* Create new dynamic config to pause coordinator helpers when needed
* Fix spelling mistakes flagged in Travis build
* Add an integration test for coordinator pause dynamic config
* Improve documentation for new dynamic coordinator config and remove un-needed info logs in favor of debug
* address naming convention of 'deep store' vs 'deep storage' in new configs doc line
* Fix newline at end of configuration index.md
* Last try to resolve newline issue in configuration readme
* fix spell checks from travis build
* Fix another flagges spelling error from Travis
* 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
* 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
* 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.
* 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
* Tutorials use new ingestion spec where possible
There are 2 main changes
* Use task type index_parallel instead of index
* Remove the use of parser + firehose in favor of inputFormat + inputSource
index_parallel is the preferred method starting in 0.17. Setting the job to
index_parallel with the default maxNumConcurrentSubTasks(1) is the equivalent
of an index task
Instead of using a parserSpec, dimensionSpec and timestampSpec have been
promoted to the dataSchema. The format is described in the ioConfig as the
inputFormat.
There are a few cases where the new format is not supported
* Hadoop must use firehoses instead of the inputSource and inputFormat
* There is no equivalent of a combining firehose as an inputSource
* A Combining firehose does not support index_parallel
* fix typo
* Fail superbatch range partition multi dim values
Change the behavior of parallel indexing range partitioning to fail
ingestion if any row had multiple values for the partition dimension.
After this change, the behavior matches that of hadoop indexing.
(Previously, rows with multiple dimension values would be skipped.)
* Improve err msg, rename method, rename test class
* Allow startup scripts to specify java home
The startup scripts now look for java in 3 locations. The order is from
most related to druid to least, ie
${DRUID_JAVA_HOME}
${JAVA_HOME}
${PATH}
* Update fn names and clean up code
* final round of fixes
* fix spellcheck
* Parallel indexing single dim partitions
Implements single dimension range partitioning for native parallel batch
indexing as described in #8769. This initial version requires the
druid-datasketches extension to be loaded.
The algorithm has 5 phases that are orchestrated by the supervisor in
`ParallelIndexSupervisorTask#runRangePartitionMultiPhaseParallel()`.
These phases and the main classes involved are described below:
1) In parallel, determine the distribution of dimension values for each
input source split.
`PartialDimensionDistributionTask` uses `StringSketch` to generate
the approximate distribution of dimension values for each input
source split. If the rows are ungrouped,
`PartialDimensionDistributionTask.UngroupedRowDimensionValueFilter`
uses a Bloom filter to skip rows that would be grouped. The final
distribution is sent back to the supervisor via
`DimensionDistributionReport`.
2) The range partitions are determined.
In `ParallelIndexSupervisorTask#determineAllRangePartitions()`, the
supervisor uses `StringSketchMerger` to merge the individual
`StringSketch`es created in the preceding phase. The merged sketch is
then used to create the range partitions.
3) In parallel, generate partial range-partitioned segments.
`PartialRangeSegmentGenerateTask` uses the range partitions
determined in the preceding phase and
`RangePartitionCachingLocalSegmentAllocator` to generate
`SingleDimensionShardSpec`s. The partition information is sent back
to the supervisor via `GeneratedGenericPartitionsReport`.
4) The partial range segments are grouped.
In `ParallelIndexSupervisorTask#groupGenericPartitionLocationsPerPartition()`,
the supervisor creates the `PartialGenericSegmentMergeIOConfig`s
necessary for the next phase.
5) In parallel, merge partial range-partitioned segments.
`PartialGenericSegmentMergeTask` uses `GenericPartitionLocation` to
retrieve the partial range-partitioned segments generated earlier and
then merges and publishes them.
* Fix dependencies & forbidden apis
* Fixes for integration test
* Address review comments
* Fix docs, strict compile, sketch check, rollup check
* Fix first shard spec, partition serde, single subtask
* Fix first partition check in test
* Misc rewording/refactoring to address code review
* Fix doc link
* Split batch index integration test
* Do not run parallel-batch-index twice
* Adjust last partition
* Split ITParallelIndexTest to reduce runtime
* Rename test class
* Allow null values in range partitions
* Indicate which phase failed
* Improve asserts in tests
* add prefixes support to google input source, making it symmetrical-ish with s3
* docs
* more better, and tests
* unused
* formatting
* javadoc
* dependencies
* oops
* review comments
* better javadoc
* add s3 input source for native batch ingestion
* add docs
* fixes
* checkstyle
* lazy splits
* fixes and hella tests
* fix it
* re-use better iterator
* use key
* javadoc and checkstyle
* exception
* oops
* refactor to use S3Coords instead of URI
* remove unused code, add retrying stream to handle s3 stream
* remove unused parameter
* update to latest master
* use list of objects instead of object
* serde test
* refactor and such
* now with the ability to compile
* fix signature and javadocs
* fix conflicts yet again, fix S3 uri stuffs
* more tests, enforce uri for bucket
* javadoc
* oops
* abstract class instead of interface
* null or empty
* better error
* Fix the potential race SplittableInputSource.getNumSplits() and SplittableInputSource.createSplits() in TaskMonitor
* Fix docs and javadoc
* Add unit tests for large or small estimated num splits
* add override
* add parquet support to native batch
* cleanup
* implement toJson for sampler support
* better binaryAsString test
* docs
* i hate spellcheck
* refactor toMap conversion so can be shared through flattenerMaker, default impls should be good enough for orc+avro, fixup for merge with latest
* add comment, fix some stuff
* adjustments
* fix accident
* tweaks
Maytas Monsereenusorn
Clint Wylie
Dusan Maric
Atul Mohan
Lucas Capistrant
Aditya
sthetland
Roman Leventov
Zhenxiao Luo
Suneet Saldanha
Gian Merlino
Jihoon Son
singh
Jonathan Wei
Chi Cao Minh
Himanshu
Benjamin Hopp
Parag Jain
Vadim Ogievetsky
Fangyuan Deng
SeKing
Surekha