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Will Uto commented on SPARK-26943: ---------------------------------- Thanks for the information - I was hoping that if I e.g. installed PySpark v2.4.0 in each Python Virtual Environment on each cluster worker/node, then I could run against Spark v2.4.0, but it sounds like I would need to upgrade Spark through something like Cloudera Manager. > Weird behaviour with `.cache()` > ------------------------------- > > Key: SPARK-26943 > URL: https://issues.apache.org/jira/browse/SPARK-26943 > Project: Spark > Issue Type: Bug > Components: PySpark > Affects Versions: 2.1.0 > Reporter: Will Uto > Priority: Major > > > {code:java} > sdf.count(){code} > > works fine. However: > > {code:java} > sdf = sdf.cache() > sdf.count() > {code} > does not, and produces error > {code:java} > Py4JJavaError: An error occurred while calling o314.count. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 75 > in stage 8.0 failed 4 times, most recent failure: Lost task 75.3 in stage 8.0 > (TID 438, uat-datanode-02, executor 1): java.text.ParseException: Unparseable > number: "(N/A)" > at java.text.NumberFormat.parse(NumberFormat.java:350) > {code} -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org