[SPARK-13219] Pushdown predicate propagation in SparkSQL with join

• Type: Improvement
• Status: Resolved
• Priority: Major
• Resolution: Duplicate
• Affects Version/s: 1.4.1, 1.5.2, 1.6.0
• Component/s: SQL

Environment

Spark 1.4
Datastax Spark connector 1.4
Cassandra. 2.1.12
Centos 6.6

• Assignee: Unassigned
• Reporter: Abhinav Chawade
• Created: 05/Feb/16 23:07
• Updated: 27/Feb/17 04:56
• Resolved: 14/Feb/17 03:35

Description

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.

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)

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.

Issue Links

• is duplicated by: SPARK-12532 Join-key Pushdown via Predicate Transitivity