Changes:
- Fix race condition in KubernetesTaskRunner introduced by #14435
- Perform addition and removal from map inside a synchronized block
- Update tests
changes:
* new filters that preserve match value typing to better handle filtering different column types
* sql planner uses new filters by default in sql compatible null handling mode
* remove isFilterable from column capabilities
* proper handling of array filtering, add array processor to column processors
* javadoc for sql test filter functions
* range filter support for arrays, tons more tests, fixes
* add dimension selector tests for mixed type roots
* support json equality
* rename semantic index maker thingys to mostly have plural names since they typically make many indexes, e.g. StringValueSetIndex -> StringValueSetIndexes
* add cooler equality index maker, ValueIndexes
* fix missing string utf8 index supplier
* expression array comparator stuff
This adds a new contrib extension: druid-iceberg-extensions which can be used to ingest data stored in Apache Iceberg format. It adds a new input source of type iceberg that connects to a catalog and retrieves the data files associated with an iceberg table and provides these data file paths to either an S3 or HDFS input source depending on the warehouse location.
Two important dependencies associated with Apache Iceberg tables are:
Catalog : This extension supports reading from either a Hive Metastore catalog or a Local file-based catalog. Support for AWS Glue is not available yet.
Warehouse : This extension supports reading data files from either HDFS or S3. Adapters for other cloud object locations should be easy to add by extending the AbstractInputSourceAdapter.
Apache Druid brings multiple direct and transitive dependencies that are affected by plethora of CVEs.
This PR attempts to update all the dependencies that did not require code refactoring.
This PR modifies pom files, license file and OWASP Dependency Check suppression file.
* Fix EarliestLatestBySqlAggregator signature; Include function name for all signatures.
* Single quote function signatures, space between args and remove \n.
* fixup UT assertion
In this PR, we are enhancing KafkaEmitter, to emit metadata about published segments (SegmentMetadataEvent) into a Kafka topic. This segment metadata information that gets published into Kafka, can be used by any other downstream services to query Druid intelligently based on the segments published. The segment metadata gets published into kafka topic in json string format similar to other events.
It was found that several supported tasks / input sources did not have implementations for the methods used by the input source security feature, causing these tasks and input sources to fail when used with this feature. This pr adds the needed missing implementations. Also securing the sampling endpoint with input source security, when enabled.
* Be able to load segments on Peons
This change introduces a new config on WorkerConfig
that indicates how many bytes of each storage
location to use for storage of a task. Said config
is divided up amongst the locations and slots
and then used to set TaskConfig.tmpStorageBytesPerTask
The Peons use their local task dir and
tmpStorageBytesPerTask as their StorageLocations for
the SegmentManager such that they can accept broadcast
segments.
* queue tasks if all slots in use
* Declare hamcrest-core dependency
* Use AtomicBoolean for shutdown requested
* Use AtomicReference for peon lifecycle state
* fix uninitialized read error
* fix indentations
* Make tasks protected
* fix KubernetesTaskRunnerConfig deserialization
* ensure k8s task runner max capacity is Integer.MAX_VALUE
* set job duration as task status duration
* Address pr comments
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Co-authored-by: George Shiqi Wu <george.wu@imply.io>
This PR fixes an issue when using 'auto' encoded LONG typed columns and the 'vectorized' query engine. These columns use a delta based bit-packing mechanism, and errors in the vectorized reader would cause it to incorrectly read column values for some bit sizes (1 through 32 bits). This is a regression caused by #11004, which added the optimized readers to improve performance, so impacts Druid versions 0.22.0+.
While writing the test I finally got sad enough about IndexSpec not having a "builder", so I made one, and switched all the things to use it. Apologies for the noise in this bug fix PR, the only real changes are in VSizeLongSerde, and the tests that have been modified to cover the buggy behavior, VSizeLongSerdeTest and ExpressionVectorSelectorsTest. Everything else is just cleanup of IndexSpec usage.
Hadoop 2 often causes red security scans on Druid distribution because of the dependencies it brings. We want to move away from Hadoop 2 and provide Hadoop 3 distribution available. Switch druid to building with Hadoop 3 by default. Druid will still be compatible with Hadoop 2 and users can build hadoop-2 compatible distribution using hadoop2 profile.
* return task status reported by peon
* Write TaskStatus to file in AbstractTask.cleanUp
* Get TaskStatus from task log
* Fix merge conflicts in AbstractTaskTest
* Add unit tests for TaskLogPusher, TaskLogStreamer, NoopTaskLogs to satisfy code coverage
* Add license headerss
* Fix style
* Remove unknown exception declarations
* Make the tasks run with only a single directory
There was a change that tried to get indexing to run on multiple disks
It made a bunch of changes to how tasks run, effectively hiding the
"safe" directory for tasks to write files into from the task code itself
making it extremely difficult to do anything correctly inside of a task.
This change reverts those changes inside of the tasks and makes it so that
only the task runners are the ones that make decisions about which
mount points should be used for storing task-related files.
It adds the config druid.worker.baseTaskDirs which can be used by the
task runners to know which directories they should schedule tasks inside of.
The TaskConfig remains the authoritative source of configuration for where
and how an individual task should be operating.
* Always use file sizes when determining batch ingest splits.
Main changes:
1) Update CloudObjectInputSource and its subclasses (S3, GCS,
Azure, Aliyun OSS) to use SplitHintSpecs in all cases. Previously, they
were only used for prefixes, not uris or objects.
2) Update ExternalInputSpecSlicer (MSQ) to consider file size. Previously,
file size was ignored; all files were treated as equal weight when
determining splits.
A side effect of these changes is that we'll make additional network
calls to find the sizes of objects when users specify URIs or objects
as opposed to prefixes. IMO, this is worth it because it's the only way
to respect the user's split hint and task assignment settings.
Secondary changes:
1) S3, Aliyun OSS: Use getObjectMetadata instead of listObjects to get
metadata for a single object. This is a simpler call that is also
expected to be less expensive.
2) Azure: Fix a bug where getBlobLength did not populate blob
reference attributes, and therefore would not actually retrieve the
blob length.
3) MSQ: Align dynamic slicing logic between ExternalInputSpecSlicer and
TableInputSpecSlicer.
4) MSQ: Adjust WorkerInputs to ensure there is always at least one
worker, even if it has a nil slice.
* Add msqCompatible to testGroupByWithImpossibleTimeFilter.
* Fix tests.
* Add additional tests.
* Remove unused stuff.
* Remove more unused stuff.
* Adjust thresholds.
* Remove irrelevant test.
* Fix comments.
* Fix bug.
* Updates.
With the KubernetesTaskRunner, if a task is manually shutdown via the web console while running or the corresponding k8s job is manually deleted, the thread responsible for overseeing the task gets stuck in a loop because the fabric8 client sends one event to it that the job is null when the job is deleted, but this doesn't pass the condition.
This means that the thread is stuck waiting on a fabric8 event (the job being successful) that will never come up until maxTaskDuration (default 4 hours). If a user of the extension is trying to use a limited taskqueue maxSize, this can cause problems as the k8s executor pool is unable to pick up additional tasks (since threads are stuck waiting on the old tasks that have already been deleted).
* Hook up PodTemplateTaskAdapter
* Make task adapter TYPE parameters final
* Rename adapters types
* Include specified adapter name in exception message
* Documentation for sidecarSupport deprecation
* Fix order
* Set TASK_ID as environment variable in PodTemplateTaskAdapter (#13969)
* Update docs/development/extensions-contrib/k8s-jobs.md
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Hook up PodTemplateTaskAdapter
* Make task adapter TYPE parameters final
* Rename adapters types
* Include specified adapter name in exception message
* Documentation for sidecarSupport deprecation
* Fix order
* fix spelling errors
---------
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Pod template task adapter
* Use getBaseTaskDirPaths
* Remove unused task from getEnv
* Use Optional.ifPresent() instead of Optional.map()
* Pass absolute path
* Don't pass task to getEnv
* Assert the correct adapter is created
* Javadocs and Comments
* Add exception message to assertions
* Use TaskConfig to get task dir in KubernetesTaskRunner
* Use the first path specified in baseTaskDirPaths instead of deprecated baseTaskDirPath
* Use getBaseTaskDirPaths in generate command
The FiniteFirehoseFactory and InputRowParser classes were deprecated in 0.17.0 (#8823) in favor of InputSource & InputFormat. This PR removes the FiniteFirehoseFactory and all its implementations along with classes solely used by them like Fetcher (Used by PrefetchableTextFilesFirehoseFactory). Refactors classes including tests using FiniteFirehoseFactory to use InputSource instead.
Removing InputRowParser may not be as trivial as many classes that aren't deprecated depends on it (with no alternatives), like EventReceiverFirehoseFactory. Hence FirehoseFactory, EventReceiverFirehoseFactory, and Firehose are marked deprecated.
George Shiqi Wu
YongGang
George Shiqi Wu
Abhishek Agarwal
Clint Wylie
Kashif Faraz
AmatyaAvadhanula
Atul Mohan
Jan Werner
Abhishek Radhakrishnan
Harini Rajendran
zachjsh
imply-cheddar
Nicholas Lippis
minseok
Churro
Tejaswini Bandlamudi
Gian Merlino
Nicholas Lippis