This simplifies DruidSemiJoin, which no longer needs to add aggregation back
in. It also allows some more kinds of queries to plan properly, like the one
added in "testTopNFilterJoin".
* SQL: Ditch CalciteConnection layer and add DruidMeta, extension aggregators.
Switched from CalciteConnection to Planner, bringing benefits:
- CalciteConnection's JDBC interface no longer sits between the SQL server
(HTTP/Avatica) and Druid's query layer. Instead, the SQL servers can use
Druid Sequence objects directly, reducing overhead in the query return path.
- Implemented our own Planner-based Avatica Meta, letting us control
connection timeouts and connection / statement limits. The previous
CalciteConnection-based implementation didn't have any limits or timeouts.
- The Planner interface lets us override the operator table, opening up
SQL language extensions. This patch includes two: APPROX_COUNT_DISTINCT
in core, and a QUANTILE aggregator in the druid-histogram extension.
Also:
- Added INFORMATION_SCHEMA metadata schema.
- Added tests for Unicode literals and escapes.
* Verify statement is actually open before closing it.
* More detailed INFORMATION_SCHEMA docs.
* SQL support for nested groupBys.
Allows, for example, doing exact count distinct by writing:
SELECT COUNT(*) FROM (SELECT DISTINCT col FROM druid.foo)
Contrast with approximate count distinct, which is:
SELECT COUNT(DISTINCT col) FROM druid.foo
* Add deeply-nested groupBy docs, tests, and maxQueryCount config.
* Extract magic constants into statics.
* Rework rules to put preconditions in the "matches" method.
Gian Merlino
Roman Leventov