[jira] [Resolved] (SPARK-9814) EqualNotNull not passing to data sources

["Reynold Xin (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-9814?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Reynold Xin resolved SPARK-9814.
--------------------------------
       Resolution: Fixed
         Assignee: Hyukjin Kwon
    Fix Version/s: 1.5.0

> EqualNotNull not passing to data sources
> ----------------------------------------
>
>                 Key: SPARK-9814
>                 URL: https://issues.apache.org/jira/browse/SPARK-9814
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>            Reporter: Hyukjin Kwon
>            Assignee: Hyukjin Kwon
>            Priority: Minor
>             Fix For: 1.5.0
>
>
> 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 {{EqualNullSafe}} to (below) {{buildScan()}} in {{PrunedFilteredScan}} and {{PrunedScan}}, 
> {code}
> def buildScan(requiredColumns: Array[String], filters: Array[Filter]): RDD[Row]
> {code}
> 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.
> {code:sql}
> SELECT * FROM table WHERE field = 1;
> {code}
>  
> 2. 
> {code:sql}
> SELECT * FROM table WHERE field <=> 1;
> {code}
> 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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