Niel Markwick created BEAM-6887:
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Summary: Streaming Spanner Writer transform
Key: BEAM-6887
URL: https://issues.apache.org/jira/browse/BEAM-6887
Project: Beam
Issue Type: New Feature
Components: io-java-gcp
Reporter: Niel Markwick
Assignee: Niel Markwick
At present, the[
SpannerIO.Write(Grouped|http://go/gh/apache/beam/blob/master/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/spanner/SpannerIO.java#L892])
transform works by collecting an entire bundle of elements, sorts them by
table/key, splitting the sorted list into batches (by size and number of cells
modified) and then writes each batch to Spanner in a single transaction.
It returns an[
object|https://github.com/apache/beam/blob/master/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/spanner/SpannerWriteResult.java]
containing :
# a PCollection<Void> (the main output) - which will have no elements but will
be closed to signal when all the input elements have been written (which is
never in streaming because input is unbounded)
# a PCollection<MutationGroup> of elements that failed to write.
This transform is useful as a bulk sink for data because it efficiently writes
large amounts of data.
It is not at all useful as an intermediate step in a streaming pipeline -
because it has no useful output in streaming mode.
I propose that we have a separate Spanner Write transform which simply writes
each input Mutation to the database, and then pushes successful Mutations onto
its output.
This would allow use in the middle of a streaming pipeline, where the flow
would be
* Some data streamed in
* Converted to Spanner Mutations
* Written to Spanner Database
* Further processing where the values written to the Spanner Database are used.
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