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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-18211) Spark SQL ignores split.size
Date Wed, 02 Nov 2016 14:43:58 GMT

    [ https://issues.apache.org/jira/browse/SPARK-18211?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15629171#comment-15629171
] 

Sean Owen commented on SPARK-18211:
-----------------------------------

Actually, I take that back. I wonder if this is the issue? https://issues.apache.org/jira/browse/SPARK-18017

> Spark SQL ignores split.size
> ----------------------------
>
>                 Key: SPARK-18211
>                 URL: https://issues.apache.org/jira/browse/SPARK-18211
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: lostinoverflow
>
> I expect that RDD and DataFrame will have the same number of partitions (worked in 1.6)
but it looks like Spark SQL ignores Hadoop configuration.
> {code}
> import org.apache.spark.sql.SparkSession
> object App {
>   def main(args: Array[String]) {
>     val spark = SparkSession
>       .builder()
>       .master("local[*]")
>       .appName("split size")
>       .getOrCreate()
>     spark.sparkContext.hadoopConfiguration.setInt("mapred.min.split.size", args(0).toInt)
>     spark.sparkContext.hadoopConfiguration.setInt("mapred.max.split.size", args(0).toInt)
>     println(spark.sparkContext.textFile(args(1)).partitions.size)
>     println(spark.read.textFile(args(1)).rdd.partitions.size)
>     spark.stop()
>   }
> }
> {code}



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