Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/2164#discussion_r16802361
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/test/TestSQLContext.scala ---
@@ -18,8 +18,13 @@
package org.apache.spark.sql.test
import org.apache.spark.{SparkConf, SparkContext}
-import org.apache.spark.sql.SQLContext
+import org.apache.spark.sql.{SQLConf, SQLContext}
/** A SQLContext that can be used for local testing. */
object TestSQLContext
- extends SQLContext(new SparkContext("local", "TestSQLContext", new
SparkConf()))
+ extends SQLContext(new SparkContext("local", "TestSQLContext", new
SparkConf())) {
+
+ /** Fewer partitions to speed up testing. */
+ override private[spark] def numShufflePartitions: Int =
+ getConf(SQLConf.SHUFFLE_PARTITIONS, "5").toInt
--- End diff --
I guess parallelism isn't really what I meant, I'm thinking more about bugs
that could be related to expecting data to be copartitioned when it actually
isn't.
That said, perhaps the test should also run in `local[2]` or higher. We
have found a couple of bugs after deploying that are the result of concurrency
issues (scala reflection... i'm looking at you :P)
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