[jira] [Comment Edited] (SPARK-13219) Pushdown predicate propagation in SparkSQL with join
[
https://issues.apache.org/jira/browse/SPARK-13219?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15138289#comment-15138289
]
Xiao Li edited comment on SPARK-13219 at 2/9/16 3:50 AM:
-
Could you wait for me to fix another issue? When I tried your query, I found a
bug of attribute resolution in the latest build. I need to fix it now. Thanks!
was (Author: smilegator):
Could you wait for me to fix another issue? When I tried your query, I found a
bug in the latest build. I need to fix it now. Thanks!
> Pushdown predicate propagation in SparkSQL with join
>
>
> Key: SPARK-13219
> URL: https://issues.apache.org/jira/browse/SPARK-13219
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 1.4.1, 1.6.0
> Environment: Spark 1.4
> Datastax Spark connector 1.4
> Cassandra. 2.1.12
> Centos 6.6
>Reporter: Abhinav Chawade
>
> When 2 or more tables are joined in SparkSQL and there is an equality clause
> in query on attributes used to perform the join, it is useful to apply that
> clause on scans for both table. If this is not done, one of the tables
> results in full scan which can reduce the query dramatically. Consider
> following example with 2 tables being joined.
> {code}
> CREATE TABLE assets (
> assetid int PRIMARY KEY,
> address text,
> propertyname text
> )
> CREATE TABLE tenants (
> assetid int PRIMARY KEY,
> name text
> )
> spark-sql> explain select t.name from tenants t, assets a where a.assetid =
> t.assetid and t.assetid='1201';
> WARN 2016-02-05 23:05:19 org.apache.hadoop.util.NativeCodeLoader: Unable to
> load native-hadoop library for your platform... using builtin-java classes
> where applicable
> == Physical Plan ==
> Project [name#14]
> ShuffledHashJoin [assetid#13], [assetid#15], BuildRight
> Exchange (HashPartitioning 200)
>Filter (CAST(assetid#13, DoubleType) = 1201.0)
> HiveTableScan [assetid#13,name#14], (MetastoreRelation element, tenants,
> Some(t)), None
> Exchange (HashPartitioning 200)
>HiveTableScan [assetid#15], (MetastoreRelation element, assets, Some(a)),
> None
> Time taken: 1.354 seconds, Fetched 8 row(s)
> {code}
> The simple workaround is to add another equality condition for each table but
> it becomes cumbersome. It will be helpful if the query planner could improve
> filter propagation.
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[jira] [Comment Edited] (SPARK-13219) Pushdown predicate propagation in SparkSQL with join
[
https://issues.apache.org/jira/browse/SPARK-13219?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15138297#comment-15138297
]
Xiao Li edited comment on SPARK-13219 at 2/9/16 3:57 AM:
-
It should work without Join clauses, as long as these predicates are pushed
into the join/filter conditions.
However, the current PR is unable to infer the conditions when needing multiple
hops. Actually, I am glad to work on it, if needed.
Let me at [~rxin] [~marmbrus].
was (Author: smilegator):
It should work without Join clauses, as long as these predicates are pushed
into the join conditions. If they are only in filters, this is not applicable
and we should not pushed down the inferred conditions.
However, the current PR is unable to infer the conditions when needing multiple
hops. Actually, I am glad to work on it, if needed.
Let me at [~rxin] [~marmbrus].
> Pushdown predicate propagation in SparkSQL with join
>
>
> Key: SPARK-13219
> URL: https://issues.apache.org/jira/browse/SPARK-13219
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 1.4.1, 1.6.0
> Environment: Spark 1.4
> Datastax Spark connector 1.4
> Cassandra. 2.1.12
> Centos 6.6
>Reporter: Abhinav Chawade
>
> When 2 or more tables are joined in SparkSQL and there is an equality clause
> in query on attributes used to perform the join, it is useful to apply that
> clause on scans for both table. If this is not done, one of the tables
> results in full scan which can reduce the query dramatically. Consider
> following example with 2 tables being joined.
> {code}
> CREATE TABLE assets (
> assetid int PRIMARY KEY,
> address text,
> propertyname text
> )
> CREATE TABLE tenants (
> assetid int PRIMARY KEY,
> name text
> )
> spark-sql> explain select t.name from tenants t, assets a where a.assetid =
> t.assetid and t.assetid='1201';
> WARN 2016-02-05 23:05:19 org.apache.hadoop.util.NativeCodeLoader: Unable to
> load native-hadoop library for your platform... using builtin-java classes
> where applicable
> == Physical Plan ==
> Project [name#14]
> ShuffledHashJoin [assetid#13], [assetid#15], BuildRight
> Exchange (HashPartitioning 200)
>Filter (CAST(assetid#13, DoubleType) = 1201.0)
> HiveTableScan [assetid#13,name#14], (MetastoreRelation element, tenants,
> Some(t)), None
> Exchange (HashPartitioning 200)
>HiveTableScan [assetid#15], (MetastoreRelation element, assets, Some(a)),
> None
> Time taken: 1.354 seconds, Fetched 8 row(s)
> {code}
> The simple workaround is to add another equality condition for each table but
> it becomes cumbersome. It will be helpful if the query planner could improve
> filter propagation.
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[jira] [Comment Edited] (SPARK-13219) Pushdown predicate propagation in SparkSQL with join
[
https://issues.apache.org/jira/browse/SPARK-13219?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15138289#comment-15138289
]
Xiao Li edited comment on SPARK-13219 at 2/9/16 3:42 AM:
-
Could you wait for me to fix another issue? When I tried your query, I found a
bug in the latest build. I need to fix it now. Thanks!
was (Author: smilegator):
Could you wait for me to fix another issue? When I tried your query, I found a
bug. I need to fix it now. Thanks!
> Pushdown predicate propagation in SparkSQL with join
>
>
> Key: SPARK-13219
> URL: https://issues.apache.org/jira/browse/SPARK-13219
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 1.4.1, 1.6.0
> Environment: Spark 1.4
> Datastax Spark connector 1.4
> Cassandra. 2.1.12
> Centos 6.6
>Reporter: Abhinav Chawade
>
> When 2 or more tables are joined in SparkSQL and there is an equality clause
> in query on attributes used to perform the join, it is useful to apply that
> clause on scans for both table. If this is not done, one of the tables
> results in full scan which can reduce the query dramatically. Consider
> following example with 2 tables being joined.
> {code}
> CREATE TABLE assets (
> assetid int PRIMARY KEY,
> address text,
> propertyname text
> )
> CREATE TABLE tenants (
> assetid int PRIMARY KEY,
> name text
> )
> spark-sql> explain select t.name from tenants t, assets a where a.assetid =
> t.assetid and t.assetid='1201';
> WARN 2016-02-05 23:05:19 org.apache.hadoop.util.NativeCodeLoader: Unable to
> load native-hadoop library for your platform... using builtin-java classes
> where applicable
> == Physical Plan ==
> Project [name#14]
> ShuffledHashJoin [assetid#13], [assetid#15], BuildRight
> Exchange (HashPartitioning 200)
>Filter (CAST(assetid#13, DoubleType) = 1201.0)
> HiveTableScan [assetid#13,name#14], (MetastoreRelation element, tenants,
> Some(t)), None
> Exchange (HashPartitioning 200)
>HiveTableScan [assetid#15], (MetastoreRelation element, assets, Some(a)),
> None
> Time taken: 1.354 seconds, Fetched 8 row(s)
> {code}
> The simple workaround is to add another equality condition for each table but
> it becomes cumbersome. It will be helpful if the query planner could improve
> filter propagation.
--
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[jira] [Comment Edited] (SPARK-13219) Pushdown predicate propagation in SparkSQL with join
[
https://issues.apache.org/jira/browse/SPARK-13219?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15138297#comment-15138297
]
Xiao Li edited comment on SPARK-13219 at 2/9/16 3:51 AM:
-
It should work without Join clauses, as long as these predicates are pushed
into the join conditions. If they are only in filters, this is not applicable
and we should not pushed down the inferred conditions.
However, the current PR is unable to infer the conditions when needing multiple
hops. Actually, I am glad to work on it, if needed.
Let me at [~rxin] [~marmbrus].
was (Author: smilegator):
It should works without Join clauses, as long as these predicates are pushed
into the join conditions. If they are only in filters, this is not applicable
and we should not pushed down the inferred conditions.
However, the current PR is unable to infer the conditions when needing multiple
hops. Actually, I am glad to work on it, if needed.
Let me at [~rxin] [~marmbrus].
> Pushdown predicate propagation in SparkSQL with join
>
>
> Key: SPARK-13219
> URL: https://issues.apache.org/jira/browse/SPARK-13219
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 1.4.1, 1.6.0
> Environment: Spark 1.4
> Datastax Spark connector 1.4
> Cassandra. 2.1.12
> Centos 6.6
>Reporter: Abhinav Chawade
>
> When 2 or more tables are joined in SparkSQL and there is an equality clause
> in query on attributes used to perform the join, it is useful to apply that
> clause on scans for both table. If this is not done, one of the tables
> results in full scan which can reduce the query dramatically. Consider
> following example with 2 tables being joined.
> {code}
> CREATE TABLE assets (
> assetid int PRIMARY KEY,
> address text,
> propertyname text
> )
> CREATE TABLE tenants (
> assetid int PRIMARY KEY,
> name text
> )
> spark-sql> explain select t.name from tenants t, assets a where a.assetid =
> t.assetid and t.assetid='1201';
> WARN 2016-02-05 23:05:19 org.apache.hadoop.util.NativeCodeLoader: Unable to
> load native-hadoop library for your platform... using builtin-java classes
> where applicable
> == Physical Plan ==
> Project [name#14]
> ShuffledHashJoin [assetid#13], [assetid#15], BuildRight
> Exchange (HashPartitioning 200)
>Filter (CAST(assetid#13, DoubleType) = 1201.0)
> HiveTableScan [assetid#13,name#14], (MetastoreRelation element, tenants,
> Some(t)), None
> Exchange (HashPartitioning 200)
>HiveTableScan [assetid#15], (MetastoreRelation element, assets, Some(a)),
> None
> Time taken: 1.354 seconds, Fetched 8 row(s)
> {code}
> The simple workaround is to add another equality condition for each table but
> it becomes cumbersome. It will be helpful if the query planner could improve
> filter propagation.
--
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