Changes:
- Make ServiceMetricEvent.Builder extend ServiceEventBuilder<ServiceMetricEvent>
and thus convert it to a plain builder rather than a builder of builder.
- Add methods setCreatedTime , setMetricAndValue to the builder
There is a current issue due to inconsistent metadata between worker and controller in MSQ. A controller can receive one set of segments, which are then marked as unused by, say, a compaction job. The worker would be unable to get the segment information as MetadataResource.
Currently, Druid is using Guava 16.0.1 version. This upgrade to 31.1-jre fixes the following issues.
CVE-2018-10237 (Unbounded memory allocation in Google Guava 11.0 through 24.x before 24.1.1 allows remote attackers to conduct denial of service attacks against servers that depend on this library and deserialize attacker-provided data because the AtomicDoubleArray class (when serialized with Java serialization) and the CompoundOrdering class (when serialized with GWT serialization) perform eager allocation without appropriate checks on what a client has sent and whether the data size is reasonable). We don't use Java or GWT serializations. Despite being false positive they're causing red security scans on Druid distribution.
Latest version of google-client-api is incompatible with the existing Guava version. This PR unblocks Update google client apis to latest version #14414
This PR adds a way to store the topic name in a column. Such a column can be used to distinguish messages coming from different topics in multi-topic ingestion.
Motivation:
- There is no usage of the `SegmentTransactionInsertAction` which passes a
non-null non-empty value of `segmentsToBeDropped`.
- This is not really needed either as overshadowed segments are marked as unused
by the Coordinator and need not be done in the same transaction as committing segments.
- It will also help simplify the changes being made in #14407
Changes:
- Remove `segmentsToBeDropped` from the task action and all intermediate methods
- Remove related tests which are not needed anymore
* Add supervisor /resetOffsets API.
- Add a new endpoint /druid/indexer/v1/supervisor/<supervisorId>/resetOffsets
which accepts DataSourceMetadata as a body parameter.
- Update logs, unit tests and docs.
* Add a new interface method for backwards compatibility.
* Rename
* Adjust tests and javadocs.
* Use CoreInjectorBuilder instead of deprecated makeInjectorWithModules
* UT fix
* Doc updates.
* remove extraneous debugging logs.
* Remove the boolean setting; only ResetHandle() and resetInternal()
* Relax constraints and add a new ResetOffsetsNotice; cleanup old logic.
* A separate ResetOffsetsNotice and some cleanup.
* Minor cleanup
* Add a check & test to verify that sequence numbers are only of type SeekableStreamEndSequenceNumbers
* Add unit tests for the no op implementations for test coverage
* CodeQL fix
* checkstyle from merge conflict
* Doc changes
* DOCUSAURUS code tabs fix. Thanks, Brian!
In this PR, I have gotten rid of multiTopic parameter and instead added a topicPattern parameter. Kafka supervisor will pass topicPattern or topic as the stream name to the core ingestion engine. There is validation to ensure that only one of topic or topicPattern will be set. This new setting is easier to understand than overloading the topic field that earlier could be interpreted differently depending on the value of some other field.
This PR adds support to read from multiple Kafka topics in the same supervisor. A multi-topic ingestion can be useful in scenarios where a cluster admin has no control over input streams. Different teams in an org may create different input topics that they can write the data to. However, the cluster admin wants all this data to be queryable in one data source.
* Update to Calcite 1.35.0
* Update from.ftl for Calcite 1.35.0.
* Fixed tests in Calcite upgrade by doing the following:
1. Added a new rule, CoreRules.PROJECT_FILTER_TRANSPOSE_WHOLE_PROJECT_EXPRESSIONS, to Base rules
2. Refactored the CorrelateUnnestRule
3. Updated CorrelateUnnestRel accordingly
4. Fixed a case with selector filters on the left where Calcite was eliding the virtual column
5. Additional test cases for fixes in 2,3,4
6. Update to StringListAggregator to fail a query if separators are not propagated appropriately
* Refactored for testcases to pass after the upgrade, introduced 2 new data sources for handling filters and select projects
* Added a literalSqlAggregator as the upgraded Calcite involved changes to subquery remove rule. This corrected plans for 2 queries with joins and subqueries by replacing an useless literal dimension with a post agg. Additionally a test with COUNT DISTINCT and FILTER which was failing with Calcite 1.21 is added here which passes with 1.35
* Updated to latest avatica and updated code as SqlUnknownTimeStamp is now used in Calcite which needs to be resolved to a timestamp literal
* Added a wrapper segment ref to use for unnest and filter segment reference
The Azure connector is introduced and MSQ's fault tolerance and durable storage can now be used with Microsoft Azure's blob storage. Also, the results of newly introduced queries from deep storage can now store and fetch the results from Azure's blob storage.
* Rolling supervior task publishing
* add an option for number of task groups to roll over
* better
* remove docs
* oops
* checkstyle
* wip test
* undo partial test change
* remove incomplete test
* Minimize PostAggregator computations
Since a change back in 2014, the topN query has been computing
all PostAggregators on all intermediate responses from leaf nodes
to brokers. This generates significant slow downs for queries
with relatively expensive PostAggregators. This change rewrites
the query that is pushed down to only have the minimal set of
PostAggregators such that it is impossible for downstream
processing to do too much work. The final PostAggregators are
applied at the very end.
* MSQ WorkerImpl: Ignore ServiceClosedException on postCounters.
A race can happen where postCounters is in flight while the controller
goes offline. When this happens, we should ignore the ServiceClosedException
and continue without posting counters.
* Fix style and logic.
* Remove chatAsync parameter, so chat is always async.
chatAsync has been made default in Druid 26. I have seen good
battle-testing of it in production, and am comfortable removing the
older sync client.
This was the last remaining usage of IndexTaskClient, so this patch
deletes all that stuff too.
* Remove unthrown exception.
* Remove unthrown exception.
* No more TimeoutException.
This PR has fixes a bug in the SqlStatementAPI where if the task is not found on the overlord, the response status is 500.
This changes the response to invalid input since the queryID passed is not valid.
* Save a metadata call when reading files from CloudObjectInputSource.
The call to createSplits(inputFormat, null) in formattableReader would
use the default split hint spec, MaxSizeSplitHintSpec, which makes
getObjectMetadata calls in order to compute its splits. This isn't
necessary; we're just trying to unpack the files inside the input
source.
To fix this, use FilePerSplitHintSpec to extract files without any
funny business.
* Adjust call.
* Fix constant.
* Test coverage.
* Frames support for string arrays that are null.
The row format represents null arrays as 0x0001, which older readers
would interpret as an empty array. This provides compatibility with
older readers, which is useful during updates.
The column format represents null arrays by writing -(actual length) - 1
instead of the length, and using FrameColumnWriters.TYPE_STRING_ARRAY for
the type code for string arrays generally. Older readers will report this
as an unrecognized type code. Column format is only used by the operator
query, which is currently experimental, so the impact isn't too severe.
* Remove unused import.
* Return Object[] instead of List from frame array selectors.
Update MSQSelectTest and MSQInsertTest to reflect the fact that null
arrays are possible.
Add a bunch of javadocs to object selectors describing expected behavior,
including the requirement that array selectors return Object[].
* update test case.
* Update test cases.
* allow for batched delete of segments instead of deleting segment data one by one
create new batchdelete method in datasegment killer that has default functionality
of iterating through all segments and calling delete on them. This will enable
a slow rollout of other deepstorage implementations to move to a batched delete
on their own time
* cleanup batchdelete segments
* batch delete with the omni data deleter
cleaned up code
just need to add tests and docs for this functionality
* update java doc to explain how it will try to use batch if function is overwritten
* rename killBatch to kill
add unit tests
* add omniDataSegmentKillerTest for deleting multiple segments at a time. fix checkstyle
* explain test peculiarity better
* clean up batch kill in s3.
* remove unused return value. cleanup comments and fix checkstyle
* default to batch delete. more specific java docs. list segments that couldn't be deleted
if there was a client error or server error
* simplify error handling
* add tests where an exception is thrown when killing multiple s3 segments
* add test for failing to delete two calls with the s3 client
* fix javadoc for kill(List<DataSegment> segments) clean up tests remove feature flag
* fix typo in javadocs
* fix test failure
* fix checkstyle and improve tests
* fix intellij inspections issues
* address comments, make delete multiple segments not assume same bucket
* fix test errors
* better grammar and punctuation. fix test. and better logging for exception
* remove unused code
* avoid extra arraylist instantiation
* fix broken test
* fix broken test
* fix tests to use assert.throws
* Merge core CoordinatorClient with MSQ CoordinatorServiceClient.
Continuing the work from #12696, this patch merges the MSQ
CoordinatorServiceClient into the core CoordinatorClient, yielding a single
interface that serves both needs and is based on the ServiceClient RPC
system rather than DruidLeaderClient.
Also removes the backwards-compatibility code for the handoff API in
CoordinatorBasedSegmentHandoffNotifier, because the new API was added
in 0.14.0. That's long enough ago that we don't need backwards
compatibility for rolling updates.
* Fixups.
* Trigger GHA.
* Remove unnecessary retrying in DruidInputSource. Add "about an hour"
retry policy and h
* EasyMock
* Use OverlordClient for all Overlord RPCs.
Continuing the work from #12696, this patch removes HttpIndexingServiceClient
and the IndexingService flavor of DruidLeaderClient completely. All remaining
usages are migrated to OverlordClient.
Supporting changes include:
1) Add a variety of methods to OverlordClient.
2) Update MetadataTaskStorage to skip the complete-task lookup when
the caller requests zero completed tasks. This helps performance of
the "get active tasks" APIs, which don't want to see complete ones.
* Use less forbidden APIs.
* Fixes from CI.
* Add test coverage.
* Two more tests.
* Fix test.
* Updates from CR.
* Remove unthrown exceptions.
* Refactor to improve testability and test coverage.
* Add isNil tests.
* Remove unnecessary "deserialize" methods.
* Add ingest/input/bytes metric and Kafka consumer metrics.
New metrics:
1) ingest/input/bytes. Equivalent to processedBytes in the task reports.
2) kafka/consumer/bytesConsumed: Equivalent to the Kafka consumer
metric "bytes-consumed-total". Only emitted for Kafka tasks.
3) kafka/consumer/recordsConsumed: Equivalent to the Kafka consumer
metric "records-consumed-total". Only emitted for Kafka tasks.
* Fix anchor.
* Fix KafkaConsumerMonitor.
* Interface updates.
* Doc changes.
* Update indexing-service/src/main/java/org/apache/druid/indexing/seekablestream/SeekableStreamIndexTask.java
Co-authored-by: Benedict Jin <asdf2014@apache.org>
---------
Co-authored-by: Benedict Jin <asdf2014@apache.org>
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.
* Change default handoffConditionTimeout to 15 minutes.
Most of the time, when handoff is taking this long, it's because something
is preventing Historicals from loading new data. In this case, we have
two choices:
1) Stop making progress on ingestion, wait for Historicals to load stuff,
and keep the waiting-for-handoff segments available on realtime tasks.
(handoffConditionTimeout = 0, the current default)
2) Continue making progress on ingestion, by exiting the realtime tasks
that were waiting for handoff. Once the Historicals get their act
together, the segments will be loaded, as they are still there on
deep storage. They will just not be continuously available.
(handoffConditionTimeout > 0)
I believe most users would prefer [2], because [1] risks ingestion falling
behind the stream, which causes many other problems. It can cause data loss
if the stream ages-out data before we have a chance to ingest it.
Due to the way tuningConfigs are serialized -- defaults are baked into the
serialized form that is written to the database -- this default change will
not change anyone's existing supervisors. It will take effect for newly
created supervisors.
* Fix tests.
* Update docs/development/extensions-core/kafka-supervisor-reference.md
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
* Update docs/development/extensions-core/kinesis-ingestion.md
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
---------
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
MSQ engine returns correct error codes for invalid user inputs in the query context. Also, using DruidExceptions for MSQ related errors happening in the Broker with improved error messages.
The errorCode of this fault when serialized over the wire was being
set to the name of the class `InsertTimeOutOfBoundsFault` instead of
the CODE `InsertTimeOutOfBounds`. All other faults' errorCodes are
serialized as the respective Fault's code, so making consistent here
as well.
* Fixing an issue in sequential merge where workers without any partial key statistics would get stuck because controller did not change the worker state.
* Removing empty check
* Adding IT for MSQ sequential bug fix.
* Add ZooKeeper connection state alerts and metrics.
- New metric "zk/connected" is an indicator showing 1 when connected,
0 when disconnected.
- New metric "zk/disconnected/time" measures time spent disconnected.
- New alert when Curator connection state enters LOST or SUSPENDED.
* Use right GuardedBy.
* Test fixes, coverage.
* Adjustment.
* Fix tests.
* Fix ITs.
* Improved injection.
* Adjust metric name, add tests.
Kashif Faraz
Karan Kumar
Laksh Singla
Clint Wylie
Adarsh Sanjeev
Atul Mohan
Zoltan Haindrich
Tejaswini Bandlamudi
Abhishek Agarwal
Abhishek Radhakrishnan
Rishabh Singh
Soumyava
zachjsh
Suneet Saldanha
George Shiqi Wu
imply-cheddar
YongGang
Gian Merlino
Pranav
TSFenwick
AmatyaAvadhanula