[ https://issues.apache.org/jira/browse/SPARK-7192?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Josh Rosen resolved SPARK-7192. ------------------------------- 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] -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org