GitHub user sameeragarwal opened a pull request:
https://github.com/apache/spark/pull/13566
[SPARK-15678] Add support to REFRESH data source paths
## What changes were proposed in this pull request?
Spark currently incorrectly continues to use cached data even if the
underlying data is overwritten.
Current behavior:
```scala
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 <---- We are still
using the cached dataset
```
This patch fixes this bug by adding support for `REFRESH path` that
invalidates and refreshes all the cached data (and the associated metadata) for
any dataframe that contains the given data source path.
Expected behavior:
```scala
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)
spark.catalog.refreshResource(dir)
sqlContext.read.parquet(dir).count() // outputs 10 <---- We are not using
the cached dataset
```
## How was this patch tested?
Unit tests for overwrites and appends in `ParquetQuerySuite` and
`CachedTableSuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/sameeragarwal/spark refresh-path-2
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/13566.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #13566
----
commit ece34abd63176c6192ebe4ef05f2e8799ff52955
Author: Sameer Agarwal <[email protected]>
Date: 2016-06-06T23:15:42Z
[SPARK-15678] Add support to REFRESH data source paths
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