* SQL + Expressions = Best friends forever.
- Use expressions as a projection layer for anything that can't be
expressed using traditional Druid extractionFns. Sometimes they're
embedded directly (like "expression" filters, builtin aggregators,
or "expression" post-aggregators). Sometimes they're referenced
through virtual columns (like dimensionSpecs, which can't innately
reference functions of more than one column without the virtual
column layer).
- Add many new functions and operators, taking advantage of the
expression capability (see the querying/sql.md doc).
- Improve consistency of constant reduction and of casting by
using Druid expressions for this instead of Calcite's RexExecutor.
* Fix casting bug, and other code review comments.
* Fix docs.
This puts all the SQL stuff in one place. It also makes life easier by
pointing out that configs be made in either common.runtime.properties
or the broker runtime.properties.
* SQL: Resolve column type conflicts in favor of newer segments.
Helps with schema evolution from e.g. long -> float, which is supported
on the query side.
* Take columns from highest timestamp instead of max segment id.
* Fixes and docs.
* SQL: Add context and contextual functions to planner.
Added support for context parameters specified as JDBC connection properties
or a JSON object for SQL-over-JSON-over-HTTP.
Also added features that depend on context functionality:
- Added CURRENT_DATE, CURRENT_TIME, CURRENT_TIMESTAMP functions.
- Added support for time zones other than UTC via a "timeZone" context.
- Pass down query context to Druid queries too.
Also some bug fixes:
- Fix DATE handling, it was largely done incorrectly before.
- Fix CAST(__time TO DATE) which should do a floor-to-day.
- Fix non-equality comparisons to FLOOR(__time TO X).
- Fix maxQueryCount property.
* Pass down context to nested queries too.
* SQL: Add resolution parameter to quantile agg, rename to APPROX_QUANTILE.
* Fix bug with re-use of filtered approximate histogram aggregators.
Also add APPROX_QUANTILE tests for filtering and running on complex columns.
Includes some slight refactoring to allow tests to make DruidTables that
include complex columns.
* Remove unused import
* 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
Jonathan Wei
Gian Merlino
Jihoon Son
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