Hyukjin Kwon created SPARK-9814:
-----------------------------------
Summary: EqualNotNull not passing to data sources
Key: SPARK-9814
URL: https://issues.apache.org/jira/browse/SPARK-9814
Project: Spark
Issue Type: Improvement
Components: Input/Output
Environment: Centos 6.6
Reporter: Hyukjin Kwon
Priority: Minor
When data sources (such as Parquet) tries to filter data when reading from HDFS
(not in memory), Physical planing phase passes the filter objects in
`org.apache.spark.sql.sources`, which are appropriately built and picked up by
`selectFilters()` in `org.apache.spark.sql.sources.DataSourceStrategy`.
On the other hand, it does not pass `EqualNullSafe` filter in
`org.apache.spark.sql.catalyst.expressions` even though this seems possible to
pass for other datasources such as Parquet and JSON. In more detail, it does
not pass to (below) `buildScan` in `PrunedFilteredScan` and `PrunedScan`,
```
def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row]
```
even though the binary capability issue is
solved.(https://issues.apache.org/jira/browse/SPARK-8747).
I understand that `CatalystScan` can take the all raw expressions accessing to
the query planner. However, it is experimental and also it needs different
interfaces (as well as unstable for the reasons such as binary capability).
In general, the problem below can happen.
1.
```
SELECT *
FROM table
WHERE field = 1;
```
2.
```
SELECT *
FROM table
WHERE field <=> 1;
```
The second query can be hugely slow although the functionally is almost
identical because of the possible large network traffic (etc.) by not filtered
data from the source RDD.
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