Emiliano Capoccia created BEAM-9434:
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Summary: Performance improvements processiong 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
There is a performance issue when processing in Spark on K8S a large number of
small Avro files (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 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.
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