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https://issues.apache.org/jira/browse/SPARK-20110?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16974177#comment-16974177
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hurelhuyag commented on SPARK-20110:
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I just faced same problem now. It's spark version 2.4.4. I don't understand
what's difference. 2 query doing same thing. If first is wrong then second
should wrong.
> Windowed aggregation do not work when the timestamp is a nested field
> ---------------------------------------------------------------------
>
> Key: SPARK-20110
> URL: https://issues.apache.org/jira/browse/SPARK-20110
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 2.1.0
> Reporter: Alexis Seigneurin
> Priority: Major
> Labels: bulk-closed
>
> I am loading data into a DataFrame with nested fields. I want to perform a
> windowed aggregation on the timestamp from a nested fields:
> {code}
> .groupBy(window($"auth.sysEntryTimestamp", "2 minutes"))
> {code}
> I get the following error:
> {quote}
> org.apache.spark.sql.AnalysisException: Multiple time window expressions
> would result in a cartesian product of rows, therefore they are not currently
> not supported.
> {quote}
> This works fine if I first extract the timestamp to a separate column:
> {code}
> .withColumn("sysEntryTimestamp", $"auth.sysEntryTimestamp")
> .groupBy(
> window($"sysEntryTimestamp", "2 minutes")
> )
> {code}
> Please see the whole sample:
> - batch:
> https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/4683710270868386/4278399007363210/3769253384867782/latest.html
> - Structured Streaming:
> https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/4683710270868386/4278399007363192/3769253384867782/latest.html
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