[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`.

Author: Sameer Agarwal <sameer@databricks.com>

Closes #13566 from sameeragarwal/refresh-path-2.

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