Fabian Hueske created FLINK-5226:
------------------------------------
Summary: Eagerly project unused attributes
Key: FLINK-5226
URL: https://issues.apache.org/jira/browse/FLINK-5226
Project: Flink
Issue Type: Improvement
Components: Table API & SQL
Affects Versions: 1.2.0
Reporter: Fabian Hueske
The optimizer does currently not eagerly remove unused attributes.
For example given a table {{tab5}} with five attributes {{a, b, c, d, e}}, the
following query
{code}
SELECT x.a, y.b FROM tab5 AS x, tab5 AS y WHERE x.a = y.a
{code}
would result in the non-optimized plan
{code}
LogicalProject(a=[$0], b=[$6])
LogicalFilter(condition=[=($0, $5)])
LogicalJoin(condition=[true], joinType=[inner])
LogicalTableScan(table=[[tab5]])
LogicalTableScan(table=[[tab5]])
{code}
and the optimized plan:
{code}
DataSetCalc(select=[a, b0 AS b])
DataSetJoin(where=[=(a, a0)], join=[a, b, c, d, e, a0, b0, c0, d0, e0],
joinType=[InnerJoin])
DataSetScan(table=[[_DataSetTable_0]])
DataSetScan(table=[[_DataSetTable_0]])
{code}
This plan is inefficient because it joins all ten attributes of both tables
instead of eagerly projecting out all unused fields ({{x.b, x.c, x.d, x.e, y.c,
y.d, y.e}}).
Since this is one of the most common optimizations, I would assume that Calcite
provides some rules to extract eager projections. If this is the case, the
issue can be solved by adding such rules to {{FlinkRuleSets}}.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
