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https://issues.apache.org/jira/browse/SPARK-35744?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17363119#comment-17363119
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Steven Aerts commented on SPARK-35744:
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[~xkrogen] in the past we use them solely in RDD's as I guess is the most
common use case.
But we implemented an {{AvroSpecificRecordEncoder}} which is an
{{ExpressionEncoder}} which allows you to use them in the {{DataSet}} api.
Btw: this is custom code, but if any body is interested, we can push that one
upstream as it is an encoder for {{SpecifiRecord}}s which is faster than the
Generic avro encoder in spark as this one is codegened for the specific schema
you use.
> Performance degradation in avro SpecificRecordBuilders
> ------------------------------------------------------
>
> Key: SPARK-35744
> URL: https://issues.apache.org/jira/browse/SPARK-35744
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.2.0
> Reporter: Steven Aerts
> Priority: Minor
>
> Creating this bug to let you know that when we tested out spark 3.2.0 we saw
> a significant performance degradation where our code was handling Avro
> Specific Record objects. This slowed down some of our jobs with a factor 4.
> Spark 3.2.0 upsteps the avro version from 1.8.2 to 1.10.2.
> The degradation was caused by a change introduced in avro 1.9.0. This change
> degrades performance when creating avro specific records in certain
> classloader topologies, like the ones used in spark.
> We notified and [proposed|https://github.com/apache/avro/pull/1253] a simple
> fix upstream in the avro project. (Links contain more details)
> It is unclear for us how many other projects are using avro specific records
> in a spark context and will be impacted by this degradation.
> Feel free to close this issue if you think this issue is too much of a
> corner case.
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