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Posted to issues@spark.apache.org by "Suchintak Patnaik (Jira)" <ji...@apache.org> on 2019/10/30 03:39:00 UTC
[jira] [Comment Edited] (SPARK-29621) Querying internal corrupt
record column should not be allowed in filter operation
[ https://issues.apache.org/jira/browse/SPARK-29621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16962658#comment-16962658 ]
Suchintak Patnaik edited comment on SPARK-29621 at 10/30/19 3:38 AM:
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[~hyukjin.kwon]As per this,
As per *https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala#L119-L126)*,
it should not allow referencing only internal corrupt column right??
Then how come df.filter(df._corrupt_record.isNotNull()).count() shows error and df.filter(df._corrupt_record.isNotNull()).show() doesn't??
was (Author: patnaik):
[~gurwls223] it should not allow referencing only internal corrupt record right??
Then how come filter.count() shows error and filter.show() doesn't??
> Querying internal corrupt record column should not be allowed in filter operation
> ---------------------------------------------------------------------------------
>
> Key: SPARK-29621
> URL: https://issues.apache.org/jira/browse/SPARK-29621
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.3.0
> Reporter: Suchintak Patnaik
> Priority: Major
> Labels: PySpark, SparkSQL
>
> As per *https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala#L119-L126)*,
> _"Since Spark 2.3, the queries from raw JSON/CSV files are disallowed when the referenced columns only include the internal corrupt record column"_
> But it's allowing while querying only the internal corrupt record column in case of *filter* operation.
> {code}
> from pyspark.sql.types import *
> schema = StructType([
> StructField("_corrupt_record", StringType(), False),
> StructField("Name", StringType(), False),
> StructField("Colour", StringType(), True),
> StructField("Price", IntegerType(), True),
> StructField("Quantity", IntegerType(), True)])
> df = spark.read.csv("fruit.csv", schema=schema, mode="PERMISSIVE")
> df.filter(df._corrupt_record.isNotNull()).show() # Allowed
> {code}
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