Russell Alexander Spitzer created SPARK-10978:
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Summary: Allow PrunedFilterScan to eliminate predicates from
further evaluation
Key: SPARK-10978
URL: https://issues.apache.org/jira/browse/SPARK-10978
Project: Spark
Issue Type: New Feature
Components: SQL
Affects Versions: 1.5.0, 1.4.0, 1.3.0
Reporter: Russell Alexander Spitzer
Fix For: 1.6.0
Currently PrunedFilterScan allows implementors to push down predicates to an
underlying datasource. This is done solely as an optimization as the predicate
will be reapplied on the Spark side as well. This allows for bloom-filter like
operations but ends up doing a redundant scan for those sources which can do
accurate pushdowns.
In addition it makes it difficult for underlying sources to accept queries
which reference non-existent to provide ancillary function. In our case we
allow a solr query to be passed in via a non-existent solr_query column. Since
this column is not returned when Spark does a filter on "solr_query" nothing
passes.
Suggestion on the ML from [~marmbrus]
{quote}
We have to try and maintain binary compatibility here, so probably the easiest
thing to do here would be to add a method to the class. Perhaps something like:
def unhandledFilters(filters: Array[Filter]): Array[Filter] = filters
By default, this could return all filters so behavior would remain the same,
but specific implementations could override it. There is still a chance that
this would conflict with existing methods, but hopefully that would not be a
problem in practice.
{quote}
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