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Kazuaki Ishizaki commented on SPARK-15678: ------------------------------------------ Sorry for being late to reply. According to the comment of {{refreshByPath()}}, I think that it should work by calling {{refreshByPath()}} once. {quote} Invalidate and refresh all the cached data (and the associated metadata) for any dataframe that contains the given data source path. Path matching is by prefix, i.e. "/" would invalidate everything that is cached. {quote} I think that it is better to create a new JIRA entry. This JIRA entry is not for reporting issues of {{refreshByPath()}}. What do you think? > 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 > Assignee: Sameer Agarwal > Fix For: 2.0.0 > > > 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} -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org