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https://issues.apache.org/jira/browse/SPARK-7192?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen resolved SPARK-7192.
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Resolution: Not A Problem
I'm resolving as "Not a Problem." Please comment / re-open if you can explain
why Python's arbitrary precision integer support is a problem here or tell me
whether I've overlooked something here.
> Pyspark casts hive bigint to int
> --------------------------------
>
> Key: SPARK-7192
> URL: https://issues.apache.org/jira/browse/SPARK-7192
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.3.0
> Reporter: Tamas Jambor
>
> It seems that pyspark reads bigint from hive and stores it as an int:
> >> hive_ctx = HiveContext(sc)
> >> data = hive_ctx.sql("select col1, col2 from dataset1")
> >> data
> DataFrame[col1: int, col2: bigint]
> >> c_t = [type(v) for v in data.collect()[0]]
> >> c_t
> [int, int]
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