.client_id)
else:
dynamic_members.add(p.client_id)
assert len(static_members) == 1
assert len(dynamic_members) == 1
self.producer.wait()
self.producer.free()
for c in consumers:
c.stop()
c.wait()
c.free()
def wait_for_members(self, group, members_count):
rpk = RpkTool(self.redpanda)
def group_stable():
rpk_group = rpk.group_describe(group)
return rpk_group.members == members_count and rpk_group.state == "Stable"
return wait_until(group_stable, 30, 2)
@cluster(num_nodes=6)
@parametrize(static_members=True)
@parametrize(static_members=False)
def test_consumer_rejoin(self, static_members):
"""
Test validating that re-joining static member will not casuse rebalance
"""
self.setup_producer(20)
group = 'test-gr-1'
consumers = self.create_consumers(
2,
self.topic_spec.name,
group,
static_members=static_members,
consumer_properties={"session.timeout.ms": 40000})
# wait for some messages
wait_until(lambda: ConsumerGroupTest.consumed_at_least(consumers, 50),
30, 2)
rpk = RpkTool(self.redpanda)
# at this point we have 2 consumers in stable group
self.validate_group_state(group,
expected_state="Stable",
static_members=static_members)
# stop one of the consumers
consumers[0].stop()
consumers[0].wait()
rpk_group = rpk.group_describe(group)
if static_members:
# with static members group should still be in stable state
assert rpk_group.state == "Stable"
assert rpk_group.members == 2
else:
# consumer will request group leave when shutdown gracefully and it is dynamic
self.wait_for_members(group, 1)
# start the consumer again
consumers[0].start()
consumers[0].wait_for_started()
# wait for consumer to start
if static_members:
# with static members group should be stable immediately as the
# consumer is rejoining with the same instance id
self.validate_group_state(group,
expected_state="Stable",
static_members=static_members)
else:
# group should get back to its original 2 members state
self.wait_for_members(group, 2)
self.producer.wait()
self.producer.free()
for c in consumers:
c.stop()
c.wait()
c.free()
@cluster(num_nodes=6)
@parametrize(static_members=True)
@parametrize(static_members=False)
def test_consumer_is_removed_when_timedout(self, static_members):
"""
Test validating that consumer is evicted if it failed to deliver heartbeat to the broker
"""
self.setup_producer(20)
group = 'test-gr-1'
# using short session timeout to make the test finish faster
consumers = self.create_consumers(
2,
self.topic_spec.name,
group,
static_members=static_members,
consumer_properties={"session.timeout.ms": 6000})
# wait for some messages
wait_until(lambda: ConsumerGroupTest.consumed_at_least(consumers, 50),
30, 2)
rpk = RpkTool(self.redpanda)
# at this point we have 2 consumers in stable group
self.validate_group_state(group,
expected_state="Stable",
static_members=static_members)
# stop one of the consumers
consumers[0].stop()
# wait for rebalance
self.wait_for_members(group, 1)
# start the consumer again
consumers[0].start()
# group should get back to its original 2 members state
self.wait_for_members(group, 2)
self.validate_group_state(group,
expected_state="Stable",
static_members=static_members)
self.producer.wait()
self.producer.free()
for c in consumers:
c.stop()
c.wait()
c.free()
def test_leader_transfers_recovery(self, acks):
"""
Validate that leadership transfers complete successfully
under acks=1 writes that prompt the leader to frequently
activate recovery_stm.
When acks=1, this is a reproducer for
https://github.com/vectorizedio/redpanda/issues/2580
When acks=-1, this is a reproducer rfor
https://github.com/vectorizedio/redpanda/issues/2606
"""
leader_node_id, replicas = self._wait_for_leader()
if acks == -1:
producer = RpkProducer(self._ctx,
self.redpanda,
self.topic,
16384,
sys.maxsize,
acks=acks)
else:
# To reproduce acks=1 issue, we need an intermittent producer that
# waits long enough between messages to let recovery_stm go to sleep
# waiting for follower_state_change
# KafProducer is intermittent because it starts a fresh process for
# each message, whereas RpkProducer writes a continuous stream.
# TODO: create a test traffic generator that has inter-message
# delay as an explicit parameter, rather than relying on implementation
# details of the producer helpers.
producer = KafProducer(self._ctx, self.redpanda, self.topic)
producer.start()
# Pass leadership around in a ring
self.logger.info(f"Initial leader of {self.topic} is {leader_node_id}")
transfer_count = 50
# FIXME: with a transfer count >100, we tend to see
# reactor stalls and corresponding nondeterministic behaviour/failures.
# This appears unrelated to the functionality under test, something else
# is tripping up the cluster when we have so many leadership transfers.
# https://github.com/vectorizedio/redpanda/issues/2623
admin = Admin(self.redpanda)
initial_leader_id = leader_node_id
for n in range(0, transfer_count):
target_idx = (initial_leader_id + n) % len(self.redpanda.nodes)
target_node_id = target_idx + 1
self.logger.info(f"Starting transfer to {target_node_id}")
admin.partition_transfer_leadership("kafka", self.topic, 0,
target_node_id)
self._wait_for_leader(
lambda l: l is not None and l == target_node_id,
timeout=ELECTION_TIMEOUT * 2)
self.logger.info(f"Completed transfer to {target_node_id}")
self.logger.info(f"Completed {transfer_count} transfers successfully")
# Explicit stop of producer so that we see any errors
producer.stop()
producer.wait()
producer.free()
def test_leadership_transfer(self):
topics = list(filter(lambda x: x.partition_count > 1, self.topics))
group = "g0"
producers = []
for topic in topics:
producer = RpkProducer(self._ctx,
self.redpanda,
topic.name,
msg_size=5,
msg_count=1000)
producer.start()
producers.append(producer)
consumers = []
for topic in topics:
consumer = RpkConsumer(self._ctx,
self.redpanda,
topic.name,
group=group)
consumer.start()
consumers.append(consumer)
# Wait until cluster starts producing metrics
wait_until(
lambda: self.redpanda.metrics_sample("kafka_group_offset") != None,
timeout_sec=30,
backoff_sec=5)
admin = Admin(redpanda=self.redpanda)
def get_group_partition():
return admin.get_partitions(namespace="kafka",
topic="__consumer_offsets",
partition=0)
def get_group_leader():
return get_group_partition()['leader_id']
def metrics_from_single_node(node):
"""
Check that metrics are produced only by the given node.
"""
metrics = self.redpanda.metrics_sample("kafka_group_offset")
if not metrics:
self.logger.debug("No metrics found")
return False
metrics = metrics.label_filter(dict(group=group)).samples
for metric in metrics:
self.logger.debug(
f"Retrieved metric from node={metric.node.account.hostname}: {metric}"
)
return all([
metric.node.account.hostname == node.account.hostname
for metric in metrics
])
def transfer_leadership(new_leader):
"""
Request leadership transfer of the internal consumer group partition
and check that it completes successfully.
"""
self.logger.debug(
f"Transferring leadership to {new_leader.account.hostname}")
admin.transfer_leadership_to(namespace="kafka",
topic="__consumer_offsets",
partition=0,
target=self.redpanda.idx(new_leader))
for _ in range(3): # re-check a few times
leader = get_group_leader()
self.logger.debug(f"Current leader: {leader}")
if leader != -1 and self.redpanda.get_node(
leader) == new_leader:
return True
time.sleep(1)
return False
def partition_ready():
"""
All replicas present and known leader
"""
partition = get_group_partition()
self.logger.debug(f"XXXXX: {partition}")
return len(
partition['replicas']) == 3 and partition['leader_id'] >= 0
def select_next_leader():
"""
Select a leader different than the current leader
"""
wait_until(partition_ready, timeout_sec=30, backoff_sec=5)
partition = get_group_partition()
replicas = partition['replicas']
assert len(replicas) == 3
leader = partition['leader_id']
assert leader >= 0
replicas = filter(lambda r: r["node_id"] != leader, replicas)
new_leader = random.choice(list(replicas))['node_id']
return self.redpanda.get_node(new_leader)
# repeat the following test a few times.
#
# 1. transfer leadership to a new node
# 2. check that new leader reports metrics
# 3. check that prev leader does not report
#
# note that here reporting does not mean that the node does not report
# any metrics but that it does not report metrics for consumer groups
# for which it is not leader.
for _ in range(4):
new_leader = select_next_leader()
wait_until(lambda: transfer_leadership(new_leader),
timeout_sec=30,
backoff_sec=5)
wait_until(lambda: metrics_from_single_node(new_leader),
timeout_sec=30,
backoff_sec=5)
for host in producers + consumers:
host.stop()
host.free()
def test_consumer_group_mirroring(self, source_type):
# start redpanda
self.start_brokers(source_type=source_type)
consumer_group = "test-group-1"
# start mirror maker
self.mirror_maker = MirrorMaker2(self.test_context,
num_nodes=1,
source_cluster=self.source_broker,
target_cluster=self.redpanda,
consumer_group_pattern=consumer_group,
log_level="TRACE")
self.mirror_maker.start()
msg_size = 512
msg_cnt = 1000000 if self.redpanda.dedicated_nodes else 100
# produce some messages to source redpanda
producer = RpkProducer(self.test_context,
self.source_broker,
self.topic.name,
msg_size,
msg_cnt,
acks=-1)
producer.start()
producer.wait()
producer.free()
# consume some messages from source redpanda
consumer = RpkConsumer(self.test_context,
self.source_broker,
self.topic.name,
ignore_errors=False,
retries=3,
group=consumer_group,
save_msgs=False,
num_msgs=int(msg_cnt / 5))
consumer.start()
consumer.wait()
consumer.stop()
source_messages = consumer.messages
self.logger.info(f"source message count: {len(source_messages)}")
consumer.free()
src_rpk = RpkTool(self.source_broker)
source_group = src_rpk.group_describe(consumer_group)
target_rpk = RpkTool(self.redpanda)
def target_group_equal():
try:
target_group = target_rpk.group_describe(consumer_group)
except RpkException as e:
# e.g. COORDINATOR_NOT_AVAILABLE
self.logger.info(f"Error describing target cluster group: {e}")
return False
self.logger.info(
f"source {source_group}, target_group: {target_group}")
return target_group.partitions == source_group.partitions and target_group.name == source_group.name
# wait for consumer group sync
timeout = 600 if self.redpanda.dedicated_nodes else 60
wait_until(target_group_equal, timeout_sec=timeout, backoff_sec=5)
self.mirror_maker.stop()
def test_overlapping_changes(self):
"""
Check that while a movement is in flight, rules about
overlapping operations are properly enforced.
"""
self.start_redpanda(num_nodes=4)
node_ids = {1, 2, 3, 4}
# Create topic with enough data that inter-node movement
# will take a while.
name = f"movetest"
spec = TopicSpec(name=name, partition_count=1, replication_factor=3)
self.client().create_topic(spec)
# Wait for the partition to have a leader (`rpk produce` errors
# out if it tries to write data before this)
def partition_ready():
return KafkaCat(self.redpanda).get_partition_leader(
name, 0)[0] is not None
wait_until(partition_ready, timeout_sec=10, backoff_sec=0.5)
# Write a substantial amount of data to the topic
msg_size = 512 * 1024
write_bytes = 512 * 1024 * 1024
producer = RpkProducer(self._ctx,
self.redpanda,
name,
msg_size=msg_size,
msg_count=int(write_bytes / msg_size))
t1 = time.time()
producer.start()
# This is an absurdly low expected throughput, but necessarily
# so to run reliably on current test runners, which share an EBS
# backend among many parallel tests. 10MB/s has been empirically
# shown to be too high an expectation.
expect_bps = 1 * 1024 * 1024
expect_runtime = write_bytes / expect_bps
producer.wait(timeout_sec=expect_runtime)
self.logger.info(
f"Write complete {write_bytes} in {time.time() - t1} seconds")
# - Admin API redirects writes but not reads. Because we want synchronous
# status after submitting operations, send all operations to the controller
# leader. This is not necessary for operations to work, just to simplify
# this test by letting it see synchronous status updates.
# - Because we will later verify that a 503 is sent in response to
# a move request to an in_progress topic, set retry_codes=[] to
# disable default retries on 503.
admin_node = self.redpanda.controller()
admin = Admin(self.redpanda, default_node=admin_node, retry_codes=[])
# Start an inter-node move, which should take some time
# to complete because of recovery network traffic
assignments = self._get_assignments(admin, name, 0)
new_node = list(node_ids - set([a['node_id'] for a in assignments]))[0]
self.logger.info(f"old assignments: {assignments}")
old_assignments = assignments
assignments = assignments[1:] + [{'node_id': new_node, 'core': 0}]
self.logger.info(f"new assignments: {assignments}")
r = admin.set_partition_replicas(name, 0, assignments)
r.raise_for_status()
assert admin.get_partitions(name, 0)['status'] == "in_progress"
# Another move should fail
assert admin.get_partitions(name, 0)['status'] == "in_progress"
try:
r = admin.set_partition_replicas(name, 0, old_assignments)
except requests.exceptions.HTTPError as e:
assert e.response.status_code == 503
else:
raise RuntimeError(f"Expected 503 but got {r.status_code}")
# An update to partition properties should succeed
# (issue https://github.com/vectorizedio/redpanda/issues/2300)
rpk = RpkTool(self.redpanda)
assert admin.get_partitions(name, 0)['status'] == "in_progress"
rpk.alter_topic_config(name, "retention.ms", "3600000")
# A deletion should succeed
assert name in rpk.list_topics()
assert admin.get_partitions(name, 0)['status'] == "in_progress"
rpk.delete_topic(name)
assert name not in rpk.list_topics()