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https://issues.apache.org/jira/browse/SPARK-10287?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yin Huai updated SPARK-10287:
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Target Version/s: (was: 1.5.0)
> After processing a query using JSON data, Spark SQL continuously refreshes
> metadata of the table
> ------------------------------------------------------------------------------------------------
>
> Key: SPARK-10287
> URL: https://issues.apache.org/jira/browse/SPARK-10287
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Yin Huai
> Assignee: Yin Huai
> Priority: Critical
> Fix For: 1.5.1
>
>
> I have a partitioned json table with 1824 partitions.
> {code}
> val df = sqlContext.read.format("json").load("aPartitionedJsonData")
> val columnStr = df.schema.map(_.name).mkString(",")
> println(s"columns: $columnStr")
> val hash = df
> .selectExpr(s"hash($columnStr) as hashValue")
> .groupBy()
> .sum("hashValue")
> .head()
> .getLong(0)
> {code}
> Looks like for JSON, we refresh metadata when we call buildScan. For a
> partitioned table, we call buildScan for every partition. So, looks like we
> will refresh this table 1824 times.
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