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ASF GitHub Bot logged work on BEAM-9434: ---------------------------------------- Author: ASF GitHub Bot Created on: 09/Mar/20 17:29 Start Date: 09/Mar/20 17:29 Worklog Time Spent: 10m Work Description: lukecwik commented on issue #11037: [BEAM-9434] performance improvements reading many Avro files in S3 URL: https://github.com/apache/beam/pull/11037#issuecomment-596669808 I understand what your saying and how your solution resolves the problem. I'm trying to say that the problem shouldn't occur in the first place because [AvroIO.read](https://github.com/apache/beam/blob/a4ab76881d843a17906d866f0d6225def82ea6d0/sdks/java/core/src/main/java/org/apache/beam/sdk/io/AvroIO.java#L1030) should expand to [MatchAll](https://github.com/apache/beam/blob/060d0874e0c831a71ca6b240c66c04d367c8793d/sdks/java/core/src/main/java/org/apache/beam/sdk/io/FileIO.java#L622) that contains a [Reshuffle](https://github.com/apache/beam/blob/060d0874e0c831a71ca6b240c66c04d367c8793d/sdks/java/core/src/main/java/org/apache/beam/sdk/io/FileIO.java#L641) followed by [ReadMatches](https://github.com/apache/beam/blob/060d0874e0c831a71ca6b240c66c04d367c8793d/sdks/java/core/src/main/java/org/apache/beam/sdk/io/FileIO.java#L690) Reshuffle should ensure that there is either a repartition between MatchAll and ReadMatches, is it missing? If it isn't missing, they why is the following stage only executing on a single machine? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org Issue Time Tracking ------------------- Worklog Id: (was: 400244) Time Spent: 2h 10m (was: 2h) > Performance improvements processing a large number of Avro files in S3+Spark > ---------------------------------------------------------------------------- > > Key: BEAM-9434 > URL: https://issues.apache.org/jira/browse/BEAM-9434 > Project: Beam > Issue Type: Improvement > Components: io-java-aws, sdk-java-core > Affects Versions: 2.19.0 > Reporter: Emiliano Capoccia > Assignee: Emiliano Capoccia > Priority: Minor > Time Spent: 2h 10m > Remaining Estimate: 0h > > There is a performance issue when processing a large number of small Avro > files in Spark on K8S (tens of thousands or more). > The recommended way of reading a pattern of Avro files in Beam is by means of: > > {code:java} > PCollection<AvroGenClass> records = p.apply(AvroIO.read(AvroGenClass.class) > .from("s3://my-bucket/path-to/*.avro").withHintMatchesManyFiles()) > {code} > However, in the case of many small files, the above results in the entire > reading taking place in a single task/node, which is considerably slow and > has scalability issues. > The option of omitting the hint is not viable, as it results in too many > tasks being spawn, and the cluster being busy doing coordination of tiny > tasks with high overhead. > There are a few workarounds on the internet which mainly revolve around > compacting the input files before processing, so that a reduced number of > bulky files is processed in parallel. > -- This message was sent by Atlassian Jira (v8.3.4#803005)