* https://github.com/apache/incubator-druid/issues/7316 Use Map.putIfAbsent() instead of containsKey() + put()
* fixing indentation
* Using map.computeIfAbsent() instead of map.putIfAbsent() where appropriate
* fixing checkstyle
* Changing the recommendation text
* Reverting auto changes made by IDE
* Implementing recommendation: A ConcurrentHashMap on which computeIfAbsent() is called should be assigned into variables of ConcurrentHashMap type, not ConcurrentMap
* Removing unused import
* Throw caught exception.
* Throw caught exceptions.
* Related checkstyle rule is added to prevent further bugs.
* RuntimeException() is used instead of Throwables.propagate().
* Missing import is added.
* Throwables are propogated if possible.
* Throwables are propogated if possible.
* Throwables are propogated if possible.
* Throwables are propogated if possible.
* * Checkstyle definition is improved.
* Throwables.propagate() usages are removed.
* Checkstyle pattern is changed for only scanning "Throwables.propagate(" instead of checking lookbehind.
* Throwable is kept before firing a Runtime Exception.
* Fix unused assignments.
* write null byte in hadoop indexing for numeric dimensions
* Add test case to check output serializing null numeric dimensions
* Remove extra line
* Add @Nullable annotations
* Remove DataSegmentFinder, InsertSegmentToDb, and descriptor.json file
* delete descriptor.file when killing segments
* fix test
* Add doc for ha
* improve warning
* Fix:
1. hadoop-common dependency for druid-hdfs and druid-kerberos extensions
Refactoring:
2. Hadoop config call in the inner static class to avoid class path conflicts for stopGracefully kill
* Fix:
1. hadoop-common test dependency
* Fix:
1. Avoid issue of kill command once the job is actually completed
* KillTask from overlord UI now makes sure that it terminates the underlying MR job, thus saving unnecessary compute
Run in jobby is now split into 2
1. submitAndGetHadoopJobId followed by 2. run
submitAndGetHadoopJobId is responsible for submitting the job and returning the jobId as a string, run monitors this job for completion
JobHelper writes this jobId in the path provided by HadoopIndexTask which in turn is provided by the ForkingTaskRunner
HadoopIndexTask reads this path when kill task is clicked to get hte jobId and fire the kill command via the yarn api. This is taken care in the stopGracefully method which is called in SingleTaskBackgroundRunner. Have enabled `canRestore` method to return `true` for HadoopIndexTask in order for the stopGracefully method to be called
Hadoop*Job files have been changed to incorporate the changes to jobby
* Addressing PR comments
* Addressing PR comments - Fix taskDir
* Addressing PR comments - For changing the contract of Task.stopGracefully()
`SingleTaskBackgroundRunner` calls stopGracefully in stop() and then checks for canRestore condition to return the status of the task
* Addressing PR comments
1. Formatting
2. Removing `submitAndGetHadoopJobId` from `Jobby` and calling writeJobIdToFile in the job itself
* Addressing PR comments
1. POM change. Moving hadoop dependency to indexing-hadoop
* Addressing PR comments
1. stopGracefully now accepts TaskConfig as a param
Handling isRestoreOnRestart in stopGracefully for `AppenderatorDriverRealtimeIndexTask, RealtimeIndexTask, SeekableStreamIndexTask`
Changing tests to make TaskConfig param isRestoreOnRestart to true
* Use multi-guava version friendly direct executor implementation
* Don't use a singleton
* Fix strict compliation complaints
* Copy Guava's DirectExecutor
* Fix javadoc
* Imports are the devil
* Add checkstyle rules about imports and empty lines between members
* Add suppressions
* Update Eclipse import order
* Add empty line
* Fix StatsDEmitter
* Prohibit some guava collection APIs and use JDK APIs directly
* reset files that changed by accident
* sort codestyle/druid-forbidden-apis.txt alphabetically
This PR accumulates many refactorings and small improvements that I did while preparing the next change set of https://github.com/druid-io/druid/projects/2. I finally decided to make them a separate PR to minimize the volume of the main PR.
Some of the changes:
- Renamed confusing "Generic Column" term to "Numeric Column" (what it actually implies) in many class names.
- Generified `ComplexMetricExtractor`
* Rename io.druid to org.apache.druid.
* Fix META-INF files and remove some benchmark results.
* MonitorsConfig update for metrics package migration.
* Reorder some dimensions in inner queries for some reason.
* Fix protobuf tests.
* Various changes about druid-services module
* Patch improvements from reviewer
* Add ToArrayCallWithZeroLengthArrayArgument & ArraysAsListWithZeroOrOneArgument into inspection profile
* Fix ArraysAsListWithZeroOrOneArgument
* Fix conflict
* Fix ToArrayCallWithZeroLengthArrayArgument
* Fix AliEqualsAvoidNull
* Remove blank line
* Remove unused import clauses
* Fix code style in TopNQueryRunnerTest
* Fix conflict
* Don't use Collections.singletonList when converting the type of array type
* Add argLine into maven-surefire-plugin in druid-process module & increase the timeout value for testMoveSegment testcase
* Roll back the latest commit
* Add java.io.File#toURL() into druid-forbidden-apis
* Using Boolean.parseBoolean instead of Boolean.valueOf for CliCoordinator#isOverlord
* Add a new regexp element into stylecode xml file
* Fix style error for new regexp
* Set the level of ArraysAsListWithZeroOrOneArgument as WARNING
* Fix style error for new regexp
* Add option BY_LEVEL for ToArrayCallWithZeroLengthArrayArgument in inspection profile
* Roll back the level as ToArrayCallWithZeroLengthArrayArgument as ERROR
* Add toArray(new Object[0]) regexp into checkstyle config file & fix them
* Set the level of ArraysAsListWithZeroOrOneArgument as ERROR & Roll back the level of ToArrayCallWithZeroLengthArrayArgument as WARNING until Youtrack fix it
* Add a comment for string equals regexp in checkstyle config
* Fix code format
* Add RedundantTypeArguments as ERROR level inspection
* Fix cannot resolve symbol datasource
* VersionedIntervalTimeline: Optimize construction with heavily populated holders.
Each time a segment is "add"ed to a timeline, "isComplete" is called on the holder
that it is added to. "isComplete" is an O(segments per chunk) operation, meaning
that adding N segments to a chunk is an O(N^2) operation. This blows up badly if
we have thousands of segments per chunk.
The patch defers the "isComplete" check until after all segments have been
inserted.
* Fix imports.
* Remove setParitionerClass call from SortableBytes since callers override the paritioner class themselves
* Get rid of SortableBytesPartitioner class
* Make partitioner class a parameter
* This commit introduces a new tuning config called 'maxBytesInMemory' for ingestion tasks
Currently a config called 'maxRowsInMemory' is present which affects how much memory gets
used for indexing.If this value is not optimal for your JVM heap size, it could lead
to OutOfMemoryError sometimes. A lower value will lead to frequent persists which might
be bad for query performance and a higher value will limit number of persists but require
more jvm heap space and could lead to OOM.
'maxBytesInMemory' is an attempt to solve this problem. It limits the total number of bytes
kept in memory before persisting.
* The default value is 1/3(Runtime.maxMemory())
* To maintain the current behaviour set 'maxBytesInMemory' to -1
* If both 'maxRowsInMemory' and 'maxBytesInMemory' are present, both of them
will be respected i.e. the first one to go above threshold will trigger persist
* Fix check style and remove a comment
* Add overlord unsecured paths to coordinator when using combined service (#5579)
* Add overlord unsecured paths to coordinator when using combined service
* PR comment
* More error reporting and stats for ingestion tasks (#5418)
* Add more indexing task status and error reporting
* PR comments, add support in AppenderatorDriverRealtimeIndexTask
* Use TaskReport instead of metrics/context
* Fix tests
* Use TaskReport uploads
* Refactor fire department metrics retrieval
* Refactor input row serde in hadoop task
* Refactor hadoop task loader names
* Truncate error message in TaskStatus, add errorMsg to task report
* PR comments
* Allow getDomain to return disjointed intervals (#5570)
* Allow getDomain to return disjointed intervals
* Indentation issues
* Adding feature thetaSketchConstant to do some set operation in PostAgg (#5551)
* Adding feature thetaSketchConstant to do some set operation in PostAggregator
* Updated review comments for PR #5551 - Adding thetaSketchConstant
* Fixed CI build issue
* Updated review comments 2 for PR #5551 - Adding thetaSketchConstant
* Fix taskDuration docs for KafkaIndexingService (#5572)
* With incremental handoff the changed line is no longer true.
* Add doc for automatic pendingSegments (#5565)
* Add missing doc for automatic pendingSegments
* address comments
* Fix indexTask to respect forceExtendableShardSpecs (#5509)
* Fix indexTask to respect forceExtendableShardSpecs
* add comments
* Deprecate spark2 profile in pom.xml (#5581)
Deprecated due to https://github.com/druid-io/druid/pull/5382
* CompressionUtils: Add support for decompressing xz, bz2, zip. (#5586)
Also switch various firehoses to the new method.
Fixes#5585.
* This commit introduces a new tuning config called 'maxBytesInMemory' for ingestion tasks
Currently a config called 'maxRowsInMemory' is present which affects how much memory gets
used for indexing.If this value is not optimal for your JVM heap size, it could lead
to OutOfMemoryError sometimes. A lower value will lead to frequent persists which might
be bad for query performance and a higher value will limit number of persists but require
more jvm heap space and could lead to OOM.
'maxBytesInMemory' is an attempt to solve this problem. It limits the total number of bytes
kept in memory before persisting.
* The default value is 1/3(Runtime.maxMemory())
* To maintain the current behaviour set 'maxBytesInMemory' to -1
* If both 'maxRowsInMemory' and 'maxBytesInMemory' are present, both of them
will be respected i.e. the first one to go above threshold will trigger persist
* Address code review comments
* Fix the coding style according to druid conventions
* Add more javadocs
* Rename some variables/methods
* Other minor issues
* Address more code review comments
* Some refactoring to put defaults in IndexTaskUtils
* Added check for maxBytesInMemory in AppenderatorImpl
* Decrement bytes in abandonSegment
* Test unit test for multiple sinks in single appenderator
* Fix some merge conflicts after rebase
* Fix some style checks
* Merge conflicts
* Fix failing tests
Add back check for 0 maxBytesInMemory in OnHeapIncrementalIndex
* Address PR comments
* Put defaults for maxRows and maxBytes in TuningConfig
* Change/add javadocs
* Refactoring and renaming some variables/methods
* Fix TeamCity inspection warnings
* Added maxBytesInMemory config to HadoopTuningConfig
* Updated the docs and examples
* Added maxBytesInMemory config in docs
* Removed references to maxRowsInMemory under tuningConfig in examples
* Set maxBytesInMemory to 0 until used
Set the maxBytesInMemory to 0 if user does not set it as part of tuningConfing
and set to part of max jvm memory when ingestion task starts
* Update toString in KafkaSupervisorTuningConfig
* Use correct maxBytesInMemory value in AppenderatorImpl
* Update DEFAULT_MAX_BYTES_IN_MEMORY to 1/6 max jvm memory
Experimenting with various defaults, 1/3 jvm memory causes OOM
* Update docs to correct maxBytesInMemory default value
* Minor to rename and add comment
* Add more details in docs
* Address new PR comments
* Address PR comments
* Fix spelling typo
In DeterminePartitonsJob -
config.get("mapred.job.tracker").equals("local") throws NPE as the
property name is changed in hadoop 3.0 to mapreduce.jobtracker.address
This patch extracts the logic to fetch jobTrackerAddress in JobHelper
and reuses it when needed.
* Add more indexing task status and error reporting
* PR comments, add support in AppenderatorDriverRealtimeIndexTask
* Use TaskReport instead of metrics/context
* Fix tests
* Use TaskReport uploads
* Refactor fire department metrics retrieval
* Refactor input row serde in hadoop task
* Refactor hadoop task loader names
* Truncate error message in TaskStatus, add errorMsg to task report
* PR comments
Sashidhar Thallam
Jihoon Son
Himanshu
Jonathan Wei
Fokko Driesprong
Samarth Jain
Faxian Zhao
Roman Leventov
Furkan KAMACI
Clint Wylie
Ferris Tseng
Ankit Kothari
Charles Allen
Christoph Hösler
QiuMM
David Lim
David Lim
Atul Mohan
Gian Merlino
es1220
Nishant Bangarwa
Benedict Jin
Surekha