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https://issues.apache.org/jira/browse/SPARK-42199?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-42199:
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Labels: pull-request-available (was: )
> groupByKey creates columns that may conflict with exising columns
> -----------------------------------------------------------------
>
> Key: SPARK-42199
> URL: https://issues.apache.org/jira/browse/SPARK-42199
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.3, 3.1.3, 3.2.3, 3.3.2, 3.4.0, 3.5.0
> Reporter: Enrico Minack
> Priority: Major
> Labels: pull-request-available
>
> Calling {{ds.groupByKey(func: V => K)}} creates columns to store the key
> value. These columns may conflict with columns that already exist in {{ds}}.
> Function {{Dataset.groupByKey.agg}} accounts for this with a very specific
> rule, which has some surprising weaknesses:
> {code:scala}
> spark.range(1)
> // groupByKey adds column 'value'
> .groupByKey(id => id)
> // which cannot be referenced, though it is suggested
> .agg(count("value"))
> {code}
> {code:java}
> org.apache.spark.sql.AnalysisException: Column 'value' does not exist. Did
> you mean one of the following? [value, id];
> {code}
> An existing 'value' column can be referenced:
> {code:scala}
> // dataset with column 'value'
> spark.range(1).select($"id".as("value")).as[Long]
> // groupByKey adds another column 'value'
> .groupByKey(id => id)
> // agg accounts for the extra column and excludes it when resolving 'value'
> .agg(count("value"))
> .show()
> {code}
> {code:java}
> +---+------------+
> |key|count(value)|
> +---+------------+
> | 0| 1|
> +---+------------+
> {code}
> While column suggestion shows both 'value' columns:
> {code:scala}
> spark.range(1).select($"id".as("value")).as[Long]
> .groupByKey(id => id)
> .agg(count("unknown"))
> {code}
> {code:java}
> org.apache.spark.sql.AnalysisException: Column 'unknown' does not exist. Did
> you mean one of the following? [value, value]
> {code}
> However, {{mapValues}} introduces another 'value' column, which should be
> referencable, but it breaks the exclusion introduced by {{agg}}:
> {code:scala}
> spark.range(1)
> // groupByKey adds column 'value'
> .groupByKey(id => id)
> // adds another 'value' column
> .mapValues(value => value)
> // which cannot be referenced in agg
> .agg(count("value"))
> {code}
> {code:java}
> org.apache.spark.sql.AnalysisException: Reference 'value' is ambiguous, could
> be: value, value.
> {code}
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