Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/9991#discussion_r45949524
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/ui/SQLListenerSuite.scala
---
@@ -343,6 +343,8 @@ class SQLListenerMemoryLeakSuite extends SparkFunSuite {
.set("spark.sql.ui.retainedExecutions", "50") // Set it to 50 to run
this test quickly
val sc = new SparkContext(conf)
try {
+ // Clear the sql listener created by a previous test suite.
+ SQLContext.clearSqlListener()
--- End diff --
SPARK-11700 is a bit different. But my point is we should not keep a big
object in memory and don't provide an approach to clean it. In some user cases,
Spark SQL may be just one of some ETL steps. And if the user finishes his/her
work in Spark SQL, he/she usually wants to clean up all resources used by
SparkContext/SQLContext.
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