Changes:
- Fix capacity response in mm-less ingestion.
- Add field usedClusterCapacity to the GET /totalWorkerCapacity response.
This API should be used to get the total ingestion capacity on the overlord.
- Remove method `isK8sTaskRunner` from interface `TaskRunner`
Changes:
- Determine the default value of balancerComputeThreads based on number of
coordinator cpus rather than number of segments. Even if the number of segments
is low and we create more balancer threads, it doesn't hurt the system as threads
would mostly be idle.
- Remove unused field from SegmentLoadQueueManager
Expected values:
- Clusters with ~1M segments typically work with Coordinators having 16 cores or more.
This would give us 8 balancer threads, which is the same as the current maximum.
- On small clusters, even a single thread is enough to do the required balancing work.
Suppress CVEs from dependencies with no available fix or false positives
hadoop-annotations: CVE-2022-25168, CVE-2021-33036
hadoop-client-runtime: CVE-2023-1370, CVE-2023-37475
okio: CVE-2023-3635
Upgrade grpc version to fix CVE-2023-33953
This patch fixes a few issues toward #14858
1. some phony classes were added to enable maven to track the compilation of those classes
2. cyclonedx 2.7.9 seem to handle incremental compilation better; it had a PR relating to that
3. needed to update root pom to 25
4. update antlr to 4.5.3 older one didn't really worked incrementally; 4.5.3 works much better
### Description
This change enables the `KillUnusedSegments` coordinator duty to be scheduled continuously. Things that prevented this, or made this difficult before were the following:
1. If scheduled at fast enough rate, the duty would find the same intervals to kill for the same datasources, while kill tasks submitted for those same datasources and intervals were already underway, thus wasting task slots on duplicated work.
2. The task resources used by auto kill were previously unbounded. Each duty run period, if unused
segments were found for any datasource, a kill task would be submitted to kill them.
This pr solves for both of these issues:
1. The duty keeps track of the end time of the last interval found when killing unused segments for each datasource, in a in memory map. The end time for each datasource, if found, is used as the start time lower bound, when searching for unused intervals for that same datasource. Each duty run, we remove any datasource keys from this map that are no longer found to match datasources in the system, or in whitelist, and also remove a datasource entry, if there is found to be no unused segments for the datasource, which happens when we fail to find an interval which includes unused segments. Removing the datasource entry from the map, allows for searching for unusedSegments in the datasource from the beginning of time once again
2. The unbounded task resource usage can be mitigated with coordinator dynamic config added as part of ba957a9b97
Operators can configure continous auto kill by providing coordinator runtime properties similar to the following:
```
druid.coordinator.period.indexingPeriod=PT60S
druid.coordinator.kill.period=PT60S
```
And providing sensible limits to the killTask usage via coordinator dynamic properties.
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.
Motivation:
- Clean up `DruidCoordinator` and move methods to classes where they are most relevant
Changes:
- No functional change
- Add duty `PrepareBalancerAndLoadQueues` to replace `UpdateCoordinatorState`
- Move map of `LoadQueuePeon` from `DruidCoordinator` to `LoadQueueTaskMaster`
- Make `BalancerStrategyFactory` an abstract class and keep the balancer executor here
- Move reporting of used segment stats and historical capacity stats from
`CollectSegmentAndServerStats` to `PrepareBalancerAndLoadQueues`
- Move reporting of unavailable and under-replicated segment stats from
`CollectSegmentAndServerStats` to `UpdateReplicationStatus` duty
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
Changes:
- Move logic of `NewestSegmentFirstIterator.needsCompaction` to `CompactionStatus`
to improve testability and readability
- Capture the list of checks performed to determine if compaction is needed in a readable
manner in `CompactionStatus.CHECKS`
- Make `CompactionSegmentIterator` iterate over instances of `SegmentsToCompact`
instead of `List<DataSegment>`. This allows use of the `umbrellaInterval` later.
- Replace usages of `QueueEntry` with `SegmentsToCompact`
- Move `SegmentsToCompact` out of `NewestSegmentFirstIterator`
- Simplify `CompactionStatistics`
- Reduce level of less important logs to debug
- No change made to tests to ensure correctness
Changes:
- Use separate executor for every duty group
- This change is thread-safe as every duty group uses its own copy of
`DruidCoordinatorRuntimeParams` and does not share any other mutable instances
with other duty groups.
- With the exception of `HistoricalManagementDuties`, duty groups are typically not
very compute intensive and mostly perform database or HTTP I/O. So, coordinator
resources would still mostly be available for `HistoricalManagementDuties`.
Follow up changes to #12599
Changes:
- Rename column `used_flag_last_updated` to `used_status_last_updated`
- Remove new CLI tool `UpdateTables`.
- We already have a `CreateTables` with similar functionality, which should be able to
handle update cases too.
- Any user running the cluster for the first time should either just have `connector.createTables`
enabled or run `CreateTables` which should create tables at the latest version.
- For instance, the `UpdateTables` tool would be inadequate when a new metadata table has
been added to Druid, and users would have to run `CreateTables` anyway.
- Remove `upgrade-prep.md` and include that info in `metadata-init.md`.
- Fix log messages to adhere to Druid style
- Use lambdas
* Add new configurable buffer period to create gap between mark unused and kill of segment
* Changes after testing
* fixes and improvements
* changes after initial self review
* self review changes
* update sql statement that was lacking last_used
* shore up some code in SqlMetadataConnector after self review
* fix derby compatibility and improve testing/docs
* fix checkstyle violations
* Fixes post merge with master
* add some unit tests to improve coverage
* ignore test coverage on new UpdateTools cli tool
* another attempt to ignore UpdateTables in coverage check
* change column name to used_flag_last_updated
* fix a method signature after column name switch
* update docs spelling
* Update spelling dictionary
* Fixing up docs/spelling and integrating altering tasks table with my alteration code
* Update NULL values for used_flag_last_updated in the background
* Remove logic to allow segs with null used_flag_last_updated to be killed regardless of bufferPeriod
* remove unneeded things now that the new column is automatically updated
* Test new background row updater method
* fix broken tests
* fix create table statement
* cleanup DDL formatting
* Revert adding columns to entry table by default
* fix compilation issues after merge with master
* discovered and fixed metastore inserts that were breaking integration tests
* fixup forgotten insert by using pattern of sharing now timestamp across columns
* fix issue introduced by merge
* fixup after merge with master
* add some directions to docs in the case of segment table validation issues
* 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!
Changes:
- No change in behaviour if `smartSegmentLoading` is disabled
- If `smartSegmentLoading` is enabled
- Compute `balancerComputeThreads` based on `numUsedSegments`
- Compute `maxSegmentsToMove` based on `balancerComputeThreads`
- Compute `segmentsToMoveToFixSkew` based on usage skew
- Compute `segmentsToMove = Math.min(maxSegmentsToMove, segmentsToMoveToFixSkew)`
Limits:
- 1 <= `balancerComputeThreads` <= 8
- `maxSegmentsToMove` <= 20% of total segments
- `minSegmentsToMove` = 0.15% of total segments
George Shiqi Wu
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