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mirror_maker.py
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mirror_maker.py
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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.
import os
from ducktape.services.service import Service
from ducktape.utils.util import wait_until
from kafkatest.directory_layout.kafka_path import KafkaPathResolverMixin
"""
MirrorMaker is a tool for mirroring data between two Kafka clusters.
"""
class MirrorMaker(KafkaPathResolverMixin, Service):
# Root directory for persistent output
PERSISTENT_ROOT = "/mnt/mirror_maker"
LOG_DIR = os.path.join(PERSISTENT_ROOT, "logs")
LOG_FILE = os.path.join(LOG_DIR, "mirror_maker.log")
LOG4J_CONFIG = os.path.join(PERSISTENT_ROOT, "tools-log4j.properties")
PRODUCER_CONFIG = os.path.join(PERSISTENT_ROOT, "producer.properties")
CONSUMER_CONFIG = os.path.join(PERSISTENT_ROOT, "consumer.properties")
logs = {
"mirror_maker_log": {
"path": LOG_FILE,
"collect_default": True}
}
def __init__(self, context, num_nodes, source, target, whitelist=None, num_streams=1,
consumer_timeout_ms=None, offsets_storage="kafka",
offset_commit_interval_ms=60000, log_level="DEBUG", producer_interceptor_classes=None):
"""
MirrorMaker mirrors messages from one or more source clusters to a single destination cluster.
Args:
context: standard context
source: source Kafka cluster
target: target Kafka cluster to which data will be mirrored
whitelist: whitelist regex for topics to mirror
blacklist: blacklist regex for topics not to mirror
num_streams: number of consumer threads to create; can be a single int, or a list with
one value per node, allowing num_streams to be the same for each node,
or configured independently per-node
consumer_timeout_ms: consumer stops if t > consumer_timeout_ms elapses between consecutive messages
offsets_storage: used for consumer offsets.storage property
offset_commit_interval_ms: how frequently the mirror maker consumer commits offsets
"""
super(MirrorMaker, self).__init__(context, num_nodes=num_nodes)
self.log_level = log_level
self.consumer_timeout_ms = consumer_timeout_ms
self.num_streams = num_streams
if not isinstance(num_streams, int):
# if not an integer, num_streams should be configured per-node
assert len(num_streams) == num_nodes
self.whitelist = whitelist
self.source = source
self.target = target
self.offsets_storage = offsets_storage.lower()
if not (self.offsets_storage in ["kafka", "zookeeper"]):
raise Exception("offsets_storage should be 'kafka' or 'zookeeper'. Instead found %s" % self.offsets_storage)
self.offset_commit_interval_ms = offset_commit_interval_ms
self.producer_interceptor_classes = producer_interceptor_classes
self.external_jars = None
# These properties are potentially used by third-party tests.
self.source_auto_offset_reset = None
self.partition_assignment_strategy = None
def start_cmd(self, node):
cmd = "export LOG_DIR=%s;" % MirrorMaker.LOG_DIR
cmd += " export KAFKA_LOG4J_OPTS=\"-Dlog4j.configuration=file:%s\";" % MirrorMaker.LOG4J_CONFIG
cmd += " export KAFKA_OPTS=%s;" % self.security_config.kafka_opts
# add external dependencies, for instance for interceptors
if self.external_jars is not None:
cmd += "for file in %s; do CLASSPATH=$CLASSPATH:$file; done; " % self.external_jars
cmd += "export CLASSPATH; "
cmd += " %s %s" % (self.path.script("kafka-run-class.sh", node),
self.java_class_name())
cmd += " --consumer.config %s" % MirrorMaker.CONSUMER_CONFIG
cmd += " --producer.config %s" % MirrorMaker.PRODUCER_CONFIG
cmd += " --offset.commit.interval.ms %s" % str(self.offset_commit_interval_ms)
if isinstance(self.num_streams, int):
cmd += " --num.streams %d" % self.num_streams
else:
# config num_streams separately on each node
cmd += " --num.streams %d" % self.num_streams[self.idx(node) - 1]
if self.whitelist is not None:
cmd += " --whitelist=\"%s\"" % self.whitelist
cmd += " 1>> %s 2>> %s &" % (MirrorMaker.LOG_FILE, MirrorMaker.LOG_FILE)
return cmd
def pids(self, node):
return node.account.java_pids(self.java_class_name())
def alive(self, node):
return len(self.pids(node)) > 0
def start_node(self, node):
node.account.ssh("mkdir -p %s" % MirrorMaker.PERSISTENT_ROOT, allow_fail=False)
node.account.ssh("mkdir -p %s" % MirrorMaker.LOG_DIR, allow_fail=False)
self.security_config = self.source.security_config.client_config()
self.security_config.setup_node(node)
# Create, upload one consumer config file for source cluster
consumer_props = self.render("mirror_maker_consumer.properties")
consumer_props += str(self.security_config)
node.account.create_file(MirrorMaker.CONSUMER_CONFIG, consumer_props)
self.logger.info("Mirrormaker consumer props:\n" + consumer_props)
# Create, upload producer properties file for target cluster
producer_props = self.render('mirror_maker_producer.properties')
producer_props += str(self.security_config)
self.logger.info("Mirrormaker producer props:\n" + producer_props)
node.account.create_file(MirrorMaker.PRODUCER_CONFIG, producer_props)
# Create and upload log properties
log_config = self.render('tools_log4j.properties', log_file=MirrorMaker.LOG_FILE)
node.account.create_file(MirrorMaker.LOG4J_CONFIG, log_config)
# Run mirror maker
cmd = self.start_cmd(node)
self.logger.debug("Mirror maker command: %s", cmd)
node.account.ssh(cmd, allow_fail=False)
wait_until(lambda: self.alive(node), timeout_sec=30, backoff_sec=.5,
err_msg="Mirror maker took to long to start.")
self.logger.debug("Mirror maker is alive")
def stop_node(self, node, clean_shutdown=True):
node.account.kill_java_processes(self.java_class_name(), allow_fail=True,
clean_shutdown=clean_shutdown)
wait_until(lambda: not self.alive(node), timeout_sec=30, backoff_sec=.5,
err_msg="Mirror maker took to long to stop.")
def clean_node(self, node):
if self.alive(node):
self.logger.warn("%s %s was still alive at cleanup time. Killing forcefully..." %
(self.__class__.__name__, node.account))
node.account.kill_java_processes(self.java_class_name(), clean_shutdown=False,
allow_fail=True)
node.account.ssh("rm -rf %s" % MirrorMaker.PERSISTENT_ROOT, allow_fail=False)
self.security_config.clean_node(node)
def java_class_name(self):
return "kafka.tools.MirrorMaker"