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Posted to issues@spark.apache.org by "Sameer Agarwal (JIRA)" <ji...@apache.org> on 2016/06/01 01:28:12 UTC
[jira] [Updated] (SPARK-15678) Not use cache on appends and
overwrites
[ https://issues.apache.org/jira/browse/SPARK-15678?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sameer Agarwal updated SPARK-15678:
-----------------------------------
Summary: Not use cache on appends and overwrites (was: Drop cache on appends and overwrites)
> Not use cache on appends and overwrites
> ---------------------------------------
>
> Key: SPARK-15678
> URL: https://issues.apache.org/jira/browse/SPARK-15678
> Project: Spark
> Issue Type: Bug
> Affects Versions: 2.0.0
> Reporter: Sameer Agarwal
>
> SparkSQL currently doesn't drop caches if the underlying data is overwritten.
> {code}
> val dir = "/tmp/test"
> sqlContext.range(1000).write.mode("overwrite").parquet(dir)
> val df = sqlContext.read.parquet(dir).cache()
> df.count() // outputs 1000
> sqlContext.range(10).write.mode("overwrite").parquet(dir)
> sqlContext.read.parquet(dir).count() // outputs 1000 instead of 10 <---- We are still using the cached dataset
> {code}
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