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Apache Spark commented on SPARK-33228: -------------------------------------- User 'viirya' has created a pull request for this issue: https://github.com/apache/spark/pull/30152 > Don't uncache data when replacing an existing view having the same plan > ----------------------------------------------------------------------- > > Key: SPARK-33228 > URL: https://issues.apache.org/jira/browse/SPARK-33228 > Project: Spark > Issue Type: Improvement > Components: SQL > Affects Versions: 2.4.8, 3.0.2, 3.1.0 > Reporter: Takeshi Yamamuro > Assignee: Takeshi Yamamuro > Priority: Major > Fix For: 2.4.8, 3.0.2, 3.1.0 > > > SPARK-30494's updated the `CreateViewCommand` code to implicitly drop cache > when replacing an existing view. But, this change drops cache even when > replacing a view having the same logical plan. A sequence of queries to > reproduce this as follows; > {code} > scala> val df = spark.range(1).selectExpr("id a", "id b") > scala> df.cache() > scala> df.explain() > == Physical Plan == > *(1) ColumnarToRow > +- InMemoryTableScan [a#2L, b#3L] > +- InMemoryRelation [a#2L, b#3L], StorageLevel(disk, memory, deserialized, 1 > replicas) > +- *(1) Project [id#0L AS a#2L, id#0L AS b#3L] > +- *(1) Range (0, 1, step=1, splits=4) > scala> df.createOrReplaceTempView("t") > scala> sql("select * from t").explain() > == Physical Plan == > *(1) ColumnarToRow > +- InMemoryTableScan [a#2L, b#3L] > +- InMemoryRelation [a#2L, b#3L], StorageLevel(disk, memory, deserialized, 1 > replicas) > +- *(1) Project [id#0L AS a#2L, id#0L AS b#3L] > +- *(1) Range (0, 1, step=1, splits=4) > // If one re-runs the same query `df.createOrReplaceTempView("t")`, the > cache's swept away > scala> df.createOrReplaceTempView("t") > scala> sql("select * from t").explain() > == Physical Plan == > *(1) Project [id#0L AS a#2L, id#0L AS b#3L] > +- *(1) Range (0, 1, step=1, splits=4) > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org