Key by Task number

[robert]

I am trying to use the task number as a keyby value to help fan out the work load reading from kafka.

Given:

       DataStream<SchemaRecord> stream =

                env.addSource(new FlinkKafkaConsumer010<SchemaRecord>("topicA", schema, properties)

                ).setParallelism(240).flatMap(new SchemaRecordSplit()).setParallelism(240).

                        name("TopicA splitter").keyBy("partition", "keyByHelper", "schemaId");

        stream.addSink(new CustomMaprFsSink()).name("TopicA Sink").setParallelism(240);

In the DeserialClass I am trying to get to the 

getRuntimeContext().getIndexOfThisSubtask(); 

Which is only avaliable in the RichSinkFunction

The above is partition (by hour) , schemaID (avro schemaId) and I would like to add the task number so that all 240 readers / writers have something to do.

Any ideas ?

[Kamil Dziublinski]

I am not sure if you really need a keyby, your load will be distributed among your map function without it.  But could you explain a bit what is your sink doing?

As for setting parallelism on the consumer remember that you wont have higher parallelism than number of partitions in your topic.

If you have 240 partitions that's fine, but if you have less than other subtasks will be idle. Only one task can read from one partition in parallel.

On Tue, Apr 18, 2017 at 3:38 PM Telco Phone <[hidden email]> wrote:

I am trying to use the task number as a keyby value to help fan out the work load reading from kafka.

Given:

       DataStream<SchemaRecord> stream =

                env.addSource(new FlinkKafkaConsumer010<SchemaRecord>("topicA", schema, properties)

                ).setParallelism(240).flatMap(new SchemaRecordSplit()).setParallelism(240).

                        name("TopicA splitter").keyBy("partition", "keyByHelper", "schemaId");

        stream.addSink(new CustomMaprFsSink()).name("TopicA Sink").setParallelism(240);

In the DeserialClass I am trying to get to the 

getRuntimeContext().getIndexOfThisSubtask(); 

Which is only avaliable in the RichSinkFunction

The above is partition (by hour) , schemaID (avro schemaId) and I would like to add the task number so that all 240 readers / writers have something to do.

Any ideas ?

[Chesnay Schepler]

If the number of combinations between partition and schemaID is limited then the subtask index could actually improve the distribution of values.

In any case, the easiest way to do this is to add a RichMapFunction after the flatMap, or modify the flatMap, to also include the subtask index.
Typically this would be done by creating a Tuple2 containing the index and value.

On 18.04.2017 15:43, Kamil Dziublinski wrote:

I am not sure if you really need a keyby, your load will be distributed among your map function without it.  But could you explain a bit what is your sink doing?

As for setting parallelism on the consumer remember that you wont have higher parallelism than number of partitions in your topic.

If you have 240 partitions that's fine, but if you have less than other subtasks will be idle. Only one task can read from one partition in parallel.

On Tue, Apr 18, 2017 at 3:38 PM Telco Phone <[hidden email]> wrote:

I am trying to use the task number as a keyby value to help fan out the work load reading from kafka.

Given:

       DataStream<SchemaRecord> stream =

                env.addSource(new FlinkKafkaConsumer010<SchemaRecord>("topicA", schema, properties)

                ).setParallelism(240).flatMap(new SchemaRecordSplit()).setParallelism(240).

                        name("TopicA splitter").keyBy("partition", "keyByHelper", "schemaId");

        stream.addSink(new CustomMaprFsSink()).name("TopicA Sink").setParallelism(240);

In the DeserialClass I am trying to get to the 

getRuntimeContext().getIndexOfThisSubtask(); 

Which is only avaliable in the RichSinkFunction

The above is partition (by hour) , schemaID (avro schemaId) and I would like to add the task number so that all 240 readers / writers have something to do.

Any ideas ?

[robert]

Do you have a small example or a link to a doc that has one ?

---

From: Chesnay Schepler <[hidden email]>
To: [hidden email]
Sent: Tuesday, April 18, 2017 8:16 AM
Subject: Re: Key by Task number

If the number of combinations between partition and schemaID is limited then the subtask index could actually improve the distribution of values.

In any case, the easiest way to do this is to add a RichMapFunction after the flatMap, or modify the flatMap, to also include the subtask index.
Typically this would be done by creating a Tuple2 containing the index and value.

On 18.04.2017 15:43, Kamil Dziublinski wrote:

I am not sure if you really need a keyby, your load will be distributed among your map function without it.  But could you explain a bit what is your sink doing?

As for setting parallelism on the consumer remember that you wont have higher parallelism than number of partitions in your topic.

If you have 240 partitions that's fine, but if you have less than other subtasks will be idle. Only one task can read from one partition in parallel.

On Tue, Apr 18, 2017 at 3:38 PM Telco Phone <[hidden email]> wrote:

I am trying to use the task number as a keyby value to help fan out the work load reading from kafka.

Given:

       DataStream<SchemaRecord> stream =

                env.addSource(new FlinkKafkaConsumer010<SchemaRecord>("topicA", schema, properties)

                ).setParallelism(240).flatMap(new SchemaRecordSplit()).setParallelism(240).

                        name("TopicA splitter").keyBy("partition", "keyByHelper", "schemaId");

        stream.addSink(new CustomMaprFsSink()).name("TopicA Sink").setParallelism(240);

In the DeserialClass I am trying to get to the 

getRuntimeContext().getIndexOfThisSubtask(); 

Which is only avaliable in the RichSinkFunction

The above is partition (by hour) , schemaID (avro schemaId) and I would like to add the task number so that all 240 readers / writers have something to do.

Any ideas ?