* HRTR: make pending task execution handling to go through all tasks on
not finding worker slots
* make HRTR methods package private that are meant to be used only in HttpRemoteTaskRunnerResource
* mark HttpRemoteTaskRunnerWorkItem.State global variables final
* hrtr: move immutableWorker NULL check outside of try-catch or finally block could have NPE
* add some explanatory comments
* add comment on explaining mechanics around hand off of pending tasks from submission to it getting picked up by a task execution thread
* fix spelling
* 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 customize separator for TSV inputFormat
* fix spotbug
* code refactor
* code refactor
* add argument check for delimiter
* refine null check
* add check for delimiter and listdelimiter can not be same
* add unit tests
* Address security vulnerabilities CVSS >= 7
Update dependencies to address security vulnerabilities with CVSS scores
of 7 or higher. A new Travis CI job is added to prevent new
high/critical security vulnerabilities from being added.
Updated dependencies:
- api-util 1.0.0 -> 1.0.3
- jackson 2.9.10 -> 2.10.1
- kafka 2.1.0 -> 2.1.1
- libthrift 0.10.0 -> 0.13.0
- protobuf 3.2.0 -> 3.11.0
The following high/critical security vulnerabilities are currently
suppressed (so that the new Travis CI job can be added now) and are left
as future work to fix:
- hibernate-validator:5.2.5
- jackson-mapper-asl:1.9.13
- libthrift:0.6.1
- netty:3.10.6
- nimbus-jose-jwt:4.41.1
* Rename EDL1 license file
* Fix inspection errors
* 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
* Support orc format for native batch ingestion
* fix pom and remove wrong comment
* fix unnecessary condition check
* use flatMap back to handle exception properly
* move exceptionThrowingIterator to intermediateRowParsingReader
* runtime
* 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 FileUtils.createTempDir() and enforce its usage.
The purpose of this is to improve error messages. Previously, the error
message on a nonexistent or unwritable temp directory would be
"Failed to create directory within 10,000 attempts".
* Further updates.
* Another update.
* Remove commons-io from benchmark.
* Fix tests.
* add TsvInputFormat
* refactor code
* fix grammar
* use enum replace string literal
* code refactor
* code refactor
* mark abstract for base class meant not to be instantiated
* remove constructor for test
* 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
* Refactor parallel indexing perfect rollup partitioning
Refactoring to make it easier to later add range partitioning for
perfect rollup parallel indexing. This is accomplished by adding several
new base classes (e.g., PerfectRollupWorkerTask) and new classes for
encapsulating logic that needs to be changed for different partitioning
strategies (e.g., IndexTaskInputRowIteratorBuilder).
The code is functionally equivalent to before except for the following
small behavior changes:
1) PartialSegmentMergeTask: Previously, this task had a priority of
DEFAULT_TASK_PRIORITY. It now has a priority of
DEFAULT_BATCH_INDEX_TASK_PRIORITY (via the new PerfectRollupWorkerTask
base class), since it is a batch index task.
2) ParallelIndexPhaseRunner: A decorator was added to
subTaskSpecIterator to ensure the subtasks are generated with unique
ids. Previously, only tests (i.e., MultiPhaseParallelIndexingTest)
would have this decorator, but this behavior is desired for non-test
code as well.
* Fix forbidden apis and pmd warnings
* Fix analyze dependencies warnings
* Fix IndexTask json and add IT diags
* Fix parallel index supervisor<->worker serde
* Fix TeamCity inspection errors/warnings
* Fix TeamCity inspection errors/warnings again
* Integrate changes with those from #8823
* Address review comments
* Address more review comments
* Fix forbidden apis
* Address more review comments
* HDFS input source
Add support for using HDFS as an input source. In this version, commas
or globs are not supported in HDFS paths.
* Fix forbidden api
* Address review comments
* Tidy up lifecycle, query, and ingestion logging.
The goal of this patch is to improve the clarity and usefulness of
Druid's logging for cluster operators. For more information, see
https://twitter.com/cowtowncoder/status/1195469299814555648.
Concretely, this patch does the following:
- Changes a lot of INFO logs to DEBUG, and DEBUG to TRACE, with the
goal of reducing redundancy and improving clarity by avoiding
showing rarely-useful log messages. This includes most "starting"
and "stopping" messages, and most messages related to individual
columns.
- Adds new log4j2 templates that show operators how to enabled DEBUG
logging for certain important packages.
- Eliminate stack traces for query errors, unless log level is DEBUG
or more. This is useful because query errors often indicate user
error rather than system error, but dumping stack trace often gave
operators the impression that there was a system failure.
- Adds task id to Appenderator, AppenderatorDriver thread names. In
the default log4j2 configuration, this will put them in log lines
as well. It's very useful if a user is using the Indexer, where
multiple tasks run in the same JVM.
- More consistent terminology when it comes to "sequences" (sets of
segments that are handed-off together by Kafka ingestion) and
"offsets" (cursors in partitions). These terms had been confused in
some log messages due to the fact that Kinesis calls offsets
"sequence numbers".
- Replaces some ugly toString calls with either the JSONification or
something more operator-accessible (like a URL or segment identifier,
instead of JSON object representing the same).
* Adjustments.
* Adjust integration test.
* transformSpec + array expressions
changes:
* added array expression support to transformSpec
* removed ParseSpec.verify since its only use afaict was preventing transform expr that did not replace their input from functioning
* hijacked index task test to test changes
* remove docs about being unsupported
* re-arrange test assert
* unused imports
* imports
* fix tests
* preserve types
* suppress warning, fixes, add test
* formatting
* cleanup
* better list to array type conversion and tests
* fix oops
There is a class of bugs due to the fact that BaseObjectColumnValueSelector
has both "getObject" and "isNull" methods, but in most selector implementations
and most call sites, it is clear that the intent of "isNull" is only to apply
to the primitive getters, not the object getter. This makes sense, because the
purpose of isNull is to enable detection of nulls in otherwise-primitive columns.
Imagine a string column with a numeric selector built on top of it. You would
want it to return isNull = true, so numeric aggregators don't treat it as
all zeroes.
Sometimes this design leads people to accidentally guard non-primitive get
methods with "selector.isNull" checks, which is improper.
This patch has three goals:
1) Fix null-handling bugs that already exist in this class.
2) Make interface and doc changes that reduce the probability of future bugs.
3) Fix other, unrelated bugs I noticed in the stringFirst and stringLast
aggregators while fixing null-handling bugs. I thought about splitting this
into its own patch, but it ended up being tough to split from the
null-handling fixes.
For (1) the fixes are,
- Fix StringFirst and StringLastAggregatorFactory to stop guarding getObject
calls on isNull, by no longer extending NullableAggregatorFactory. Now uses
-1 as a sigil value for null, to differentiate nulls and empty strings.
- Fix ExpressionFilter to stop guarding getObject calls on isNull. Also, use
eval.asBoolean() to avoid calling getLong on the selector after already
calling getObject.
- Fix ObjectBloomFilterAggregator to stop guarding DimensionSelector calls
on isNull. Also, refactored slightly to avoid the overhead of calling
getObject followed by another getter (see BloomFilterAggregatorFactory for
part of this).
For (2) the main changes are,
- Remove the "isNull" method from BaseObjectColumnValueSelector.
- Clarify "isNull" doc on BaseNullableColumnValueSelector.
- Rename NullableAggregatorFactory -> NullbleNumericAggregatorFactory to emphasize
that it only works on aggregators that take numbers as input.
- Similar naming changes to the Aggregator, BufferAggregator, and AggregateCombiner.
- Similar naming changes to helper methods for groupBy, ValueMatchers, etc.
For (3) the other fixes for StringFirst and StringLastAggregatorFactory are,
- Fixed buffer overrun in the buffer aggregators when some characters in the string
code into more than one byte (the old code used "substring" to apply a byte limit,
which is bad). I did this by introducing a new StringUtils.toUtf8WithLimit method.
- Fixed weird IncrementalIndex logic that led to reading nulls for the timestamp.
- Adjusted weird StringFirst/Last logic that worked around the weird IncrementalIndex
behavior.
- Refactored to share code between the four aggregators.
- Improved test coverage.
- Made the base stringFirst, stringLast aggregators adaptive, and streamlined the
xFold versions into aliases. The adaptiveness is similar to how other aggregators
like hyperUnique work.
* sketch of broker parallel merges done in small batches on fork join pool
* fix non-terminating sequences, auto compute parallelism
* adjust benches
* adjust benchmarks
* now hella more faster, fixed dumb
* fix
* remove comments
* log.info for debug
* javadoc
* safer block for sequence to yielder conversion
* refactor LifecycleForkJoinPool into LifecycleForkJoinPoolProvider which wraps a ForkJoinPool
* smooth yield rate adjustment, more logs to help tune
* cleanup, less logs
* error handling, bug fixes, on by default, more parallel, more tests
* remove unused var
* comments
* timeboundary mergeFn
* simplify, more javadoc
* formatting
* pushdown config
* use nanos consistently, move logs back to debug level, bit more javadoc
* static terminal result batch
* javadoc for nullability of createMergeFn
* cleanup
* oops
* fix race, add docs
* spelling, remove todo, add unhandled exception log
* cleanup, revert unintended change
* another unintended change
* review stuff
* add ParallelMergeCombiningSequenceBenchmark, fixes
* hyper-threading is the enemy
* fix initial start delay, lol
* parallelism computer now balances partition sizes to partition counts using sqrt of sequence count instead of sequence count by 2
* fix those important style issues with the benchmarks code
* lazy sequence creation for benchmarks
* more benchmark comments
* stable sequence generation time
* update defaults to use 100ms target time, 4096 batch size, 16384 initial yield, also update user docs
* add jmh thread based benchmarks, cleanup some stuff
* oops
* style
* add spread to jmh thread benchmark start range, more comments to benchmarks parameters and purpose
* retool benchmark to allow modeling more typical heterogenous heavy workloads
* spelling
* fix
* refactor benchmarks
* formatting
* docs
* add maxThreadStartDelay parameter to threaded benchmark
* why does catch need to be on its own line but else doesnt
* IndexerSQLMetadataStorageCoordinator.getTimelineForIntervalsWithHandle() don't fetch abutting intervals; simplify getUsedSegmentsForIntervals()
* Add VersionedIntervalTimeline.findNonOvershadowedObjectsInInterval() method; Propagate the decision about whether only visible segmetns or visible and overshadowed segments should be returned from IndexerMetadataStorageCoordinator's methods to the user logic; Rename SegmentListUsedAction to RetrieveUsedSegmentsAction, SegmetnListUnusedAction to RetrieveUnusedSegmentsAction, and UsedSegmentLister to UsedSegmentsRetriever
* Fix tests
* More fixes
* Add javadoc notes about returning Collection instead of Set. Add JacksonUtils.readValue() to reduce boilerplate code
* Fix KinesisIndexTaskTest, factor out common parts from KinesisIndexTaskTest and KafkaIndexTaskTest into SeekableStreamIndexTaskTestBase
* More test fixes
* More test fixes
* Add a comment to VersionedIntervalTimelineTestBase
* Fix tests
* Set DataSegment.size(0) in more tests
* Specify DataSegment.size(0) in more places in tests
* Fix more tests
* Fix DruidSchemaTest
* Set DataSegment's size in more tests and benchmarks
* Fix HdfsDataSegmentPusherTest
* Doc changes addressing comments
* Extended doc for visibility
* Typo
* Typo 2
* Address comment
* remove select query
* thanks teamcity
* oops
* oops
* add back a SelectQuery class that throws RuntimeExceptions linking to docs
* adjust text
* update docs per review
* deprecated
When using single-dimension partitioning, use targetRowsPerSegment (if
specified) to size segments. Previously, single-dimension partitioning
would always size segments as close to the max size as possible.
Also, change single-dimension partitioning to allow partitions that have
a size equal to the target or max size. Previously, it would create
partitions up to 1 less than those limits.
Also, fix some IntelliJ inspection warnings in HadoopDruidIndexerConfig.
Jonathan Wei
Jihoon Son
Himanshu
Chi Cao Minh
Clint Wylie
Rye
Roman Leventov
jon-wei
Atul Mohan
Gian Merlino
Zhenxiao Luo