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Date: Tue, 4 Jul 2017 08:31:00 +0000 (UTC)
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Subject: [jira] [Commented] (FLINK-6996) FlinkKafkaProducer010 doesn't
 guarantee at-least-once semantic
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archived-at: Tue, 04 Jul 2017 08:31:05 -0000


    [ https://issues.apache.org/jira/browse/FLINK-6996?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16073315#comment-16073315 ] 

ASF GitHub Bot commented on FLINK-6996:
---------------------------------------

Github user pnowojski commented on a diff in the pull request:

    https://github.com/apache/flink/pull/4206#discussion_r125416757
  
    --- Diff: flink-connectors/flink-connector-kafka-base/src/test/java/org/apache/flink/streaming/connectors/kafka/KafkaProducerTestBase.java ---
    @@ -172,6 +195,144 @@ public void cancel() {
     		}
     	}
     
    +	/**
    +	 * Tests the at-least-once semantic for the simple writes into Kafka.
    +	 */
    +	@Test
    +	public void testOneToOneAtLeastOnceRegularSink() throws Exception {
    +		testOneToOneAtLeastOnce(true);
    +	}
    +
    +	/**
    +	 * Tests the at-least-once semantic for the simple writes into Kafka.
    +	 */
    +	@Test
    +	public void testOneToOneAtLeastOnceCustomOperator() throws Exception {
    +		testOneToOneAtLeastOnce(false);
    +	}
    +
    +	/**
    +	 * This test sets KafkaProducer so that it will not automatically flush the data and
    +	 * and fails the broker to check whether FlinkKafkaProducer flushed records manually on snapshotState.
    +	 */
    +	protected void testOneToOneAtLeastOnce(boolean regularSink) throws Exception {
    +		final String topic = regularSink ? "oneToOneTopicRegularSink" : "oneToOneTopicCustomOperator";
    +		final int partition = 0;
    +		final int numElements = 1000;
    +		final int failAfterElements = 333;
    +
    +		createTestTopic(topic, 1, 1);
    +
    +		TypeInformationSerializationSchema<Integer> schema = new TypeInformationSerializationSchema<>(BasicTypeInfo.INT_TYPE_INFO, new ExecutionConfig());
    +		KeyedSerializationSchema<Integer> keyedSerializationSchema = new KeyedSerializationSchemaWrapper(schema);
    +
    +		StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    +		env.enableCheckpointing(500);
    +		env.setParallelism(1);
    +		env.setRestartStrategy(RestartStrategies.noRestart());
    +		env.getConfig().disableSysoutLogging();
    +
    +		Properties properties = new Properties();
    +		properties.putAll(standardProps);
    +		properties.putAll(secureProps);
    +		// decrease timeout and block time from 60s down to 10s - this is how long KafkaProducer will try send pending (not flushed) data on close()
    +		properties.setProperty("timeout.ms", "10000");
    +		properties.setProperty("max.block.ms", "10000");
    +		// increase batch.size and linger.ms - this tells KafkaProducer to batch produced events instead of flushing them immediately
    +		properties.setProperty("batch.size", "10240000");
    +		properties.setProperty("linger.ms", "10000");
    +
    +		int leaderId = kafkaServer.getLeaderToShutDown(topic);
    +		BrokerRestartingMapper.resetState();
    +
    +		// process exactly failAfterElements number of elements and then shutdown Kafka broker and fail application
    +		DataStream<Integer> inputStream = env
    +			.fromCollection(getIntegersSequence(numElements))
    +			.map(new BrokerRestartingMapper<Integer>(leaderId, failAfterElements));
    +
    +		StreamSink<Integer> kafkaSink = kafkaServer.getProducerSink(topic, keyedSerializationSchema, properties, new FlinkKafkaPartitioner<Integer>() {
    +			@Override
    +			public int partition(Integer record, byte[] key, byte[] value, String targetTopic, int[] partitions) {
    +				return partition;
    +			}
    +		});
    +
    +		if (regularSink) {
    +			inputStream.addSink(kafkaSink.getUserFunction());
    +		}
    +		else {
    +			kafkaServer.produceIntoKafka(inputStream, topic, keyedSerializationSchema, properties, new FlinkKafkaPartitioner<Integer>() {
    +				@Override
    +				public int partition(Integer record, byte[] key, byte[] value, String targetTopic, int[] partitions) {
    +					return partition;
    +				}
    +			});
    +		}
    +
    +		FailingIdentityMapper.failedBefore = false;
    +		try {
    +			env.execute("One-to-one at least once test");
    +			fail("Job should fail!");
    +		}
    +		catch (Exception ex) {
    --- End diff --
    
    FYI `getCause` Exception is type of `java.lang.Exception`, so there is no point in making an assertion on that.


> FlinkKafkaProducer010 doesn't guarantee at-least-once semantic
> --------------------------------------------------------------
>
>                 Key: FLINK-6996
>                 URL: https://issues.apache.org/jira/browse/FLINK-6996
>             Project: Flink
>          Issue Type: Bug
>          Components: Kafka Connector
>    Affects Versions: 1.2.0, 1.3.0, 1.2.1, 1.3.1
>            Reporter: Piotr Nowojski
>            Assignee: Piotr Nowojski
>
> FlinkKafkaProducer010 doesn't implement CheckpointedFunction interface. This means, when it's used like a "regular sink function" (option a from [the java doc|https://ci.apache.org/projects/flink/flink-docs-master/api/java/org/apache/flink/streaming/connectors/kafka/FlinkKafkaProducer010.html]) it will not flush the data on "snapshotState"  as it is supposed to.


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