[jira] [Updated] (SPARK-10978) Allow PrunedFilterScan to eliminate predicates from further evaluation
[
https://issues.apache.org/jira/browse/SPARK-10978?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yin Huai updated SPARK-10978:
-
Priority: Critical (was: Minor)
> 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: 1.3.0, 1.4.0, 1.5.0
>Reporter: Russell Alexander Spitzer
>Priority: Critical
>
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-10978) Allow PrunedFilterScan to eliminate predicates from further evaluation
[
https://issues.apache.org/jira/browse/SPARK-10978?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Michael Armbrust updated SPARK-10978:
-
Target Version/s: 1.6.0
> 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: 1.3.0, 1.4.0, 1.5.0
>Reporter: Russell Alexander Spitzer
>Priority: Minor
>
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-10978) Allow PrunedFilterScan to eliminate predicates from further evaluation
[
https://issues.apache.org/jira/browse/SPARK-10978?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen updated SPARK-10978:
--
Priority: Minor (was: Major)
([~rspitzer] don't set Fix Version)
> 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: 1.3.0, 1.4.0, 1.5.0
>Reporter: Russell Alexander Spitzer
>Priority: Minor
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
