Apache Flink: Performance issue when running many jobs

Question

With a high number of Flink SQL queries (100 of below), the Flink command line client fails with a "JobManager did not respond within 600000 ms" on a Yarn cluster, i.e. the job is never started on the cluster.

JobManager logs has nothing after the last TaskManager started except DEBUG logs with "job with ID 5cd95f89ed7a66ec44f2d19eca0592f7 not found in JobManager", indicating its likely stuck (creating the ExecutionGraph?).
The same works as standalone java program locally (high CPU initially)
Note: Each Row in structStream contains 515 columns (many end up null) including a column that has the raw message.
In the YARN cluster we specify 18GB for TaskManager, 18GB for the JobManager, 5 slots each and parallelism of 725 (partitions in our Kafka source).

Flink SQL Query:

select count (*), 'idnumber' as criteria, Environment, CollectedTimestamp, 
       EventTimestamp, RawMsg, Source 
from structStream
where Environment='MyEnvironment' and Rule='MyRule' and LogType='MyLogType' 
      and Outcome='Success'
group by tumble(proctime, INTERVAL '1' SECOND), Environment, 
         CollectedTimestamp, EventTimestamp, RawMsg, Source

Code

public static void main(String[] args) throws Exception {
    FileSystems.newFileSystem(KafkaReadingStreamingJob.class
                             .getResource(WHITELIST_CSV).toURI(), new HashMap<>());

    final StreamExecutionEnvironment streamingEnvironment = getStreamExecutionEnvironment();
    final StreamTableEnvironment tableEnv = TableEnvironment.getTableEnvironment(streamingEnvironment);

    final DataStream<Row> structStream = getKafkaStreamOfRows(streamingEnvironment);
    tableEnv.registerDataStream("structStream", structStream);
    tableEnv.scan("structStream").printSchema();

    for (int i = 0; i < 100; i++) {
        for (String query : Queries.sample) {
            // Queries.sample has one query that is above. 
            Table selectQuery = tableEnv.sqlQuery(query);

            DataStream<Row> selectQueryStream =                                                 
                               tableEnv.toAppendStream(selectQuery, Row.class);
            selectQueryStream.print();
        }
    }

    // execute program
    streamingEnvironment.execute("Kafka Streaming SQL");
}

private static DataStream<Row> getKafkaStreamOfRows(StreamExecutionEnvironment environment) throws Exception {
    Properties properties = getKafkaProperties();

    // TestDeserializer deserializes the JSON to a ROW of string columns (515)
    // and also adds a column for the raw message. 
    FlinkKafkaConsumer011 consumer = new         
         FlinkKafkaConsumer011(KAFKA_TOPIC_TO_CONSUME, new TestDeserializer(getRowTypeInfo()), properties);
    DataStream<Row> stream = environment.addSource(consumer);

    return stream;
}

private static RowTypeInfo getRowTypeInfo() throws Exception {
    // This has 515 fields. 
    List<String> fieldNames = DDIManager.getDDIFieldNames();
    fieldNames.add("rawkafka"); // rawMessage added by TestDeserializer
    fieldNames.add("proctime");

    // Fill typeInformationArray with StringType to all but the last field which is of type Time
    .....
    return new RowTypeInfo(typeInformationArray, fieldNamesArray);
}

private static StreamExecutionEnvironment getStreamExecutionEnvironment() throws IOException {
    final StreamExecutionEnvironment env =                      
    StreamExecutionEnvironment.getExecutionEnvironment(); 
    env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);

    env.enableCheckpointing(60000);
    env.setStateBackend(new FsStateBackend(CHECKPOINT_DIR));
    env.setParallelism(725);
    return env;
}

private static DataStream<Row> getKafkaStreamOfRows(StreamExecutionEnvironment environment) throws Exception {
    Properties properties = getKafkaProperties();

    // TestDeserializer deserializes the JSON to a ROW of string columns (515)
    // and also adds a column for the raw message. 
    FlinkKafkaConsumer011 consumer = new FlinkKafkaConsumer011(KAFKA_TOPIC_TO_CONSUME, new  TestDeserializer(getRowTypeInfo()), properties);
    DataStream<Row> stream = environment.addSource(consumer);

    return stream;
}

private static RowTypeInfo getRowTypeInfo() throws Exception {
    // This has 515 fields. 
    List<String> fieldNames = DDIManager.getDDIFieldNames();
    fieldNames.add("rawkafka"); // rawMessage added by TestDeserializer
    fieldNames.add("proctime");

    // Fill typeInformationArray with StringType to all but the last field which is of type Time
    .....
    return new RowTypeInfo(typeInformationArray, fieldNamesArray);
}

private static StreamExecutionEnvironment getStreamExecutionEnvironment() throws IOException {
    final StreamExecutionEnvironment env =     StreamExecutionEnvironment.getExecutionEnvironment(); 
    env.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);

    env.enableCheckpointing(60000);
    env.setStateBackend(new FsStateBackend(CHECKPOINT_DIR));
    env.setParallelism(725);
    return env;
}

With the command line client timing out, and the JobManager being stuck, the job never gets beyond the initialization phase, so is unable to run the specified queries. I have tried to make it explicit in the question, thanks. — Subramanya Suresh
There is also a JIRA ticket in Flink with additional information: issues.apache.org/jira/browse/FLINK-9166 — Robert Metzger

Fabian Hueske Fabian Hueske · Accepted Answer · 2018-04-16T12:17:23

This looks to me as if the JobManager is overloaded with too many concurrently running jobs. I'd suggest to distribute the jobs to more JobManagers / Flink clusters.

Apache Flink: Performance issue when running many jobs

Flink SQL Query:

Code

1 Answers