With this change, Druid will only support ZooKeeper 3.5.x and later.
In order to support Java 15 we need to switch to ZK 3.5.x client libraries and drop support for ZK 3.4.x
(see #10780 for the detailed reasons)
* remove ZooKeeper 3.4.x compatibility
* exclude additional ZK 3.5.x netty dependencies to ensure we use our version
* keep ZooKeeper version used for integration tests in sync with client library version
* remove the need to specify ZK version at runtime for docker
* add support to run integration tests with JDK 15
* build and run unit tests with Java 15 in travis
* 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
* fix count and average SQL aggregators on constant virtual columns
* style
* even better, why are we tracking virtual columns in aggregations at all if we have a virtual column registry
* oops missed a few
* remove unused
* this will fix it
* SQL timeseries no longer skip empty buckets with all granularity
* add comment, fix tests
* the ol switcheroo
* revert unintended change
* docs and more tests
* style
* make checkstyle happy
* docs fixes and more tests
* add docs, tests for array_agg
* fixes
* oops
* doc stuffs
* fix compile, match doc style
* allow user to set group.id for Kafka ingestion task
* fix test coverage by removing deprecated code and add doc
* fix typo
* Update docs/development/extensions-core/kafka-ingestion.md
Co-authored-by: frank chen <frankchen@apache.org>
Co-authored-by: frank chen <frankchen@apache.org>
* Vectorize the DataSketches quantiles aggregator.
Also removes synchronization for the BufferAggregator and VectorAggregator
implementations, since it is not necessary (similar to #11115).
Extends DoublesSketchAggregatorTest and DoublesSketchSqlAggregatorTest
to run all test cases in vectorized mode.
* Style fix.
* upgrade to Apache Kafka 2.8.0 (release notes:
https://downloads.apache.org/kafka/2.8.0/RELEASE_NOTES.html)
* pass Kafka version as a Docker argument in integration tests
to keep in sync with maven version
* fix use of internal Kafka APIs in integration tests
* Vectorized versions of HllSketch aggregators.
The patch uses the same "helper" approach as #10767 and #10304, and
extends the tests to run in both vectorized and non-vectorized modes.
Also includes some minor changes to the theta sketch vector aggregator:
- Cosmetic changes to make the hll and theta implementations look
more similar.
- Extends the theta SQL tests to run in vectorized mode.
* Updates post-code-review.
* Fix javadoc.
* Enable rewriting certain inner joins as filters.
The main logic for doing the rewrite is in JoinableFactoryWrapper's
segmentMapFn method. The requirements are:
- It must be an inner equi-join.
- The right-hand columns referenced by the condition must not contain any
duplicate values. (If they did, the inner join would not be guaranteed
to return at most one row for each left-hand-side row.)
- No columns from the right-hand side can be used by anything other than
the join condition itself.
HashJoinSegmentStorageAdapter is also modified to pass through to
the base adapter (even allowing vectorization!) in the case where 100%
of join clauses could be rewritten as filters.
In support of this goal:
- Add Query getRequiredColumns() method to help us figure out whether
the right-hand side of a join datasource is being used or not.
- Add JoinConditionAnalysis getRequiredColumns() method to help us
figure out if the right-hand side of a join is being used by later
join clauses acting on the same base.
- Add Joinable getNonNullColumnValuesIfAllUnique method to enable
retrieving the set of values that will form the "in" filter.
- Add LookupExtractor canGetKeySet() and keySet() methods to support
LookupJoinable in its efforts to implement the new Joinable method.
- Add "enableRewriteJoinToFilter" feature flag to
JoinFilterRewriteConfig. The default is disabled.
* Test improvements.
* Test fixes.
* Avoid slow size() call.
* Remove invalid test.
* Fix style.
* Fix mistaken default.
* Small fixes.
* Fix logic error.
* add protobuf inputformat
* repair pom
* alter intermediateRow to type of Dynamicmessage
* add document
* refine test
* fix document
* add protoBytesDecoder
* refine document and add ser test
* add hash
* add schema registry ser test
Co-authored-by: yuanyi <yuanyi@freewheel.tv>
* 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.
* Allow only HTTP and HTTPS protocols for the HTTP inputSource
* rename
* Update core/src/main/java/org/apache/druid/data/input/impl/HttpInputSource.java
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* fix http firehose and update doc
* HDFS inputSource
* add configs for allowed protocols
* fix checkstyle and doc
* more checkstyle
* remove stale doc
* remove more doc
* Apply doc suggestions from code review
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* update hdfs address in docs
* fix test
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* 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 config and header support for confluent schema registry. (porting code from https://github.com/apache/druid/pull/9096)
* Add Eclipse Public License 2.0 to license check
* Update licenses.yaml, revert changes to check-licenses.py and dependencies for integration-tests
* Add spelling exception and remove unused dependency
* Use non-deprecated getSchemaById() and remove duplicated license entry
* Update docs/ingestion/data-formats.md
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* Added check for schema being null, as per Confluent code
* Missing imports and whitespace
* Updated unit tests with AvroSchema
Co-authored-by: Sergio Spinatelli <sergio.spinatelli.extern@7-tv.de>
Co-authored-by: Sergio Spinatelli <sergio.spinatelli.extern@joyn.de>
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* use the latest Apache DataSketches release 2.0.0
* updated datasketches version
Co-authored-by: AlexanderSaydakov <AlexanderSaydakov@users.noreply.github.com>
* before i leaped i should've seen, the view from halfway down
* fixes
* fixes, more test
* rename
* fix style
* further refactoring
* review stuffs
* rename
* more javadoc and comments
* 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>
* Vectorized theta sketch aggregator.
Also a refactoring of BufferAggregator and VectorAggregator such that
they share a common interface, BaseBufferAggregator. This allows
implementing both in the same file with an abstract + dual subclass
structure.
* Rework implementation to use composition instead of inheritance.
* Rework things to enable working properly for both complex types and
regular types.
Involved finally moving makeVectorProcessor from DimensionHandlerUtils
into ColumnProcessors and harmonizing the two things.
* Add missing method.
* Style and name changes.
* Fix issues from inspections.
* Fix style issue.
* 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.
* integration test for coordinator and overlord leadership, added sys.servers is_leader column
* docs
* remove not needed
* fix comments
* fix compile heh
* oof
* revert unintended
* fix tests, split out docker-compose file selection from starting cluster, use docker-compose down to stop cluster
* fixes
* style
* dang
* heh
* scripts are hard
* fix spelling
* fix thing that must not matter since was already wrong ip, log when test fails
* needs more heap
* fix merge
* less aggro
dependabot[bot]
Egor Riashin
Abhishek Agarwal
Xavier Léauté
Agustin Gonzalez
Clint Wylie
Yuanli Han
Gian Merlino
Jihoon Son
Yi Yuan
Makdon
Lucas Capistrant
Himanshu
Parag Jain
zhangyue19921010
Maytas Monsereenusorn
spinatelli
Alexander Saydakov
Benedict Jin
Jonathan Wei
Himadri Singh