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https://issues.apache.org/jira/browse/SPARK-32046?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dustin Smith updated SPARK-32046:
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Labels: caching sql time (was: )
> current_timestamp called in a cache dataframe freezes the time for all future
> calls
> -----------------------------------------------------------------------------------
>
> Key: SPARK-32046
> URL: https://issues.apache.org/jira/browse/SPARK-32046
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.0, 2.4.4
> Reporter: Dustin Smith
> Priority: Minor
> Labels: caching, sql, time
>
> If I call current_timestamp 3 times while caching the dataframe variable in
> order to freeze that dataframes time, the 3rd dataframe time and beyond (4th,
> 5th, ...) will be frozen to the 2nd dataframe's time. The 1st dataframe and
> the 2nd will differ in time but will become static on the 3rd usage and
> beyond.
> Additionally, caching only caused 2 dataframes to cache skipping the 3rd.
> However,
> {code:java}
> val df = Seq(java.time.LocalDateTime.now.toString).toDF("datetime").cache
> df.count
> // this can be run 3 times no issue.
> // then later cast to TimestampType{code}
> doesn't have this problem and all 3 dataframes cache with correct times
> displaying.
> Running the code in shell and Jupyter or Zeppelin also produces different
> results. In the shell, you only get 1 time all 3 times.
>
> {code:java}
> val df1 = spark.range(1).select(current_timestamp as "datetime").cache
> df1.count
> df1.show(false)
> Thread.sleep(9500)
> val df2 = spark.range(1).select(current_timestamp as "datetime").cache
> df2.count
> df2.show(false)
> Thread.sleep(9500)
> val df3 = spark.range(1).select(current_timestamp as "datetime").cache
> df3.count
> df3.show(false){code}
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