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https://issues.apache.org/jira/browse/SPARK-26509?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16765719#comment-16765719
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Jialin Qiao commented on SPARK-26509:
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You can add this conf. It works for me
{{spark.conf.set("spark.sql.parquet.enableVectorizedReader", "false")}}
https://stackoverflow.com/questions/52588408/unsupported-encoding-delta-byte-array-while-writing-parquet-data-to-csv-using
> Parquet DELTA_BYTE_ARRAY is not supported in Spark 2.x's Vectorized Reader
> --------------------------------------------------------------------------
>
> Key: SPARK-26509
> URL: https://issues.apache.org/jira/browse/SPARK-26509
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 2.4.0
> Reporter: Filipe Gonzaga Miranda
> Priority: Major
> Original Estimate: 40h
> Remaining Estimate: 40h
>
> I get the exception below Spark 2.4 reading parquet files where some columns
> are DELTA_BYTE_ARRAY encoded.
>
> {code:java}
> java.lang.UnsupportedOperationException: Unsupported encoding:
> DELTA_BYTE_ARRAY
>
> {code}
>
> If the property:
> spark.sql.parquet.enableVectorizedReader is set to false that works
> The parquet files were written with Parquet V2, and as far as I understand
> the V2 is the version used in Spark 2.x.
> I did not find any property to change which Parquet Version Spark uses (V1,
> V2).
> Is there anyway to benefit from the Vectorized Reader? Or this is something
> like a new implementation to support this version? I would propose so.
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