def run(cls, args, cluster_config):
# Setup the Kafka client
client = KafkaToolClient(cluster_config.broker_list)
client.load_metadata_for_topics()
topics_dict = cls.preprocess_args(
args.groupid, args.topic, args.partitions, cluster_config, client
)
consumer_offsets_metadata = cls.get_offsets(
client,
args.groupid,
topics_dict,
args.storage,
)
# Warn the user if a topic being subscribed to does not exist in
# Kafka.
for topic in topics_dict:
if topic not in consumer_offsets_metadata:
print(
"Warning: Topic {topic} or one or more of it's partitions "
"do not exist in Kafka".format(topic=topic),
file=sys.stderr,
)
client.close()
if args.json:
print_json(consumer_offsets_metadata)
else:
cls.print_output(consumer_offsets_metadata, args.watermark)
def run(cls, args, cluster_config):
# Setup the Kafka client
client = KafkaToolClient(cluster_config.broker_list)
client.load_metadata_for_topics()
topics_dict = cls.preprocess_args(
groupid=args.groupid,
topic=args.topic,
partitions=args.partitions,
cluster_config=cluster_config,
client=client,
quiet=args.json,
storage=args.storage,
)
consumer_offsets_metadata = cls.get_offsets(
client,
args.groupid,
topics_dict,
args.storage,
)
client.close()
if args.sort_by_distance:
consumer_offsets_metadata = cls.sort_by_distance(
consumer_offsets_metadata)
elif args.sort_by_distance_percentage:
consumer_offsets_metadata = cls.sort_by_distance_percentage(
consumer_offsets_metadata)
if args.json:
partitions_info = []
for partitions in consumer_offsets_metadata.values():
for partition in partitions:
partition_info = partition._asdict()
partition_info['offset_distance'] = partition_info[
'highmark'] - partition_info['current']
partition_info[
'percentage_distance'] = cls.percentage_distance(
partition_info['highmark'],
partition_info['current'])
partitions_info.append(partition_info)
print_json(partitions_info)
else:
# Warn the user if a topic being subscribed to does not exist in
# Kafka.
for topic in topics_dict:
if topic not in consumer_offsets_metadata:
print(
"Warning: Topic {topic} or one or more of it's partitions "
"do not exist in Kafka".format(topic=topic),
file=sys.stderr,
)
cls.print_output(consumer_offsets_metadata, args.watermark)
def run(cls, args, cluster_config):
# Setup the Kafka client
client = KafkaToolClient(cluster_config.broker_list)
client.load_metadata_for_topics()
topics_dict = cls.preprocess_args(
groupid=args.groupid,
topic=args.topic,
partitions=args.partitions,
cluster_config=cluster_config,
client=client,
quiet=args.json,
)
consumer_offsets_metadata = cls.get_offsets(
client,
args.groupid,
topics_dict,
)
client.close()
if args.sort_by_distance:
consumer_offsets_metadata = cls.sort_by_distance(consumer_offsets_metadata)
elif args.sort_by_distance_percentage:
consumer_offsets_metadata = cls.sort_by_distance_percentage(consumer_offsets_metadata)
if args.json:
partitions_info = []
for partitions in consumer_offsets_metadata.values():
for partition in partitions:
partition_info = partition._asdict()
partition_info['offset_distance'] = partition_info['highmark'] - partition_info['current']
partition_info['percentage_distance'] = cls.percentage_distance(
partition_info['highmark'],
partition_info['current']
)
partitions_info.append(partition_info)
print_json(partitions_info)
else:
# Warn the user if a topic being subscribed to does not exist in
# Kafka.
for topic in topics_dict:
if topic not in consumer_offsets_metadata:
print(
"Warning: Topic {topic} or one or more of it's partitions "
"do not exist in Kafka".format(topic=topic),
file=sys.stderr,
)
cls.print_output(consumer_offsets_metadata, args.watermark)
def terminate(err_code, msg, json):
if json:
output = {
'status': STATUS_STRING[err_code],
'data': msg['raw'],
}
print_json(output)
else:
print('{status}: {msg}'.format(
status=STATUS_STRING[err_code],
msg=msg['message'],
))
if 'verbose' in msg:
print(msg['verbose'])
sys.exit(err_code)
def terminate(signal, msg, json):
if json:
output = {
'status': STATUS_STRING[signal],
'data': msg['raw'],
}
print_json(output)
else:
print('{status}: {msg}'.format(
status=STATUS_STRING[signal],
msg=msg['message'],
))
if 'verbose' in msg:
print(msg['verbose'])
sys.exit(signal)
def run(cls, args, cluster_config):
# Setup the Kafka client
client = KafkaToolClient(cluster_config.broker_list)
client.load_metadata_for_topics()
topics_dict = cls.preprocess_args(args.groupid,
args.topic,
args.partitions,
cluster_config,
client,
quiet=args.json)
consumer_offsets_metadata = cls.get_offsets(
client,
args.groupid,
topics_dict,
args.storage,
)
client.close()
if args.json:
print_json([
p._asdict()
for partitions in consumer_offsets_metadata.values()
for p in partitions
])
else:
# Warn the user if a topic being subscribed to does not exist in
# Kafka.
for topic in topics_dict:
if topic not in consumer_offsets_metadata:
print(
"Warning: Topic {topic} or one or more of it's partitions "
"do not exist in Kafka".format(topic=topic),
file=sys.stderr,
)
cls.print_output(consumer_offsets_metadata, args.watermark)
def run(cls, args, cluster_config):
# Setup the Kafka client
client = KafkaToolClient(cluster_config.broker_list)
client.load_metadata_for_topics()
watermarks = {}
if args.exact:
watermarks = cls.get_watermarks(
client,
args.topic,
exact=True,
)
else:
watermarks = cls.get_watermarks(
client,
args.topic,
exact=False,
)
client.close()
if args.json:
print_json(watermarks)
else:
cls.print_output(watermarks)