* Speed up joins on indexed tables with string keys
When joining on index tables with string keys, caching the computation
of row id to row numbers improves performance on the
JoinAndLookupBenchmark.joinIndexTableStringKey* benchmarks by about 10%
if the column cache is enabled an by about 100% if the column cache is
disabled.
* Faster cache impl and handle unknown cardinality
* Remove unused dependency
* Hoist cardinality check outside of hot loop
* Fix dummy DimensionSelector for tests
* implement shell for greatest sql aggregator with hardcoded long values
* implement functional long greatest aggregator for direct access columns
* implement greatest & least sql aggregators for long & double types using abstract base class
* add javadocs, unit tests & handling for floats for greatest/least postaggregations
* minor checkstyle fix
* improve naming for the test cases
* make inner class static
* remove blank lines to retest travis build
* change trivial text to rerun travis build
* implement suggested updates for greatest/least sql aggs & fix checkstyle issues
* fix stale comments in greatest/least sql aggs abstract base
* Update sql.md
* improve sql function definitions for greatest/least sql aggs
* add more tests for greatest/least sql aggs
* add tests to cover invalid greatest/least sql expressions
* rename & reorder greatest least sql tests
By default native batch ingestion was only getting a batch of 10
files at a time when used with google cloud. The Default for other
cloud providers is 1024, and should be similar for google cloud.
The low batch size was caused by mistype. This change updates the
batch size to 1024 when using google cloud.
* Guicify druid sql module
Break up the SQLModule in to smaller modules and provide a binding that
modules can use to register schemas with druid sql.
* fix some tests
* address code review
* tests compile
* Working tests
* Add all the tests
* fix up licenses and dependencies
* add calcite dependency to druid-benchmarks
* tests pass
* rename the schemas
* IMPLY-1946: Improve code quality and unit test coverage of the Azure extension
* Update unit tests to increase test coverage for the extension
* Clean up any messy code
* Enfore code coverage as part of tests.
* * Update azure extension pom to remove unnecessary things
* update jacoco thresholds
* * updgrade version of azure-storage library version uses to
most upto-date version
* * exclude common libraries that are included from druid core
* * address review comments
* SQL join support for lookups.
1) Add LookupSchema to SQL, so lookups show up in the catalog.
2) Add join-related rels and rules to SQL, allowing joins to be planned into
native Druid queries.
* Add two missing LookupSchema calls in tests.
* Fix tests.
* Fix typo.
This is important because if a user has the hdfs extension loaded, but is not
using hdfs deep storage, then they will not have storageDirectory set and will
get the following error:
IllegalArgumentException: Can not create a Path from an empty string
at io.druid.storage.hdfs.HdfsDataSegmentKiller.<init>(HdfsDataSegmentKiller.java:47)
This scenario is realistic: it comes up when someone has the hdfs extension
loaded because they want to use HdfsInputSource, but don't want to use hdfs for
deep storage.
Fixes#4694.
* Suppress netty 3 vulnerabilites and upgrade netty 4 version
* Upgrade netty 4 version to fix vulnerabilities CVE-2019-20445
and CVE-2019-20444
* suppress these CVEs for netty 3
* * simplify suppression xml file
* update licenses file with new version of netty
* * fix type in licenses.yaml
* Add LookupJoinableFactory.
Enables joins where the right-hand side is a lookup. Includes an
integration test.
Also, includes changes to LookupExtractorFactoryContainerProvider:
1) Add "getAllLookupNames", which will be needed to eventually connect
lookups to Druid's SQL catalog.
2) Convert "get" from nullable to Optional return.
3) Swap out most usages of LookupReferencesManager in favor of the
simpler LookupExtractorFactoryContainerProvider interface.
* Fixes for tests.
* Fix another test.
* Java 11 message fix.
* Fixups.
* Fixup benchmark class.
* Add getRightColumns to JoinConditionAnalysis
This change other implementations of JoinableFactory to ask the analysis
for the right key columns instead of having to calculate it themselves.
* Address some review comments
* more code review stuff
Add microbenchmark for joins. Enabling the column cache improves
performance by ~70% for the benchmarks for joins with string keys.
Adjusting LookupJoinMatcher.matchCondition() to have fewer branches,
improves performance by ~10% for the benchmarks for joins with lookups.
* intelliJ inspections cleanup
- remove redundant escapes
- performance warnings
- access static member via instance reference
- static method declared final
- inner class may be static
Most of these changes are aesthetic, however, they will allow inspections to
be enabled as part of CI checks going forward
The valuable changes in this delta are:
- using StringBuilder instead of string addition in a loop
indexing-hadoop/.../Utils.java
processing/.../ByteBufferMinMaxOffsetHeap.java
- Use class variables instead of static variables for parameterized test
processing/src/.../ScanQueryLimitRowIteratorTest.java
* Add intelliJ inspection warnings as errors to druid profile
* one more static inner class
* Make JoinableFactory an extension point
This change makes it so that extensions can register a JoinableFactory that
should be used for a DataSource.
Extensions can provide the factories via DruidBinders#joinableFactoryBinder
Known DataSources - like InlineDataSource are provided in the
JoinableFactoryModule. This module installs a FactoryWarehouse that is
used to decide which factory should be used to generate the Joinable for
the provided DataSource.
The ExtensionPoint is marked as Beta since it is not yet clear if this
needs to remain available to other extensions or if the best way to
register a factory is by using the datasource class.
* Add module test
* remove useless bindings in test
* remove ExtensionPoint annotation
* Make LifecycleLock not final to help with testing
* Reconcile terminology and method naming to 'used/unused segments'; Don't use terms 'enable/disable data source'; Rename MetadataSegmentManager to MetadataSegments; Make REST API methods which mark segments as used/unused to return server error instead of an empty response in case of error
* Fix brace
* Import order
* Rename withKillDataSourceWhitelist to withSpecificDataSourcesToKill
* Fix tests
* Fix tests by adding proper methods without interval parameters to IndexerMetadataStorageCoordinator instead of hacking with Intervals.ETERNITY
* More aligned names of DruidCoordinatorHelpers, rename several CoordinatorDynamicConfig parameters
* Rename ClientCompactTaskQuery to ClientCompactionTaskQuery for consistency with CompactionTask; ClientCompactQueryTuningConfig to ClientCompactionTaskQueryTuningConfig
* More variable and method renames
* Rename MetadataSegments to SegmentsMetadata
* Javadoc update
* Simplify SegmentsMetadata.getUnusedSegmentIntervals(), more javadocs
* Update Javadoc of VersionedIntervalTimeline.iterateAllObjects()
* Reorder imports
* Rename SegmentsMetadata.tryMark... methods to mark... and make them to return boolean and the numbers of segments changed and relay exceptions to callers
* Complete merge
* Add CollectionUtils.newTreeSet(); Refactor DruidCoordinatorRuntimeParams creation in tests
* Remove MetadataSegmentManager
* Rename millisLagSinceCoordinatorBecomesLeaderBeforeCanMarkAsUnusedOvershadowedSegments to leadingTimeMillisBeforeCanMarkAsUnusedOvershadowedSegments
* Fix tests, refactor DruidCluster creation in tests into DruidClusterBuilder
* Fix inspections
* Fix SQLMetadataSegmentManagerEmptyTest and rename it to SqlSegmentsMetadataEmptyTest
* Rename SegmentsAndMetadata to SegmentsAndCommitMetadata to reduce the similarity with SegmentsMetadata; Rename some methods
* Rename DruidCoordinatorHelper to CoordinatorDuty, refactor DruidCoordinator
* Unused import
* Optimize imports
* Rename IndexerSQLMetadataStorageCoordinator.getDataSourceMetadata() to retrieveDataSourceMetadata()
* Unused import
* Update terminology in datasource-view.tsx
* Fix label in datasource-view.spec.tsx.snap
* Fix lint errors in datasource-view.tsx
* Doc improvements
* Another attempt to please TSLint
* Another attempt to please TSLint
* Style fixes
* Fix IndexerSQLMetadataStorageCoordinator.createUsedSegmentsSqlQueryForIntervals() (wrong merge)
* Try to fix docs build issue
* Javadoc and spelling fixes
* Rename SegmentsMetadata to SegmentsMetadataManager, address other comments
* Address more comments
* Add JoinableFactory interface and use it in the query stack.
Also includes InlineJoinableFactory, which enables joining against
inline datasources. This is the first patch where a basic join query
actually works. It includes integration tests.
* Fix test issues.
* Adjustments from code review.
Builds on #9235, using the datasource analysis functionality to replace various ad-hoc
approaches. The most interesting changes are in ClientQuerySegmentWalker (brokers),
ServerManager (historicals), and SinkQuerySegmentWalker (indexing tasks).
Other changes related to improving how we analyze queries:
1) Changes TimelineServerView to return an Optional timeline, which I thought made
the analysis changes cleaner to implement.
2) Added QueryToolChest#canPerformSubquery, which is now used by query entry points to
determine whether it is safe to pass a subquery dataSource to the query toolchest.
Fixes an issue introduced in #5471 where subqueries under non-groupBy-typed queries
were silently ignored, since neither the query entry point nor the toolchest did
anything special with them.
3) Removes the QueryPlus.withQuerySegmentSpec method, which was mostly being used in
error-prone ways (ignoring any potential subqueries, and not verifying that the
underlying data source is actually a table). Replaces with a new function,
Queries.withSpecificSegments, that includes sanity checks.
* Update data-formats.md
Field error and light rewording of new Avro material (and working through the doc authoring process).
* Update data-formats.md
Make default statements consistent. Future change: s/=/is.
* Add join-related DataSource types, and analysis functionality.
Builds on #9111 and implements the datasource analysis mentioned in #8728. Still can't
handle join datasources, but we're a step closer.
Join-related DataSource types:
1) Add "join", "lookup", and "inline" datasources.
2) Add "getChildren" and "withChildren" methods to DataSource, which will be used
in the future for query rewriting (e.g. inlining of subqueries).
DataSource analysis functionality:
1) Add DataSourceAnalysis class, which breaks down datasources into three components:
outer queries, a base datasource (left-most of the highest level left-leaning join
tree), and other joined-in leaf datasources (the right-hand branches of the
left-leaning join tree).
2) Add "isConcrete", "isGlobal", and "isCacheable" methods to DataSource in order to
support analysis.
Other notes:
1) Renamed DataSource#getNames to DataSource#getTableNames, which I think is clearer.
Also, made it a Set, so implementations don't need to worry about duplicates.
2) The addition of "isCacheable" should work around #8713, since UnionDataSource now
returns false for cacheability.
* Remove javadoc comment.
* Updates reflecting code review.
* Add comments.
* Add more comments.
Add more unit tests for range partition native batch parallel indexing.
Also, fix a bug where ParallelIndexPhaseRunner incorrectly thinks that
identical collected DimensionDistributionReports are not equal due to
not overriding equals() in DimensionDistributionReport.
* Optimize JoinCondition matching
The LookupJoinMatcher needs to check if a condition is always true or false
multiple times. This can be pre-computed to speed up the match checking
This change reduces the time it takes to perform a for joining on a long key
from ~ 36 ms/op to 23 ms/ op
* Rename variables
* fix typo
By picking one. Otherwise, when a machine has multiple IP addresses, DOCKER_HOST_IP
would have a newline in the middle, causing havoc in configuration files.
* null handling for numeric first/last aggregators, refactor to not extend nullable numeric agg since they are complex typed aggs
* initially null or not based on config
* review stuff, make string first/last consistent with null handling of numeric columns, more tests
* docs
* handle nil selectors, revert to primitive first/last types so groupby v1 works...
* Doc update for new input source and input format.
- The input source and input format are promoted in all docs under docs/ingestion
- All input sources including core extension ones are located in docs/ingestion/native-batch.md
- All input formats and parsers including core extension ones are localted in docs/ingestion/data-formats.md
- New behavior of the parallel task with different partitionsSpecs are documented in docs/ingestion/native-batch.md
* parquet
* add warning for range partitioning with sequential mode
* hdfs + s3, gs
* add fs impl for gs
* address comments
* address comments
* gcs
* working
* - support multi-char delimiter for tsv
- respect "delimiter" property for tsv
* default value check for findColumnsFromHeader
* remove CSVParser to have a true and only CSVParser
* fix tests
* fix another test
Chi Cao Minh
Aditya
Vadim Ogievetsky
sthetland
zachjsh
Clint Wylie
Suneet Saldanha
Gian Merlino
Maytas Monsereenusorn
Roman Leventov
Yamada Koji
Caroline1000
Zhenxiao Luo
Jihoon Son