* Add error msg to parallel task's TaskStatus
* Consolidate failure block
* Add failure test
* Make it fail
* Add fail while stopped
* Simplify hash task test using a runner that fails after so many runs (parameter)
* Remove unthrown exception
* Use runner names to identify phase
* Added range partition kill test & fixed a timing bug with the custom runner
* Forbidden api
* Style
* Unit test code cleanup
* Added message to invalid state exception and improved readability of the phase error messages for the parallel task failure unit tests
This PR splits current SegmentLoader into SegmentLoader and SegmentCacheManager.
SegmentLoader - this class is responsible for building the segment object but does not expose any methods for downloading, cache space management, etc. Default implementation delegates the download operations to SegmentCacheManager and only contains the logic for building segments once downloaded. . This class will be used in SegmentManager to construct Segment objects.
SegmentCacheManager - this class manages the segment cache on the local disk. It fetches the segment files to the local disk, can clean up the cache, and in the future, support reserve and release on cache space. [See https://github.com/Make SegmentLoader extensible and customizable #11398]. This class will be used in ingestion tasks such as compaction, re-indexing where segment files need to be downloaded locally.
This PR refactors the code for QueryRunnerFactory#mergeRunners to accept a new interface called QueryProcessingPool instead of ExecutorService for concurrent execution of query runners. This interface will let custom extensions inject their own implementation for deciding which query-runner to prioritize first. The default implementation is the same as today that takes the priority of query into account. QueryProcessingPool can also be used as a regular executor service. It has a dedicated method for accepting query execution work so implementations can differentiate between regular async tasks and query execution tasks. This dedicated method also passes the QueryRunner object as part of the task information. This hook will let custom extensions carry any state from QuerySegmentWalker to QueryProcessingPool#mergeRunners which is not possible currently.
* Avoid mapping hydrants in create segments phase for native ingestion
* Drop queriable indices after a given sink is fully merged
* Do not drop memory mappings for realtime ingestion
* Style fixes
* Renamed to match use case better
* Rollback memoization code and use the real time flag instead
* Null ptr fix in FireHydrant toString plus adjustments to memory pressure tracking calculations
* Style
* Log some count stats
* Make sure sinks size is obtained at the right time
* BatchAppenderator unit test
* Fix comment typos
* Renamed methods to make them more readable
* Move persisted metadata from FireHydrant class to AppenderatorImpl. Removed superfluous differences and fix comment typo. Removed custom comparator
* Missing dependency
* Make persisted hydrant metadata map concurrent and better reflect the fact that keys are Java references. Maintain persisted metadata when dropping/closing segments.
* Replaced concurrent variables with normal ones
* Added batchMemoryMappedIndex "fallback" flag with default "false". Set this to "true" make code fallback to previous code path.
* Style fix.
* Added note to new setting in doc, using Iterables.size (and removing a dependency), and fixing a typo in a comment.
* Forgot to commit this edited documentation message
* Add ability to wait for segment availability for batch jobs
* IT updates
* fix queries in legacy hadoop IT
* Fix broken indexing integration tests
* address an lgtm flag
* spell checker still flagging for hadoop doc. adding under that file header too
* fix compaction IT
* Updates to wait for availability method
* improve unit testing for patch
* fix bad indentation
* refactor waitForSegmentAvailability
* Fixes based off of review comments
* cleanup to get compile after merging with master
* fix failing test after previous logic update
* add back code that must have gotten deleted during conflict resolution
* update some logging code
* fixes to get compilation working after merge with master
* reset interrupt flag in catch block after code review pointed it out
* small changes following self-review
* fixup some issues brought on by merge with master
* small changes after review
* cleanup a little bit after merge with master
* Fix potential resource leak in AbstractBatchIndexTask
* syntax fix
* Add a Compcation TuningConfig type
* add docs stipulating the lack of support by Compaction tasks for the new config
* Fixup compilation errors after merge with master
* Remove erreneous newline
* DruidInputSource: Fix issues in column projection, timestamp handling.
DruidInputSource, DruidSegmentReader changes:
1) Remove "dimensions" and "metrics". They are not necessary, because we
can compute which columns we need to read based on what is going to
be used by the timestamp, transform, dimensions, and metrics.
2) Start using ColumnsFilter (see below) to decide which columns we need
to read.
3) Actually respect the "timestampSpec". Previously, it was ignored, and
the timestamp of the returned InputRows was set to the `__time` column
of the input datasource.
(1) and (2) together fix a bug in which the DruidInputSource would not
properly read columns that are used as inputs to a transformSpec.
(3) fixes a bug where the timestampSpec would be ignored if you attempted
to set the column to something other than `__time`.
(1) and (3) are breaking changes.
Web console changes:
1) Remove "Dimensions" and "Metrics" from the Druid input source.
2) Set timestampSpec to `{"column": "__time", "format": "millis"}` for
compatibility with the new behavior.
Other changes:
1) Add ColumnsFilter, a new class that allows input readers to determine
which columns they need to read. Currently, it's only used by the
DruidInputSource, but it could be used by other columnar input sources
in the future.
2) Add a ColumnsFilter to InputRowSchema.
3) Remove the metric names from InputRowSchema (they were unused).
4) Add InputRowSchemas.fromDataSchema method that computes the proper
ColumnsFilter for given timestamp, dimensions, transform, and metrics.
5) Add "getRequiredColumns" method to TransformSpec to support the above.
* Various fixups.
* Uncomment incorrectly commented lines.
* Move TransformSpecTest to the proper module.
* Add druid.indexer.task.ignoreTimestampSpecForDruidInputSource setting.
* Fix.
* Fix build.
* Checkstyle.
* Misc fixes.
* Fix test.
* Move config.
* Fix imports.
* Fixup.
* Fix ShuffleResourceTest.
* Add import.
* Smarter exclusions.
* Fixes based on tests.
Also, add TIME_COLUMN constant in the web console.
* Adjustments for tests.
* Reorder test data.
* Update docs.
* Update docs to say Druid 0.22.0 instead of 0.21.0.
* Fix test.
* Fix ITAutoCompactionTest.
* Changes from review & from merging.
* druid task auto scale based on kafka lag
* fix kafkaSupervisorIOConfig and KinesisSupervisorIOConfig
* druid task auto scale based on kafka lag
* fix kafkaSupervisorIOConfig and KinesisSupervisorIOConfig
* test dynamic auto scale done
* auto scale tasks tested on prd cluster
* auto scale tasks tested on prd cluster
* modify code style to solve 29055.10 29055.9 29055.17 29055.18 29055.19 29055.20
* rename test fiel function
* change codes and add docs based on capistrant reviewed
* midify test docs
* modify docs
* modify docs
* modify docs
* merge from master
* Extract the autoScale logic out of SeekableStreamSupervisor to minimize putting more stuff inside there && Make autoscaling algorithm configurable and scalable.
* fix ci failed
* revert msic.xml
* add uts to test autoscaler create && scale out/in and kafka ingest with scale enable
* add more uts
* fix inner class check
* add IT for kafka ingestion with autoscaler
* add new IT in groups=kafka-index named testKafkaIndexDataWithWithAutoscaler
* review change
* code review
* remove unused imports
* fix NLP
* fix docs and UTs
* revert misc.xml
* use jackson to build autoScaleConfig with default values
* add uts
* use jackson to init AutoScalerConfig in IOConfig instead of Map<>
* autoscalerConfig interface and provide a defaultAutoScalerConfig
* modify uts
* modify docs
* fix checkstyle
* revert misc.xml
* modify uts
* reviewed code change
* reviewed code change
* code reviewed
* code review
* log changed
* do StringUtils.encodeForFormat when create allocationExec
* code review && limit taskCountMax to partitionNumbers
* modify docs
* code review
Co-authored-by: yuezhang <yuezhang@freewheel.tv>
* add offsetFetchPeriod to kinesis ingestion doc
* Remove jackson dependencies from extensions
* Use fixed delay for lag collection
* Metrics reset after finishing processing
* comments
* Broaden the list of exceptions to retry for
* Unit tests
* Add more tests
* Refactoring
* re-order metrics
* Doc suggestions
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Add tests
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix checkstyle
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix test
* fix test
* add log
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* address comments
* fix checkstyle
* fix checkstyle
* add config to skip overhead memory calculation
* add test for the skipBytesInMemoryOverheadCheck config
* add docs
* fix checkstyle
* fix checkstyle
* fix spelling
* address comments
* fix travis
* address comments
Today Kafka message support in streaming indexing tasks is limited to
message values, and does not provide a way to expose Kafka headers,
timestamps, or keys, which may be of interest to more specialized
Druid input formats. For instance, Kafka headers may be used to indicate
payload format/encoding or additional metadata, and timestamps are often
omitted from values in Kafka streams applications, since they are
included in the record.
This change proposes to introduce KafkaRecordEntity as InputEntity,
which would give input formats full access to the underlying Kafka record,
including headers, key, timestamps. It would also open access to low-level
information such as topic, partition, offset if needed.
KafkaEntity is a subclass of ByteEntity for backwards compatibility with
existing input formats, and to avoid introducing unnecessary complexity
for Kinesis indexing tasks.
* support multi-line text
* add test cases
* split json text into lines case by case
* improve exception handle
* fix CI
* use IntermediateRowParsingReader as base of JsonReader
* update doc
* ignore the non-immutable field in test case
* add more test cases
* mark `lineSplittable` as final
* fix testcases
* fix doc
* add a test case for SqlReader
* return all raw columns when exception occurs
* fix CI
* fix test cases
* resolve review comments
* handle ParseException returned by index.add
* apply Iterables.getOnlyElement
* fix CI
* fix test cases
* improve code in more graceful way
* fix test cases
* fix test cases
* add a test case to check multiple json string in one text block
* fix inspection check
* Introduce a Configurable Index Type
* Change to @UnstableApi
* Add AppendableIndexSpecTest
* Update doc
* Add spelling exception
* Add tests coverage
* Revert some of the changes to reduce diff
* Minor fixes
* Update getMaxBytesInMemoryOrDefault() comment
* Fix typo, remove redundant interface
* Remove off-heap spec (postponed to a later PR)
* Add javadocs to AppendableIndexSpec
* Describe testCreateTask()
* Add tests for AppendableIndexSpec within TuningConfig
* Modify hashCode() to conform with equals()
* Add comment where building incremental-index
* Add "EqualsVerifier" tests
* Revert some of the API back to AppenderatorConfig
* Don't use multi-line comments
* Remove knob documentation (deferred)
* Move tools for indexing to TaskToolbox instead of injecting them in constructor
* oops, other changes
* fix test
* unnecessary new file
* fix test
* fix build
* Add validation for authorizer name
* fix deps
* add javadocs
* Do not use resource filters
* Fix BasicAuthenticatorResource as well
* Add integration tests
* fix test
* fix
* QueryCountStatsMonitor can be injected in the Peon
This change fixes a dependency injection bug where there is a circular
dependency on getting the MonitorScheduler when a user configures the
QueryCountStatsMonitor to be used.
* fix tests
* Actually fix the tests this time
* retry 500 and 503 errors against kinesis
* add test that exercises retry logic
* more branch coverage
* retry 500 and 503 on getRecords request when fetching sequence numberu
Co-authored-by: Harshpreet Singh <hrshpr@twitch.tv>
* IntelliJ inspection and checkstyle rule for "Collection.EMPTY_* field accesses replaceable with Collections.empty*()"
* Reverted checkstyle rule
* Added tests to pass CI
* Codestyle
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.
* 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 flag to flattenSpec to keep null columns
* remove changes to inputFormat interface
* add comment
* change comment message
* update web console e2e test
* move keepNullColmns to JSONParseSpec
* fix merge conflicts
* fix tests
* set keepNullColumns to false by default
* fix lgtm
* change Boolean to boolean, add keepNullColumns to hash, add tests for keepKeepNullColumns false + true with no nuulul columns
* Add equals verifier tests
* add kinesis lag metric
* fixes
* heh
* do it right this time
* more test
* split out supervisor report lags into lagMillis, remove latest offsets from kinesis supervisor report since always null, review stuffs
* 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.
Agustin Gonzalez
Abhishek Agarwal
Yi Yuan
Lucas Capistrant
Gian Merlino
zhangyue19921010
Maytas Monsereenusorn
Jihoon Son
Xavier Léauté
Jonathan Wei
frank chen
Liran Funaro
Suneet Saldanha
Clint Wylie
Harshpreet Singh
Aleksey Plekhanov
mcbrewster
Maytas Monsereenusorn
Roman Leventov
Chi Cao Minh
jon-wei