Mirror of Apache Kafka
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# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from kafkatest.services.performance import PerformanceService
from kafkatest.utils.security_config import SecurityConfig
class ProducerPerformanceService(PerformanceService):
logs = {
"producer_performance_log": {
"path": "/mnt/producer-performance.log",
"collect_default": True},
}
def __init__(self, context, num_nodes, kafka, security_protocol, topic, num_records, record_size, throughput, settings={}, intermediate_stats=False):
super(ProducerPerformanceService, self).__init__(context, num_nodes)
self.kafka = kafka
self.security_config = SecurityConfig(security_protocol)
self.security_protocol = security_protocol
self.args = {
'topic': topic,
'num_records': num_records,
'record_size': record_size,
'throughput': throughput
}
self.settings = settings
self.intermediate_stats = intermediate_stats
def _worker(self, idx, node):
args = self.args.copy()
args.update({'bootstrap_servers': self.kafka.bootstrap_servers()})
cmd = "/opt/kafka/bin/kafka-run-class.sh org.apache.kafka.clients.tools.ProducerPerformance "\
"%(topic)s %(num_records)d %(record_size)d %(throughput)d bootstrap.servers=%(bootstrap_servers)s" % args
self.security_config.setup_node(node)
if self.security_protocol == SecurityConfig.SSL:
self.settings.update(self.security_config.properties)
for key, value in self.settings.items():
cmd += " %s=%s" % (str(key), str(value))
cmd += " | tee /mnt/producer-performance.log"
self.logger.debug("Producer performance %d command: %s", idx, cmd)
def parse_stats(line):
parts = line.split(',')
return {
'records': int(parts[0].split()[0]),
'records_per_sec': float(parts[1].split()[0]),
'mbps': float(parts[1].split('(')[1].split()[0]),
'latency_avg_ms': float(parts[2].split()[0]),
'latency_max_ms': float(parts[3].split()[0]),
'latency_50th_ms': float(parts[4].split()[0]),
'latency_95th_ms': float(parts[5].split()[0]),
'latency_99th_ms': float(parts[6].split()[0]),
'latency_999th_ms': float(parts[7].split()[0]),
}
last = None
for line in node.account.ssh_capture(cmd):
if self.intermediate_stats:
try:
self.stats[idx-1].append(parse_stats(line))
except:
# Sometimes there are extraneous log messages
pass
last = line
try:
self.results[idx-1] = parse_stats(last)
except:
raise Exception("Unable to parse aggregate performance statistics on node %d: %s" % (idx, last))