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https://issues.apache.org/jira/browse/SPARK-15678?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15877575#comment-15877575
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Kazuaki Ishizaki edited comment on SPARK-15678 at 2/22/17 6:37 AM:
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How about inserting {{spark.catalog.refreshByPath()}} as follows?
{code}
spark.range(1000).write.mode("overwrite").parquet(dir)
spark.catalog.refreshByPath(dir) // insert a NEW statement
val df1 = spark.read.parquet(dir)
df1.count
f(df1).count
{code}
was (Author: kiszk):
How about insert {{spark.catalog.refreshByPath()}} as follows?
{code}
spark.range(1000).write.mode("overwrite").parquet(dir)
spark.catalog.refreshByPath(dir) // insert a NEW statement
val df1 = spark.read.parquet(dir)
df1.count
f(df1).count
{code}
> 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}
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