[jira] [Created] (FLINK-9166) Performance issue with Flink SQL

["SUBRAMANYA SURESH (JIRA)" <ji...@apache.org>]

SUBRAMANYA SURESH created FLINK-9166:
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             Summary: Performance issue with Flink SQL
                 Key: FLINK-9166
                 URL: https://issues.apache.org/jira/browse/FLINK-9166
             Project: Flink
          Issue Type: Bug
          Components: Table API & SQL
    Affects Versions: 1.4.2
            Reporter: SUBRAMANYA SURESH


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. 
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).

*Query:*
{code:java}
 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}
*Code:*
{code:java}
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;
}
{code}



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