* batch 03 - trig functions
* Apply suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* applying suggestions and corrections
---------
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Round-robin iterator for datasources to kill.
Currently there's a fairness problem in the KillUnusedSegments duty
where the duty consistently selects the same set of datasources as discovered
from the metadata store or dynamic config params. This is a problem especially
when there are multiple unused. In a medium to large cluster, while we can increase
the task slots to increase the likelihood of broader coverage. This patch adds a simple
round-robin iterator to select datasources and has the following properties:
1. Starts with an initial random cursor position in an ordered list of candidates.
2. Consecutive {@code next()} iterations from {@link #getIterator()} are guaranteed to be deterministic
unless the set of candidates change when {@link #updateCandidates(Set)} is called.
3. Guarantees that no duplicate candidates are returned in two consecutive {@code next()} iterations.
* Renames in RoundRobinIteratorTest.
* Address review comments.
1. Clarify javadocs on the ordered list. Also flesh out the details a bit more.
2. Rename the test hooks to make intent clearer and fix typo.
3. Add NotThreadSafe annotation.
4. Remove one potentially noisy log that's in the path of iteration.
* Add null check to input candidates.
* More commentary.
* Addres review feedback: downgrade some new info logs to debug; invert condition.
Remove redundant comments.
Remove rendundant variable tracking.
* CircularList adjustments.
* Updates to CircularList and cleanup RoundRobinInterator.
* One more case and add more tests.
* Make advanceCursor private for now.
* Review comments.
* Coerce COMPLEX to number in numeric aggregators.
PR #15371 eliminated ObjectColumnSelector's built-in implementations of
numeric methods, which had been marked deprecated.
However, some complex types, like SpectatorHistogram, can be successfully coerced
to number. The documentation for spectator histograms encourages taking advantage of
this by aggregating complex columns with doubleSum and longSum. Currently, this
doesn't work properly for IncrementalIndex, where the behavior relied on those
deprecated ObjectColumnSelector methods.
This patch fixes the behavior by making two changes:
1) SimpleXYZAggregatorFactory (XYZ = type; base class for simple numeric aggregators;
all of these extend NullableNumericAggregatorFactory) use getObject for STRING
and COMPLEX. Previously, getObject was only used for STRING.
2) NullableNumericAggregatorFactory (base class for simple numeric aggregators)
has a new protected method "useGetObject". This allows the base class to
correctly check for null (using getObject or isNull).
The patch also adds a test for SpectatorHistogram + doubleSum + IncrementalIndex.
* Fix tests.
* Remove the special ColumnValueSelector.
* Add test.
* HashJoinEngine: Check for interruptions while walking left cursor.
Previously, the engine only checked for interruptions between emitting
joined rows. In scenarios where large numbers of left rows are skipped
completely (such as a highly selective INNER JOIN) this led to the
join cursor being insufficiently responsive to cancellation.
* Coverage.
Changes the WindowFrame internals / representation a bit; introduces dedicated frametypes for rows and groups which corresponds to the implemented processing methods
* more aggressive cancellation of broker parallel merge, more chill blocking queue timeouts
* wire parallel merge into query cancellation system
* oops
* style
* adjust metrics initialization
* fix timeout, fix cleanup to not block
* javadocs to clarify why cancellation future and gizmo are split
* cancelled -> canceled, simplify QueuePusher since it always takes a ResultBatch, non-static terminal marker to make stuff stop complaining about types, specialize tryOffer to be tryOfferTerminal so it wont be misused, add comments to clarify reason for non-blocking offers that might fail
For aggregators like StringFirst/Last, whose intermediate type isn't the same as the final type, using them in GroupBy, TopN or Timeseries subqueries causes a fallback when maxSubqueryBytes is set. This is because we assume that the finalization is not known, due to which the row signature cannot determine whether to use the intermediate or the final type, and it puts it as null. This PR figures out the finalization from the query context and uses the intermediate or the final type appropriately.
* MSQ window functions: Revamp logic to create separate window stages when empty over() clause is present
* Fix tests
* Revert changes of creating separate stages for empty over clause
* Address review comments
changes:
* moves value column serializer initialization, call to `writeValue` method to `GlobalDictionaryEncodedFieldColumnWriter.writeTo` instead of during `GlobalDictionaryEncodedFieldColumnWriter.addValue`. This shift means these numeric value columns are now done in the per field section that happens after serializing the nested column raw data, so only a single compression buffer and temp file will be needed at a time instead of the total number of nested literal fields present in the column. This should be especially helpful for complicated nested structures with thousands of columns as even those 64k compression buffers can add up pretty quickly to a sizeable chunk of direct memory.
changes:
* removes `druid.indexer.task.batchProcessingMode` in favor of always using `CLOSED_SEGMENT_SINKS` which uses `BatchAppenderator`. This was intended to become the default for native batch, but that was missed so `CLOSED_SEGMENTS` was the default (using `AppenderatorImpl`), however MSQ has been exclusively using `BatchAppenderator` with no problems so it seems safe to just roll it out as the only option for batch ingestion everywhere.
* with `batchProcessingMode` gone, there is no use for `AppenderatorImpl` so it has been removed
* implify `Appenderator` construction since there are only separate stream and batch versions now
* simplify tests since `batchProcessingMode` is gone
This PR aims to check if the complex column being queried aligns with the supported types in the aggregator and aggregator factories, and throws a user-friendly error message if they don't.
* Throw exception if DISTINCT used with window functions aggregate call
* Improve error message when unsupported aggregations are used with window functions
Fixes#16766
Change log level from INFO to DEBUG when processing an empty user map
during polling. An empty user map is a normal situation for some
authenticators (e.g. LDAP) and polling is frequent (1 minute by
default.)
changes:
* removed `Firehose` and `FirehoseFactory` and remaining implementations which were mostly no longer used after #16602
* Moved `IngestSegmentFirehose` which was still used internally by Hadoop ingestion to `DatasourceRecordReader.SegmentReader`
* Rename `SQLFirehoseFactoryDatabaseConnector` to `SQLInputSourceDatabaseConnector` and similar renames for sub-classes
* Moved anything remaining in a 'firehose' package somewhere else
* Clean up docs on firehose stuff
Description:
Overlord guice dependencies are currently a little difficult to plug into.
This was encountered while working on a separate PR where a class needed to depend
on `TaskMaster.getTaskQueue()` to query some task related info but this class itself
needs to be a dependency of `TaskMaster` so that it can be registered to the leader lifecycle.
The approach taken here is to simply decouple the leadership lifecycle of the overlord from
manipulation or querying of its state.
Changes:
- No functional change
- Add new class `DruidOverlord` to contain leadership logic after the model of `DruidCoordinator`
- The new class `DruidOverlord` should not be a dependency of any class with the exception of
REST endpoint `*Resource` classes.
- All classes that need to listen to leadership changes must be a dependency of `DruidOverlord`
so that they can be registered to the leadership lifecycle.
- Move all querying logic from `OverlordResource` to `TaskQueryTool` so that other classes can
leverage this logic too (required for follow up PR).
- Update tests
* pre upgrade
* did the upgrade
* update snapshots
* fix BP5 issues
* update licenses
* fix more depication warnings
* use segmented control
* updat snapshots
* convert to fake local time
* preload icons before tests
* update e2e tests
* Update web-console/src/components/segment-timeline/segment-timeline.tsx
Co-authored-by: John Gozde <john@gozde.ca>
* Update web-console/src/components/segment-timeline/segment-timeline.tsx
Co-authored-by: John Gozde <john@gozde.ca>
* update e2e test selector
* direct import date-fns
---------
Co-authored-by: John Gozde <john@gozde.ca>
* updating first batch of numeric functions
* First batch of functions
* addressing first few comments
* alphabetize list
* draft with suggestions applied
* minor discrepency expr -> <NUMERIC>
* changed raises to calculates
* Update docs/querying/sql-functions.md
* switch to underscore
* changed to exp(1) to match slack message
* adding html text for trademark symbol to .spelling
* fixed discrepancy between description and example
---------
Co-authored-by: Benedict Jin <asdf2014@apache.org>
* remove __time from min max query shortcut
* fix scrolling in retention rules dialog
* actions menus should have titles
* change term
* correctly name sort/shuffle
Changes:
- Do not hold a reference to `TaskQueue` in `TaskStorageQueryAdapter`
- Use `TaskStorage` instead of `TaskStorageQueryAdapter` in `IndexerMetadataStorageAdapter`
- Rename `TaskStorageQueryAdapter` to `TaskQueryTool`
- Fix newly added task actions `RetrieveUpgradedFromSegmentIds` and `RetrieveUpgradedToSegmentIds`
by removing `isAudited` method.
Description:
Task action audit logging was first deprecated and disabled by default in Druid 0.13, #6368.
As called out in the original discussion #5859, there are several drawbacks to persisting task action audit logs.
- Only usage of the task audit logs is to serve the API `/indexer/v1/task/{taskId}/segments`
which returns the list of segments created by a task.
- The use case is really narrow and no prod clusters really use this information.
- There can be better ways of obtaining this information, such as the metric
`segment/added/bytes` which reports both the segment ID and task ID
when a segment is committed by a task. We could also include committed segment IDs in task reports.
- A task persisting several segments would bloat up the audit logs table putting unnecessary strain
on metadata storage.
Changes:
- Remove `TaskAuditLogConfig`
- Remove method `TaskAction.isAudited()`. No task action is audited anymore.
- Remove `SegmentInsertAction` as it is not used anymore. `SegmentTransactionalInsertAction`
is the new incarnation which has been in use for a while.
- Deprecate `MetadataStorageActionHandler.addLog()` and `getLogs()`. These are not used anymore
but need to be retained for backward compatibility of extensions.
- Do not create `druid_taskLog` metadata table anymore.
* #16717 defer provider instatiation
* add license header
* fix style, ignore new class in jacoco as it is still initialization code
---------
Co-authored-by: Alberto Lago Alvarado <albl@sitecore.net>
Changes:
- Break `NewestSegmentFirstIterator` into two parts
- `DatasourceCompactibleSegmentIterator` - this contains all the code from `NewestSegmentFirstIterator`
but now handles a single datasource and allows a priority to be specified
- `PriorityBasedCompactionSegmentIterator` - contains separate iterator for each datasource and
combines the results into a single queue to be used by a compaction search policy
- Update `NewestSegmentFirstPolicy` to use the above new classes
- Cleanup `CompactionStatistics` and `AutoCompactionSnapshot`
- Cleanup `CompactSegments`
- Remove unused methods from `Tasks`
- Remove unneeded `TasksTest`
- Move tests from `NewestSegmentFirstIteratorTest` to `CompactionStatusTest`
and `DatasourceCompactibleSegmentIteratorTest`
Edgar Melendrez
Charles Smith
Abhishek Radhakrishnan
Sree Charan Manamala
Laksh Singla
Clint Wylie
Gian Merlino
Rohan Garg
Zoltan Haindrich
Edgar Melendrez
John Gozde
Akshat Jain
Vadim Ogievetsky
Sébastien
317brian
George Shiqi Wu
dave-mccowan
Kashif Faraz
Alberic Liu
trompa
Adithya Chakilam
AmatyaAvadhanula