* Reduce upload buffer size in GoogleTaskLogs.
Use a 1MB upload buffer, rather than the default of 15 MB in the API client. This is
mainly because MMs may upload logs in parallel, and typically have small heaps. The
default-sized 15 MB buffers add up quickly and can cause a MM to run out of memory.
* Make bufferSize a nullable Integer. Add tests.
* Better forced mode indication
* more robust
* Update web-console/src/components/header-bar/header-bar.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/header-bar.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/__snapshots__/restricted-mode.spec.tsx.snap
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/__snapshots__/restricted-mode.spec.tsx.snap
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update web-console/src/components/header-bar/restricted-mode/restricted-mode.tsx
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* reformat
* forced => manual capability detection
* typo
* typo2
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Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Support for exporting msq results to gcs bucket. This is essentially copying the logic of s3 export for gs, originally done by @adarshsanjeev in this PR - #15689
* Allow typedIn to run in replace-with-default mode.
Useful when data servers, like Historicals, are running in replace-with-default
mode and the Broker is running in SQL-compatible mode, which can happen during
a rolling update that is applying a mode change.
* Update error message when topic messages.
Suggest resetting the supervisor when the topic changes instead of changing
the supervisor name which is actually making a new supervisor.
* Update server/src/main/java/org/apache/druid/metadata/IndexerSQLMetadataStorageCoordinator.java
Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
* Cleanup
* Remove log and include oldCommitMetadataFromDb
* Fix test
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Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
The name of the combining filtered aggregator factory should be the same
as the name of the original factory. However, it wasn't the same in the
case where the original factory's name and the original delegate aggregator
were inconsistently named. In this scenario, we should use the name of
the original filtered aggregator, not the name of the original delegate
aggregator.
This PR creates an interface for ImmutableRTree and moved the existing implementation to new class which represent 32 bit implementation (stores coordinate as floats). This PR makes the ImmutableRTree extendable to create higher precision implementation as well (64 bit).
In all spatial bound filters, we accept float as input which might not be accurate in the case of high precision implementation of ImmutableRTree. This PR changed the bound filters to accepts the query bounds as double instead of float and it is backward compatible change as it compares double to existing float values in RTree. Previously it was comparing input float to RTree floats which can cause precision loss, now it is little better as it compares double to float which is still not 100% accurate.
There are no changes in the way that we query spatial dimension today except input bound parsing. There is little improvement in string filter predicate which now parse double strings instead of float and compares double to double which is 100% accurate but string predicate is only called when we dont have spatial index.
With allowing the interface to extend ImmutableRTree, we allow to create high precision (HP) implementation and defines new search strategies to perform HP search Iterable<ImmutableBitmap> search(ImmutableDoubleNode node, Bound bound);
With possible HP implementations, Radius bound filter can not really focus on accuracy, it is calculating Euclidean distance in comparing. As EARTH 🌍 is round and not flat, Euclidean distances are not accurate in geo system. This PR adds new param called 'radiusUnit' which allows you to specify units like meters, km, miles etc. It uses https://en.wikipedia.org/wiki/Haversine_formula to check if given geo point falls inside circle or not. Added a test that generates set of points inside and outside in RadiusBoundTest.
Changes
- No functional changes
- Add method `AbstractBatchIndexTask.buildIngestionStatsReport()` used in several batch tasks
- Add utility method `AbstractBatchIndexTask.addBuildSegmentStatsToReport()`
- Use boolean argument to represent a full report instead of the String `full`
in internal methods. (REST API remains unchanged.)
- Rename `IngestionStatsAndErrorsTaskReportData` to `IngestionStatsAndErrors`
- Clean up some of the methods
This PR aims to introduce Window functions on MSQ by doing the following:
Introduce a Window querykit for handling window queries along with its factory and a processor for window queries
If a window operator is present with a partition by clause, pushes the partition as a shuffle spec of the previous stage
In presence of empty OVER() clause lets all operators loose on a single rac
In presence of no empty OVER() clause, breaks down each window into individual stages
Associated machinery to handle window functions in MSQ
Introduced a separate hidden engine feature WINDOW_LEAF_OPERATOR which is set only for MSQ engine. In presence of this feature, the planner plans without the leaf operators by creating a window query over an inner scan query. In case of native this is set to false and the planner generates the leafOperators
Guardrails around materialization
Comprehensive UTs
WorkerAssignmentStrategy.AUTO was missing a check for maxWorkerCount
in the case where the inputs to a stage are not dynamically sliceable.
A common case here is when the inputs to a stage are other stages.
Changes:
- Handle exceptions in the API and map them to a `Response` object with the appropriate error code.
- Replace `AuthorizationUtils.filterAuthorizedResources()` with `DatasourceResourceFilter`.
The endpoint is annotated consistent with other usages.
- Update `DatasourceResourceFilter` to remove the lambda and update javadocs.
The usages information is self-evident with an IDE.
- Adjust the invalid interval exception message.
- Break up the large unit test `testGetUnusedSegmentsInDataSource()` into smaller unit tests
for each test case. Also, validate the error codes.
* Avoid conversion to String in JsonReader, JsonNodeReader.
These readers were running UTF-8 decode on the provided entity to
convert it to a String, then parsing the String as JSON. The patch
changes them to parse the provided entity's input stream directly.
In order to preserve the nice error messages that include parse errors,
the readers now need to open the entity again on the error path, to
re-read the data. To make this possible, the InputEntity#open contract
is tightened to require the ability to re-open entities, and existing
InputEntity implementations are updated to allow re-opening.
This patch also renames JsonLineReaderBenchmark to JsonInputFormatBenchmark,
updates it to benchmark all three JSON readers, and adds a case that reads
fields out of the parsed row (not just creates it).
* Fixes for static analysis.
* Implement intermediateRowAsString in JsonReader.
* Enhanced JsonInputFormatBenchmark.
Renames JsonLineReaderBenchmark to JsonInputFormatBenchmark, and enhances it to
test various readers (JsonReader, JsonLineReader, JsonNodeReader) as well as
to test with/without field discovery.
This commit allows to use the MV_FILTER_ONLY & MV_FILTER_NONE functions
with a non literal argument.
Currently `select mv_filter_only('mvd_dim', 'array_dim') from 'table'`
returns a `Unhandled Query Planning Failure`
This is being tackled and also considered for the cases where the `array_dim`
having null & empty values.
Changed classes:
* `MultiValueStringOperatorConversions`
* `ApplyFunction`
* `CalciteMultiValueStringQueryTest`
* Differentiate null and empty lists of segment IDs and versions.
Treat them differently so the. Segment IDs and versions can be An empty list,
in which case, the queries should just not return anything. Versions are optional, so
they can be null, which just indicates nothing, so the queries should return segments with
all possible versions. Segment IDs cannot be null as indicated by the absence of @Nullable
annotation.
* Update javadocs and add empty versions test to kill task.
* Add test for RetrieveSegmentsActions as well.
* Rewrite exotic LAST_VALUE/FIRST_VALUE to self-reference.
* rewrite `LAST_VALUE(x) OVER (ORDER BY y)` to `LAG(x,0) OVER (ORDER BY y)`
* not directly to `x` because some queries get unplannable that way
* restrict `NTILE` from framing - as its not supported
* add test to ensure that all of the `KNOWN_WINDOW_FNS`'s framing is accounted for
* checkstyle/etc
* add test
* apidoc
* add assume to avoid MSQ fail
Changes:
- Use error code `internalServerError` for failures of this type
- Remove the error code argument from `InternalServerError.exception()` methods
thus fixing a bug in the callers.
changes:
* adds TypedInFilter which preserves matching sets in the native match value type
* SQL planner uses new TypedInFilter when druid.generic.useDefaultValueForNull=false (the default)
* Add parameterized segment IDs.
* Refactor into one common method.
* Refactor getConditionForIntervalsAndMatchMode - pass in only what's needed.
* Minor cleanup.
Bug:
In the `MarkOvershadowedSegmentsAsUnused` duty, the coordinator marks a segment
as unused if it is overshadowed by a segment currently being served by a historical or broker.
But it is possible to have segments that are eligible for a load rule but require zero replicas
to be loaded. (Such segments can be queried only using the MSQ engine).
If such a zero-replica segment overshadows any other segment, the overshadowed segment will
never be marked as unused and will continue to exist in the metadata store as a dangling segment.
Fix:
- In a coordinator run, keep track of segments that are eligible for a load rule but require zero replicas
- Allow the zero-replicas segments to overshadow old segments and hence mark the latter as unused
Other changes:
- Add simulation test to verify new behaviour. This test fails with the current code.
- Clean up javadocs
Changes:
Add the following indexer level task metrics:
- `worker/task/running/count`
- `worker/task/assigned/count`
- `worker/task/completed/count`
These metrics will provide more visibility into the tasks distribution across indexers
(We often see a task skew issue across indexers and with this issue it would be easier
to catch the imbalance)
Gian Merlino
Vadim Ogievetsky
sullis
Vishesh Garg
Parag Jain
Sergio Ferragut
Soumyava
Abhishek Radhakrishnan
Zoltan Haindrich
AmatyaAvadhanula
zachjsh
Sree Charan Manamala
Aleksey Plekhanov
Kashif Faraz
Charles Smith
Tapajit Chandra Paul
Pranav
dependabot[bot]
Adithya Chakilam
Rishabh Singh
Sensor
Aru Raghuwanshi
Clint Wylie
Arun Ramani
Rushikesh Bankar