Hi,
If you are expressing a job that contains three pairs of source->sinks that
are isolated from each other, then Flink supports this form of Job.
It is not much different from a single source->sink, just changed from a
DataStream to three DataStreams.
For example,
*DataStream ds1 = xxx*
*ds1.addSink();*
*DataStream ds2 = xxx*
*ds2.addSink();*
*DataStream ds3 = xxx*
*ds3.addSink();*
Thanks, vino.
Flink Developer 于2018年11月11日周日 上午9:24写道：
> How can I configure 1 Flink Job (stream execution environment, parallelism
> set to 10) to have multiple kafka sources where each has its' own sink to
> s3.
>
> For example, let's say the sources are:
>
>1. Kafka Topic A - Consumer (10 partitions)
>2. Kafka Topic B - Consumer (10 partitions)
>3. Kafka Topic C - Consumer (10 partitions)
>
> And let's say the sinks are:
>
>1. BucketingSink to S3 in bucket: s3://kafka_topic_a/
>2. BucketingSink to S3 in bucket: s3://kafka_topic_b/
>3. BucketingSink to S3 in bucket: s3://kafka_topic_c/
>
> And between source 1 to sink 1, I would like to perform unique processing.
> Between source 2 to sink 2, it should have unique processing and between
> source 3 to sink 3, it should also have unique processing.
>
> How can this be achieved? Is there an example?
>
