* move benchmark data generator into druid-processing, add a GeneratorInputSource to fill up a cluster with data
* newlines
* make test coverage not fail maybe
* remove useless test
* Update pom.xml
* Update GeneratorInputSourceTest.java
* less passive aggressive test names
* Empty partitionDimension has less rollup compared to the case when it is explicitly specified
* Adding a unit test for the empty partitionDimension scenario. Fixing another test which was failing
* Fixing CI Build Inspection Issue
* Addressing all review comments
* Updating the javadocs for the hash method in HashBasedNumberedShardSpec
* fix groupBy with literal in subquery grouping
* fix groupBy with literal in subquery grouping
* fix groupBy with literal in subquery grouping
* address comments
* update javadocs
* Fix join
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* add tests
* address comments
* fix failing tests
* Add REGEXP_LIKE, fix empty-pattern bug in REGEXP_EXTRACT.
- Add REGEXP_LIKE function that returns a boolean, and is useful in
WHERE clauses.
- Fix REGEXP_EXTRACT return type (should be nullable; causes incorrect
filter elision).
- Fix REGEXP_EXTRACT behavior for empty patterns: should always match
(previously, they threw errors).
- Improve error behavior when REGEXP_EXTRACT and REGEXP_LIKE are passed
non-literal patterns.
- Improve documentation of REGEXP_EXTRACT.
* Changes based on PR review.
* Fix arg check.
* Important fixes!
* Add speller.
* wip
* Additional tests.
* Fix up tests.
* Add validation error tests.
* Additional tests.
* Remove useless call.
This change removes ListenableFutures.transformAsync in favor of the
existing Guava Futures.transform implementation. Our own implementation
had a bug which did not fail the future if the applied function threw an
exception, resulting in the future never completing.
An attempt was made to fix this bug, however when running againts Guava's own
tests, our version failed another half dozen tests, so it was decided to not
continue down that path and scrap our own implementation.
Explanation for how was this bug manifested itself:
An exception thrown in BaseAppenderatorDriver.publishInBackground when
invoked via transformAsync in StreamAppenderatorDriver.publish will
cause the resulting future to never complete.
This explains why when encountering https://github.com/apache/druid/issues/9845
the task will never complete, forever waiting for the publishFuture to
register the handoff. As a result, the corresponding "Error while
publishing segments ..." message only gets logged once the index task
times out and is forcefully shutdown when the future is force-cancelled
by the executor.
* - GroupByQueryEngineV2: Fix leak of intermediate processing buffer when
exceptions are thrown before result sequence is created.
- PooledTopNAlgorithm: Fix leak of intermediate processing buffer when
exceptions are thrown before the PooledTopNParams object is created.
- BlockingPool: Remove unused "take" methods.
* Add tests to verify that buffers have been returned.
* Fix various Yielder leaks.
- CombiningSequence leaked the input yielder from "toYielder" if it ran
into an exception while accumulating the last value from the input
yielder.
- MergeSequence leaked input yielders from "toYielder" if it ran into
an exception while building the initial priority queue.
- ScanQueryRunnerFactory leaked the input yielder in its
"priorityQueueSortAndLimit" strategy if it ran into an exception
while scanning and sorting.
- YieldingSequenceBase.accumulate chomped IOExceptions thrown in
"accumulate" during yielder closing.
* Add tests.
* Fix braces.
Since there is not currently a good way to have fine-grain code coverage
check exclusions, lower the coverage thresholds to make the check more
lenient for now. Also, display the code coverage report in the Travis CI
logs to make it easier to understand how to improve coverage.
during segment publishing we do streaming operations on a collection not
safe for concurrent modification. To guarantee correct results we must
also guard any operations on the stream itself.
This may explain the issue seen in https://github.com/apache/druid/issues/9845
* Refactor JoinFilterAnalyzer
This patch attempts to make it easier to follow the join filter analysis code
with the hope of making it easier to add rewrite optimizations in the future.
To keep the patch small and easy to review, this is the first of at least 2
patches that are planned.
This patch adds a builder to the Pre-Analysis, so that it is easier to
instantiate the preAnalysis. It also moves some of the filter normalization
code out to Fitlers with associated tests.
* fix tests
* Refactor JoinFilterAnalyzer - part 2
This change introduces the following components:
* RhsRewriteCandidates - a wrapper for a list of candidates and associated
functions to operate on the set of candidates.
* JoinableClauses - a wrapper for the list of JoinableClause that represent
a join condition and the associated functions to operate on the clauses.
* Equiconditions - a wrapper representing the equiconditions that are used
in the join condition.
And associated test changes.
This refactoring surfaced 2 bugs:
- Missing equals and hashcode implementation for RhsRewriteCandidate, thus
allowing potential duplicates in the rhs rewrite candidates
- Missing Filter#supportsRequiredColumnRewrite check in
analyzeJoinFilterClause, which could result in UnsupportedOperationException
being thrown by the filter
* fix compile error
* remove unused class
* Refactor JoinFilterAnalyzer - Correlations
Move the correlation related code out into it's own class so it's easier
to maintain.
Another patch should follow this one so that the query path uses the
correlation object instead of it's underlying maps.
* Optimize join queries where filter matches nothing
Fixes#9787
This PR changes the Joinable interface to return an Optional set of correlated
values for a column.
This allows the JoinFilterAnalyzer to differentiate between the case where the
column has no matching values and when the column could not find matching
values.
This PR chose not to distinguish between cases where correlated values could
not be computed because of a config that has this behavior disabled or because
of user error - like a column that could not be found. The reasoning was that
the latter is likely an error and the non filter pushdown path will surface the
error if it is.
* Refactor JoinFilterAnalyzer
This patch attempts to make it easier to follow the join filter analysis code
with the hope of making it easier to add rewrite optimizations in the future.
To keep the patch small and easy to review, this is the first of at least 2
patches that are planned.
This patch adds a builder to the Pre-Analysis, so that it is easier to
instantiate the preAnalysis. It also moves some of the filter normalization
code out to Fitlers with associated tests.
* fix tests
* Refactor JoinFilterAnalyzer - part 2
This change introduces the following components:
* RhsRewriteCandidates - a wrapper for a list of candidates and associated
functions to operate on the set of candidates.
* JoinableClauses - a wrapper for the list of JoinableClause that represent
a join condition and the associated functions to operate on the clauses.
* Equiconditions - a wrapper representing the equiconditions that are used
in the join condition.
And associated test changes.
This refactoring surfaced 2 bugs:
- Missing equals and hashcode implementation for RhsRewriteCandidate, thus
allowing potential duplicates in the rhs rewrite candidates
- Missing Filter#supportsRequiredColumnRewrite check in
analyzeJoinFilterClause, which could result in UnsupportedOperationException
being thrown by the filter
* fix compile error
* remove unused class
* Update tutorial-query.md
* First full pass complete
* Smoothing over, a bit
* link and spell checking
* Update querying.md
* Review comments; screenshot fixes
* Making ports consistent, pending confirmation
Switching to the Router port, to make this be consistent with the tutorial ports, but can switch back here and there if it should be 8082 instead.
* Resizing screenshot
* Update querying.md
* Review feedback incorporated.
* Refactor JoinFilterAnalyzer
This patch attempts to make it easier to follow the join filter analysis code
with the hope of making it easier to add rewrite optimizations in the future.
To keep the patch small and easy to review, this is the first of at least 2
patches that are planned.
This patch adds a builder to the Pre-Analysis, so that it is easier to
instantiate the preAnalysis. It also moves some of the filter normalization
code out to Fitlers with associated tests.
* fix tests
* Add ingestion specs for CalciteQueryTests
This PR introduces ingestion specs that can be used for local testing
so that CalciteQueryTests can be built on a druid cluster.
* Add README
* Update sql/src/test/resources/calcite/tests/README.md
Motivation for this change is to not inadvertently identify binary
formats that contain uncompressed string data as TSV or CSV.
Moving detection of magic byte headers before heuristics should be more
robust in general.
* Enforce code coverage
Add an automated way of checking if new code has adequate unit tests,
since merging code coverage reports and check coverage thresholds via
coveralls or codecov is unreliable.
The following minimum unit test code coverage is now enforced:
- 80% functions
- 65% branch
- 65% line
Branch and line coverage thresholds are slightly lower for now as they
are harder to achieve.
After the code coverage check looks reliable, the thresholds can be
increased later if needed.
* Add comments
* Number based columns representing time in custom format cannot be used as timestamp column in Druid.
Prior to this fix, if an integer column in parquet is storing dateint in format yyyyMMdd, it cannot be used as timestamp column in Druid as the timestamp parser interprets it as a number storing UTC time instead of treating it as a number representing time in yyyyMMdd format. Data formats like TSV or CSV don't suffer from this problem as the timestamp is passed in an as string which the timestamp parser is able to parse correctly.
* refactor SeekableStreamSupervisor usage of RecordSupplier to reduce contention between background threads and main thread, refactor KinesisRecordSupplier, refactor Kinesis lag metric collection and emitting
* fix style and test
* cleanup, refactor, javadocs, test
* fixes
* keep collecting current offsets and lag if unhealthy in background reporting thread
* review stuffs
* add comment
* Add AvroOCFInputFormat
* Support supplying a reader schema in AvroOCFInputFormat
* Add docs for Avro OCF input format
* Address review comments
* Address second round of review