Hi Albert, Apache Flink leverages Apache Calcite to optimize and translate queries. The optimization currently performed include projection and filter push-down, subquery decorrelation, and other kinds of query rewriting. Flink does not yet optimize the order of joins[1]. I agree with you it is valuable to make flink support changing the order of aggregation operators.
Btw, the main code can be found here[2], in the "def optimize(relNode: RelNode, updatesAsRetraction: Boolean)" function. Best, Hequn [1] https://ci.apache.org/projects/flink/flink-docs-master/dev/table/common.html#query-optimization [2] https://github.com/apache/flink/blob/master/flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/StreamTableEnvironment.scala On Sun, Jul 15, 2018 at 3:14 AM, Albert Jonathan <alb...@cs.umn.edu> wrote: > Hello, > > I am just wondering, does Flink use Apache Calcite's query optimizer to > generate an optimal logical plan for stream queries, or does it have its > own independent query optimizer? > From what I observed so far, the Flink's query optimizer only groups > operator together without changing the order of aggregation operators > (e.g., join). Did I miss anything? > > I am thinking of extending Flink to apply query optimization as in the > context of DBMS by either integrating it with Calcite or implementing it as > a new module. > Any feedback or guidelines will be highly appreciated. > > Thank you, > Albert > >
