* Fix VARIANCE aggregator comparator
The comparator for the variance aggregator used to compare values using the
count. This is now fixed to compare values using the variance. If the variance
is equal, the count and sum are used as tie breakers.
* fix tests + sql compatible mode
* code review
* more tests
* fix last test
* optimize announceHistoricalSegment
* optimize announceHistoricalSegment
* revert offline SegmentTransactionalInsertAction uses a separate lock
* optimize segmentExistsBatch: Avoid too many elements in the in condition
* add unit test && Modified according to cr
Co-authored-by: xiangqiao <xiangqiao@kuaishou.com>
Per suggestion in comment https://github.com/apache/druid/pull/9262#issuecomment-675732237, I think this should eventually result in the copy mirrored on dockerhub to also be updated, if I understand how things work. Only the github `README.md` has been updated, not the `README.template` used for src and bin packages because presumably if you are reading from either of those you are just going to run locally and so the local quickstart is appropriate.
* SQL support for union datasources.
Exposed via the "UNION ALL" operator. This means that there are now two
different implementations of UNION ALL: one at the top level of a query
that works by concatenating subquery results, and one at the table level
that works by creating a UnionDataSource.
The SQL documentation is updated to discuss these two use cases and how
they behave.
Future work could unify these by building support for a native datasource
that represents the union of multiple subqueries. (Today, UnionDataSource
can only represent the union of tables, not subqueries.)
* Fixes.
* Error message for sanity check.
* Additional test fixes.
* Add some error messages.
* Move tools for indexing to TaskToolbox instead of injecting them in constructor
* oops, other changes
* fix test
* unnecessary new file
* fix test
* fix build
* Fix handling of 'join' on top of 'union' datasources.
The problem is that unions are typically rewritten into a series of
individual queries on the underlying tables, but this isn't done when
the union is wrapped in a join.
The main changes are in UnionQueryRunner:
1) Replace an instanceof UnionQueryRunner check with DataSourceAnalysis.
2) Replace a "query.withDataSource" call with a new function, "Queries.withBaseDataSource".
Together, these enable UnionQueryRunner to "see through" a join.
* Tests.
* Adjust heap sizes for integration tests.
* Different approach, more tests.
* Tweak.
* Styling.
* Add support for all partitioing schemes for auto compaction
* annotate last compaction state for multi phase parallel indexing
* fix build and tests
* test
* better home
* better type tracking: add typed postaggs, finalized types for agg factories
* more javadoc
* adjustments
* transition to getTypeName to be used exclusively for complex types
* remove unused fn
* adjust
* more better
* rename getTypeName to getComplexTypeName
* setup expression post agg for type inference existing
* more javadocs
* fixup
* oops
* more test
* more test
* more comments/javadoc
* nulls
* explicitly handle only numeric and complex aggregators for incremental index
* checkstyle
* more tests
* adjust
* more tests to showcase difference in behavior
* timeseries longsum array
* Make NUMERIC_HASHING_THRESHOLD configurable
Change the default numeric hashing threshold to 1 and make it configurable.
Benchmarks attached to this PR show that binary searches are not more faster
than doing a set contains check. The attached flamegraph shows the amount of
time a query spent in the binary search. Given the benchmarks, we can expect
to see roughly a 2x speed up in this part of the query which works out to
~ a 10% faster query in this instance.
* Remove NUMERIC_HASHING_THRESHOLD
* Remove stale docs
Previously, this was disallowed, because expressions treated multi-values
as nulls. But now, if there's a single multi-value column that can be
mapped over, it's okay to use the index. Expression selectors already do
this.
* Optimize large InDimFilters
For large InDimFilters, in default mode, the filter does a linear check of the
set to see if it contains either an empty or null. If it does, the empties are
converted to nulls by passing through the entire list again.
Instead of this, in default mode, we attempt to remove an empty string from the
values that are passed to the InDimFilter. If an empty string was removed, we
add null to the set
* code review
* Revert "code review"
This reverts commit 61fe33ebf7.
* code review - less brittle
* support redis cluster
* add 'password', 'database' properties
* test cases passed
* update doc
* some improvements
* fix CI
* add more test cases to improve branch coverage
* fix dependency check for test
* resolve review comments
* Add SQL "OFFSET" clause.
Under the hood, this uses the new offset features from #10233 (Scan)
and #10235 (GroupBy). Since Timeseries and TopN queries do not currently
have an offset feature, SQL planning will switch from one of those to
Scan or GroupBy if users add an OFFSET.
Includes a refactoring to harmonize offset and limit planning using an
OffsetLimit wrapper class. This is useful because it ensures that the
various places that need to deal with offset and limit collapsing all
behave the same way, using its "andThen" method.
* Fix test and add another test.
* Segment backed broadcast join IndexedTable
* fix comments
* fix tests
* sharing is caring
* fix test
* i hope this doesnt fix it
* filter by schema to maybe fix test
* changes
* close join stuffs so it does not leak, allow table to directly make selector factory
* oops
* update comment
* review stuffs
* better check
* Add note about aggreations on floats
Floating point math is known to be unstable. Due to the way aggregators work
across segments it's possible for the same query operating on the same data to
produce slightly different results.
The same problem exists with any aggregators that are not commutative since
the merge order across segments is not guaranteed.
* Also talk about doubles
* Apply suggestions from code review
* remove DruidLeaderClient.goAsync(..) that does not follow redirect.
Replace its usage by DruidLeaadereClient.go(..) with
InputStreamFullResponseHandler
* remove ByteArrayResponseHolder dependency from JsonParserIterator
* add UT to cover lines in InputStreamFullResponseHandler
* refactor SystemSchema to reduce branches
* further reduce branches
* Revert "add UT to cover lines in InputStreamFullResponseHandler"
This reverts commit 330aba3dd9.
* UTs for InputStreamFullResponseHandler
* remove unused imports
* Add "offset" parameter to the Scan query.
It works by doing the query as normal and then throwing away the first
"offset" number of rows on the broker.
* Fix constructor call.
* Fix up JSONs.
* Fix call to ScanQuery.
* Doc update.
* Fix javadocs.
* Spotbugs, LGTM suppressions.
* Javadocs.
* Fix suppression.
* Stabilize Scan query result order, add tests.
* Update LGTM comment.
* Fixup.
* Test different batch sizes too.
* Nicer tests.
* Fix comment.
1) lookupId could return IDs beyond maxId if called with a recently added value.
2) getRow could return an ID for null beyond maxId, if null was recently
encountered in a dimension that initially didn't appear at all. (In this case,
the dictionary ID for null can be > 0).
Also add a comment explaining how this stuff is supposed to work.
* Fix broken sampler for re-indexer
When re-indexing a Druid datasource, the web-console would generate an
invalid inputFormat since the type is not specified.
* code review
* fix bug with realtime expressions on sparse string columns
* fix test
* add comment back
* push capabilities for dimensions to dimension indexers since they know things
* style
* style
* fixes
* getting a bit carried away
* missed one
* fix it
* benchmark build fix
* review stuffs
* javadoc and comments
* add comment
* more strict check
* fix missed usaged of impl instead of interface
* LongMaxVectorAggregator support and test case.
* DoubleMinVectorAggregator and test cases.
* DoubleMaxVectorAggregator and unit test.
* FloatMinVectorAggregator and FloatMaxVectorAggregator.
* Documentation update to include the other vector aggregators.
* Bug fix.
* checkstyle formatting fixes.
* CalciteQueryTest cases update.
* Separate test classes for FloatMaxAggregation and FloatMniAggregation.
* remove the cannotVectorize for float max/min aggregator in test.
* Tests in GroupByQueryRunner, GroupByTimeseriesQueryRunner and TimeseriesQueryRunner.
* Combine InDimFilter, InFilter.
There are two motivations:
1. Ensure that when HashJoinSegmentStorageAdapter compares its Filter
to the original one, and it is an "in" type, the comparison is by
reference and does not need to check deep equality. This is useful
when the "in" filter is very large.
2. Simplify things. (There isn't a great reason for the DimFilter and
Filter logic to be separate, and combining them reduces some
duplication.)
* Fix test.
* Add "offset" parameter to GroupBy query.
It works by doing the query as normal and then throwing away the first
"offset" number of rows on the broker.
* Stabilize GroupBy sorts.
* Fix inspections.
* Fix suppression.
* Fixups.
* Move TopNSequence to druid-core.
* Addl comments.
* NumberedElement equals verification.
* Changes from review.
* Fix minor formatting in docs.
* Add Nullhandling initialization for test to run from IDE.
* Vectorize longMin aggregator.
- A new vectorized class for the vectorized long min aggregator.
- Changes to AggregatorFactory to support vectorize functionality.
- Few changes to schema evolution test to add LongMinAggregatorFactory.
* Add longSum to the supported vectorized aggregator implementations.
* Add MIN() long min to calcite query test that can vectorize.
* Add simple long aggregations test.
* Fixup formatting per checkstyle guide.
* fixup and add more tests for long min aggregator.
* Override test for groupBy since timestamps are handled differently.
* Null compatibility check in test.
* Review comment: Add a test case to LongMinAggregationTest.