mirror of https://github.com/apache/kafka.git
99 lines
4.1 KiB
Python
99 lines
4.1 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ducktape.mark.resource import cluster
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from ducktape.tests.test import Test
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from kafkatest.services.kafka import KafkaService
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from kafkatest.services.streams import StreamsNamedRepartitionTopicService
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from kafkatest.services.verifiable_producer import VerifiableProducer
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from kafkatest.services.zookeeper import ZookeeperService
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from kafkatest.tests.streams.utils import verify_stopped, stop_processors, verify_running
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class StreamsNamedRepartitionTopicTest(Test):
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"""
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Tests using a named repartition topic by starting
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application then doing a rolling upgrade with added
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operations and the application still runs
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"""
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input_topic = 'inputTopic'
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aggregation_topic = 'aggregationTopic'
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pattern = 'AGGREGATED'
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stopped_message = 'NAMED_REPARTITION_TEST Streams Stopped'
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def __init__(self, test_context):
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super(StreamsNamedRepartitionTopicTest, self).__init__(test_context)
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self.topics = {
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self.input_topic: {'partitions': 6},
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self.aggregation_topic: {'partitions': 6}
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}
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self.zookeeper = ZookeeperService(self.test_context, num_nodes=1)
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self.kafka = KafkaService(self.test_context, num_nodes=3,
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zk=self.zookeeper, topics=self.topics)
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self.producer = VerifiableProducer(self.test_context,
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1,
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self.kafka,
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self.input_topic,
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throughput=1000,
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acks=1)
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@cluster(num_nodes=8)
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def test_upgrade_topology_with_named_repartition_topic(self):
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self.zookeeper.start()
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self.kafka.start()
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processor1 = StreamsNamedRepartitionTopicService(self.test_context, self.kafka)
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processor2 = StreamsNamedRepartitionTopicService(self.test_context, self.kafka)
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processor3 = StreamsNamedRepartitionTopicService(self.test_context, self.kafka)
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processors = [processor1, processor2, processor3]
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self.producer.start()
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for processor in processors:
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processor.CLEAN_NODE_ENABLED = False
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self.set_topics(processor)
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verify_running(processor, 'REBALANCING -> RUNNING')
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self.verify_processing(processors)
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# do rolling upgrade
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for processor in processors:
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verify_stopped(processor, self.stopped_message)
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# will tell app to add operations before repartition topic
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processor.ADD_ADDITIONAL_OPS = 'true'
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verify_running(processor, 'UPDATED Topology')
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self.verify_processing(processors)
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stop_processors(processors, self.stopped_message)
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self.producer.stop()
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self.kafka.stop()
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self.zookeeper.stop()
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def verify_processing(self, processors):
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for processor in processors:
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with processor.node.account.monitor_log(processor.STDOUT_FILE) as monitor:
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monitor.wait_until(self.pattern,
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timeout_sec=60,
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err_msg="Never saw processing of %s " % self.pattern + str(processor.node.account))
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def set_topics(self, processor):
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processor.INPUT_TOPIC = self.input_topic
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processor.AGGREGATION_TOPIC = self.aggregation_topic
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