This patch re-uses timeBoundaryInspector for each cursor holder, which
enables caching of minDataTimestamp and maxDataTimestamp.
Fixes a performance regression introduced in #16533, where these fields
stopped being cached across cursors. Prior to that patch, they were
cached in the QueryableIndexStorageAdapter.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
changes:
* fix issue when merging projections from multiple-incremental persists which was hoping that some 'dim conversion' buffers were not closed, but they already were (by the merging iterator). fix involves selectively persisting these conversion buffers to temp files in the segment write out directory and mapping them and tying them to the segment level closer so that they are available after the lifetime of the parent merger
* modify auto column serializers to use segment write out directory for temp files instead of java.io.tmpdir
* fix queryable index projection to not put the time-like column as a dimension, instead only adding it as __time
* use smoosh for temp files so can safely write any Serializer to a temp smoosh
* Run JDK 21 workflows with 21.0.4.
To work around #17429, run our JDK 21 workflows with
version 21.0.4. It does not appear to have this problem.
* Undo changes in standard-its.yml
* Add comments.
---------
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
Co-authored-by: Zoltan Haindrich <kirk@rxd.hu>
The timeout handler should fire if the response has not been handled yet
(i.e. if responseResolved was previously false). However, it erroneously
fires only if the response *was* handled. This causes HTTP 500 errors if
the timeout actually does fire. The timeout is 30 seconds, which can be
hit during pipelined queries, if an earlier stage of the query hasn't
produced its first frame within 30 seconds.
This fixes a regression introduced in #17140.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
Follow up to #17214, adds implementations for substituteCombiningFactory so that more
datasketches aggs can match projections, along with some projections tests for datasketches.
Co-authored-by: Clint Wylie <cwylie@apache.org>
* MSQ: Use leaf worker count for stages that have any leaf inputs. (#17312)
(cherry picked from commit b27712933e)
* MSQ: Call "onQueryComplete" after the query is closed. (#17313)
(cherry picked from commit 4092f3fe47)
* Dart: Only use historicals as workers. (#17319)
(cherry picked from commit 074944e02c)
---------
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* BaseWorkerClientImpl: Don't attempt to recover from a closed channel.
This patch introduces an exception type "ChannelClosedForWritesException",
which allows the BaseWorkerClientImpl to avoid retrying when the local
channel has been closed. This can happen in cases of cancellation.
* Add some test coverage.
* wip
* Add test coverage.
* Style.
(cherry picked from commit 4dc5942dab)
1) ControllerQueryKernel: Update readyToReadResults to acknowledge that sorting stages can
go directly from READING_INPUT to RESULTS_READY.
2) WorkerStageKernel: Ignore RESULTS_COMPLETE if work is already finished, which can happen
if the transition to FINISHED comes early due to a downstream LIMIT.
(cherry picked from commit 654e0b444b)
[Backport] MSQ: Wake up the main controller thread on workerError. (#17075) #17304
This isn't necessary when using MSQWorkerTaskLauncher as the WorkerManager
implementation, because in that case, task failure also wakes up the
main thread. However, when using workers that are not task-based, we don't
want to rely on the WorkerManager for this.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
Prior to this patch, the workerId() method did not actually return
the worker ID. It returned some other string that had similar information,
but was different.
This caused the /druid/dart-worker/workers API, to return an internal
server error. The API is useful for debugging, although it is not used
during actual queries.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* QueryResource: Don't close JSON content on error.
Following similar issues fixed in #11685 and #15880, this patch fixes
a bug where QueryResource would write a closing array marker if it
encountered an exception after starting to push results. This makes it
difficult for callers to detect errors.
The prior patches didn't catch this problem because QueryResource uses
the ObjectMapper in a unique way, through writeValuesAsArray, which
doesn't respect the global AUTO_CLOSE_JSON_CONTENT setting.
* Fix usage of customized ObjectMappers.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
Fix the logic for usage of segment descriptors from queries in SinkQuerySegmentWalker when there are upgraded segments as a result of concurrent replace.
Concurrent append and replace:
With the introduction of concurrent append and replace, for a given interval:
The same sink can correspond to a base segment V0_x0, and have multiple mappings to higher versions with distinct partition numbers such as V1_x1.... Vn_xn.
The initial segment allocation can happen on version V0, but there can be several allocations during the lifecycle of a task which can have different versions spanning from V0 to Vn.
Changes:
Maintain a new timeline of (An overshadowable holding a SegmentDescriptor)
Every segment allocation of version upgrade adds the latest segment descriptor to this timeline.
Iterate this timeline instead of the sinkTimeline to get the segment descriptors in getQueryRunnerForIntervals
Also maintain a mapping of the upgraded segment to its base segment.
When a sink is needed to process the query, find the base segment corresponding to a given descriptor, and then use the sinkTimeline to find its chunk.
* from start to step 3 of Ingest data using Theta sketche
* updated upto "Query the Theta sketch column"
* fixed sentence
* another typo
* using sql ingestion instead of batch-sql
* waiting for explanations on DS_THETA
* Revert "using sql ingestion instead of batch-sql"
This reverts commit b95fcb9b32.
* Revert "using sql ingestion instead of batch-sql"
This reverts commit b95fcb9b32.
* just copy and pasting to where I was
* updated tutorial
* fixing images, and removing unused
* slightly updating explanatio
* Update docs/tutorials/tutorial-sketches-theta.md
* Apply suggestions from code review
* addressing comments in review
* made filter clause consitent with other instances
* Apply suggestions from code review
---------
Co-authored-by: Edgar Melendrez <evmelendrez@gmail.com>
Co-authored-by: Benedict Jin <asdf2014@apache.org>
Co-authored-by: Victoria Lim <vtlim@users.noreply.github.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* draft update to known issues
* Update known issues
Remove addressed known issues. Clarify the issue with SELECT * queries.
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Fixes#16587
Streaming ingestion tasks operate by allocating segments before ingesting rows.
These allocations happen across replicas which may send different requests but
must get the same segment id for a given (datasource, interval, version, sequenceName)
across replicas.
This patch fixes the bug by ignoring the previousSegmentId when skipLineageCheck is true.
Co-authored-by: AmatyaAvadhanula <amatya.avadhanula@imply.io>
The patch makes the following changes:
1. Fixes a bug causing compaction to fail on array, complex, and other non-primitive-type columns
2. Updates compaction status check to be conscious of partition dimensions when comparing dimension ordering.
3. Ensures only string columns are specified as partition dimensions
4. Ensures `rollup` is true if and only if metricsSpec is non-empty
5. Ensures disjoint intervals aren't submitted for compaction
6. Adds `compactionReason` to compaction task context.
(cherry picked from commit 7e35e50052)
changes:
adds ExpressionProcessing.allowVectorizeFallback() and ExpressionProcessingConfig.allowVectorizeFallback(), defaulting to false until few remaining bugs can be fixed (mostly complex types and some odd interactions with mixed types)
add cannotVectorizeUnlessFallback functions to make it easy to toggle the default of this config, and easy to know what to delete when we remove it in the future
Co-authored-by: Clint Wylie <cwylie@apache.org>
* abstract `IncrementalIndex` cursor stuff to prepare for using different "views" of the data based on the cursor build spec (#17064)
* abstract `IncrementalIndex` cursor stuff to prepare to allow for possibility of using different "views" of the data based on the cursor build spec
changes:
* introduce `IncrementalIndexRowSelector` interface to capture how `IncrementalIndexCursor` and `IncrementalIndexColumnSelectorFactory` read data
* `IncrementalIndex` implements `IncrementalIndexRowSelector`
* move `FactsHolder` interface to separate file
* other minor refactorings
* add DataSchema.Builder to tidy stuff up a bit (#17065)
* add DataSchema.Builder to tidy stuff up a bit
* fixes
* fixes
* more style fixes
* review stuff
* Projections prototype (#17214)
In a Dart query, all Historicals are given worker IDs, but not all of them
are going to actually be started or receive work orders.
Attempting to send a getCounters or postFinish command to a worker that
never received a work order is not only wasteful, but it causes errors due
to the workers not knowing about that query ID.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* MSQ: Properly report errors that occur when starting up RunWorkOrder. (#17069)
* Dart: Smoother handling of stage early-exit. (#17228)
---------
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* SQL: Use regular filters for time filtering in subqueries. (#17173)
* RunWorkOrder: Account for two simultaneous statistics collectors. (#17216)
* DartTableInputSpecSlicer: Fix for TLS workers. (#17224)
* Upgrade avro - minor version (#17230)
* SuperSorter: Don't set allDone if it's already set. (#17238)
* Decoupled planning: improve join support (#17039)
---------
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
Co-authored-by: Zoltan Haindrich <kirk@rxd.hu>
Clint Wylie
317brian
Jill Osborne
Laksh Singla
Pranav
Abhishek Agarwal
Kashif Faraz
Karan Kumar
Zoltan Haindrich
Gian Merlino
AmatyaAvadhanula
Charles Smith
Vadim Ogievetsky
Vishesh Garg