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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/01/23 14:01:39 UTC
[jira] [Resolved] (SPARK-6922) RDD.cartesian is much slower than
join
[ https://issues.apache.org/jira/browse/SPARK-6922?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-6922.
------------------------------
Resolution: Duplicate
Yes, a likely subset of SPARK-6307. I'm closing this since I don't see it's likely that there will be separate activity here.
> RDD.cartesian is much slower than join
> --------------------------------------
>
> Key: SPARK-6922
> URL: https://issues.apache.org/jira/browse/SPARK-6922
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.3.0
> Environment: Ubuntu 12.04.5, Spark 1.3.0 CDH 4 binary, standalone
> Reporter: David Tolnay
>
> Cartesian takes 3 minutes to join 500x500 partitions. Join with a constant key takes only 4 seconds. Here is a deterministic repro:
> {code}
> val lst = List.fill(500)(Tuple1(0))
> val df = sqlContext.createDataFrame(lst).repartition(500)
> df.select($"_1".as("a")).saveAsParquetFile("file:///tmp/parquet/left")
> df.select($"_1".as("b")).saveAsParquetFile("file:///tmp/parquet/right")
> val left = sqlContext.parquetFile("file:///tmp/parquet/left")
> val right = sqlContext.parquetFile("file:///tmp/parquet/right")
> def time[A](f: => A) = {
> val start = System.nanoTime
> f
> (System.nanoTime-start)/1e6
> }
> time { left.rdd.cartesian(right.rdd).count } // 3 minutes
> time { left.rdd.keyBy(_=>0).join(right.rdd.keyBy(_=>0)).count } // 4 seconds
> {code}
> Possibly related to SPARK-6307 in which cartesian causes the block manager to fetch the same blocks over and over.
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