* Add type coercion and null check to left, right, repeat exprs.
These exprs shouldn't validate types; they should coerce types. Coercion
is typical behavior for functions because it enables schema evolution.
The functions are also modified to check isNumericNull on the right-hand
argument. This was missing previously, which would erroneously cause
nulls to be treated as zeroes.
* Fix tests.
Reduction of nullable DATE and TIMESTAMP expressions did not perform
a necessary null check, so would in some cases reduce to
1970-01-01 00:00:00 (epoch) rather than NULL.
changes:
* Added `CursorBuildSpec` which captures all of the 'interesting' stuff that goes into producing a cursor as a replacement for the method arguments of `CursorFactory.canVectorize`, `CursorFactory.makeCursor`, and `CursorFactory.makeVectorCursor`
* added new interface `CursorHolder` and new interface `CursorHolderFactory` as a replacement for `CursorFactory`, with method `makeCursorHolder`, which takes a `CursorBuildSpec` as an argument and replaces `CursorFactory.canVectorize`, `CursorFactory.makeCursor`, and `CursorFactory.makeVectorCursor`
* `CursorFactory.makeCursors` previously returned a `Sequence<Cursor>` corresponding to the query granularity buckets, with a separate `Cursor` per bucket. `CursorHolder.asCursor` instead returns a single `Cursor` (equivalent to 'ALL' granularity), and a new `CursorGranularizer` has been added for query engines to iterate over the cursor and divide into granularity buckets. This makes the non-vectorized engine behave the same way as the vectorized query engine (with its `VectorCursorGranularizer`), and simplifies a lot of stuff that has to read segments particularly if it does not care about bucketing the results into granularities.
* Deprecated `CursorFactory`, `CursorFactory.canVectorize`, `CursorFactory.makeCursors`, and `CursorFactory.makeVectorCursor`
* updated all `StorageAdapter` implementations to implement `makeCursorHolder`, transitioned direct `CursorFactory` implementations to instead implement `CursorMakerFactory`. `StorageAdapter` being a `CursorMakerFactory` is intended to be a transitional thing, ideally will not be released in favor of moving `CursorMakerFactory` to be fetched directly from `Segment`, however this PR was already large enough so this will be done in a follow-up.
* updated all query engines to use `makeCursorHolder`, granularity based engines to use `CursorGranularizer`.
* SQL syntax error should target USER persona
* * revert change to queryHandler and related tests, based on review comments
* * add test
* Properly handle Druid schema blending with catalog definition and segment metadata
* * add javadocs
* SQL: Add ProjectableFilterableTable to SegmentsTable.
This allows us to skip serialization of expensive fields such as
shard_spec, dimensions, metrics, and last_compaction_state, if those
fields are not actually being queried.
* Restructure logic to avoid unnecessary toString() as well.
When a window is defined as WINDOW W AS <DEF> and using a syntax of (PARTITION BY col1 ORDER BY col2 ROWS x PRECEDING), we would need to default the other bound to CURRENT ROW
We already have implemented this earlier, but when defined as WINDOW W AS <DEF>, Calcite takes a different route to validate the window.
* enables to launch a fake broker based on test resources (druidtest uri)
* could record queries into new testfiles during usage
* instead of re-purpose Calcite's Hook migrates to use DruidHook which we can add further keys
* added a quidem-ut module which could be the place for tests which could iteract with modules/etc
This patch introduces an optional cluster configuration, druid.indexing.formats.stringMultiValueHandlingMode, allowing operators to override the default mode SORTED_SET for string dimensions. The possible values for the config are SORTED_SET, SORTED_ARRAY, or ARRAY (SORTED_SET is the default). Case insensitive values are allowed.
While this cluster property allows users to manage the multi-value handling mode for string dimension types, it's recommended to migrate to using real array types instead of MVDs.
This fixes a long-standing issue where compaction will honor the configured cluster wide property instead of rewriting it as the default SORTED_ARRAY always, even if the data was originally ingested with ARRAY or SORTED_SET.
Rejects having clauses if they contain windowed expressions.
Also added a check to produce a more descriptive error if an OVER expression
reaches the filter translation layer.
---------
Co-authored-by: Benedict Jin <asdf2014@apache.org>
Changes the WindowFrame internals / representation a bit; introduces dedicated frametypes for rows and groups which corresponds to the implemented processing methods
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
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
* When an ArrayList RAC creates a child RAC, the start and end offsets need to have the offset of parent's start offset
* Defaults the 2nd window bound to CURRENT ROW when only a single bound is specified
* Removes the windowingStrictValidation warning and throws a hard exception when Order By alongside RANGE clause is not provided with UNBOUNDED or CURRENT ROW as both bounds
Description:
Compaction operations issued by the Coordinator currently run using the native query engine.
As majority of the advancements that we are making in batch ingestion are in MSQ, it is imperative
that we support compaction on MSQ to make Compaction more robust and possibly faster.
For instance, we have seen OOM errors in native compaction that MSQ could have handled by its
auto-calculation of tuning parameters.
This commit enables compaction on MSQ to remove the dependency on native engine.
Main changes:
* `DataSourceCompactionConfig` now has an additional field `engine` that can be one of
`[native, msq]` with `native` being the default.
* if engine is MSQ, `CompactSegments` duty assigns all available compaction task slots to the
launched `CompactionTask` to ensure full capacity is available to MSQ. This is to avoid stalling which
could happen in case a fraction of the tasks were allotted and they eventually fell short of the number
of tasks required by the MSQ engine to run the compaction.
* `ClientCompactionTaskQuery` has a new field `compactionRunner` with just one `engine` field.
* `CompactionTask` now has `CompactionRunner` interface instance with its implementations
`NativeCompactinRunner` and `MSQCompactionRunner` in the `druid-multi-stage-query` extension.
The objectmapper deserializes `ClientCompactionRunnerInfo` in `ClientCompactionTaskQuery` to the
`CompactionRunner` instance that is mapped to the specified type [`native`, `msq`].
* `CompactTask` uses the `CompactionRunner` instance it receives to create the indexing tasks.
* `CompactionTask` to `MSQControllerTask` conversion logic checks whether metrics are present in
the segment schema. If present, the task is created with a native group-by query; if not, the task is
issued with a scan query. The `storeCompactionState` flag is set in the context.
* Each created `MSQControllerTask` is launched in-place and its `TaskStatus` tracked to determine the
final status of the `CompactionTask`. The id of each of these tasks is the same as that of `CompactionTask`
since otherwise, the workers will be unable to determine the controller task's location for communication
(as they haven't been launched via the overlord).
temp fix until CALCITE-6435 gets fixed (released&upgraded to)
added a custom rule (FixIncorrectInExpansionTypes) to fix-up types of the affected literals
added a testcase which will alert on upgrade
* first pass
* more changes
* fix tests and formatting
* fix kinesis failing tests
* fix kafka tests
* add dimension name to float parse errors
* double and convertToType handling of dimensionName can report parse errors with dimension name
* fix checkstyle issue
* fix tests
* more cases to have better parse exception messages
* fix test
* fix tests
* partially address comments
* annotate method parameter with nullable
* address comments
* fix tests
* let float, double, long dimensionIndexer pass dimensionName down to dimensionHandlerUtils
* fix compilation error and clean up formatting
* clean up whitespace
* address feedback. undo change, pass down report parse exception for convertToType
* fix test
index_realtime tasks were removed from the documentation in #13107. Even
at that time, they weren't really documented per se— just mentioned. They
existed solely to support Tranquility, which is an obsolete ingestion
method that predates migration of Druid to ASF and is no longer being
maintained. Tranquility docs were also de-linked from the sidebars and
the other doc pages in #11134. Only a stub remains, so people with
links to the page can see that it's no longer recommended.
index_realtime_appenderator tasks existed in the code base, but were
never documented, nor as far as I am aware were they used for any purpose.
This patch removes both task types completely, as well as removes all
supporting code that was otherwise unused. It also updates the stub
doc for Tranquility to be firmer that it is not compatible. (Previously,
the stub doc said it wasn't recommended, and pointed out that it is
built against an ancient 0.9.2 version of Druid.)
ITUnionQueryTest has been migrated to the new integration tests framework and updated to use Kafka ingestion.
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* Turn invalid periods into user-facing exception providing more context.
The current exception is targeting the ADMIN persona. Catch that and turn
it into a USER persona instead. Also, provide more context in the error
message.
* Review comment: pass the wrapping expression and stringify.
* Update processing/src/main/java/org/apache/druid/query/expression/ExprUtils.java
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
---------
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* contains Make a full copy of the parser and apply our modifications to it #16503
* some minor api changes pair/entry
* some unnecessary aggregation was removed from a set of queries in `CalciteSubqueryTest`
* `AliasedOperatorConversion` was detecting `CHAR_LENGTH` as not a function ; I've removed the check
* the field it was using doesn't look maintained that much
* the `kind` is passed for the created `SqlFunction` so I don't think this check is actually needed
* some decoupled test cases become broken - will be fixed later
* some aggregate related changes: due to the fact that SUM() and COUNT() of no inputs are different
* upgrade avatica to 1.25.0
* `CalciteQueryTest#testExactCountDistinctWithFilter` is now executable
Closeapache/druid#16503
* fix NestedDataColumnIndexerV4 to not report cardinality
changes:
* fix issue similar to #16489 but for NestedDataColumnIndexerV4, which can report STRING type if it only processes a single type of values. this should be less common than the auto indexer problem
* fix some issues with sql benchmarks
This fixes an issue where in some cases, a SQL syntax error encountered when parsing / planning a query results in an error returned to the user with persona a `admin` when it should instead be `user`.
Gian Merlino
Akshat Jain
Rishabh Singh
Clint Wylie
Sree Charan Manamala
zachjsh
Zoltan Haindrich
Abhishek Radhakrishnan
Laksh Singla
Vishesh Garg
Alberic Liu
Tom