[
https://issues.apache.org/jira/browse/BEAM-17?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15348444#comment-15348444
]
Amit Sela edited comment on BEAM-17 at 9/21/16 11:44 AM:
---------------------------------------------------------
Since the SDK has moved to the Apache Incubator, it now provides a Runner API
and "matching" InputFormats doesn't seem like the "Beam way".
Instead, it seems that a solution in the form of creating an RDD backed by
BoundedSource makes more sense.
was (Author: amitsela):
Implementing for next gen. Spark runner - Spark 2.x
> Add support for new Beam Source API
> -----------------------------------
>
> Key: BEAM-17
> URL: https://issues.apache.org/jira/browse/BEAM-17
> Project: Beam
> Issue Type: Improvement
> Components: runner-spark
> Reporter: Amit Sela
> Assignee: Amit Sela
>
> The API is discussed in
> https://cloud.google.com/dataflow/model/sources-and-sinks#creating-sources
> To implement this, we need to add support for
> com.google.cloud.dataflow.sdk.io.Read in TransformTranslator. This can be
> done by creating a new SourceInputFormat class that translates from a DF
> Source to a Hadoop InputFormat. The two concepts are pretty-well aligned
> since they both have the concept of splits and readers.
> Note that when there's a native HadoopSource in DF, it will need
> special-casing in the code for Read since we'll be able to use the underlying
> InputFormat directly.
> This could be tested using XmlSource from the SDK.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
