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[1] https://issues.apache.org/jira/browse/IGNITE-4509

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Theory

This technique is used excessively by both distributed databases and classical RDBMS vendors (as a part of their partitioning/sharding solutions). First, query is analyzed and optionally re-written to allow for better partition pruning. Second, information of interesting partitions are extracted from query for every table (cache) and subquery (for complex multi-stage distributed queries). 

Query Rewrite

WHERE conditions and JOIN-s are relatively simple targets for extract partition extraction. The main difficulty is subqueries, as they potentially introduce unlimited nesting what complicates analysis a lot. So the main goal of query rewrite is to minimize number of subqueries. Main techniques are JOIN conversion, correlation and materialization. Interestingly, all these techniques not only simplify partition extraction, but also allow optimizer to choose better execution plan for local execution, as JOINs are much easier to be analyzed and reordered than subqueries. As we shall see below, efforts are usually focused on non-correlated subqueries as they are the most costly for straightforward execution.

JOIN conversion

TODO

Correlation

TODO

Materialization

TODO

Partition Extraction

TOODPartition extraction

Proposed Changes

TODO

Tickets

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