I was looking into adding a rule to do this, and found that it was already
happening as part of Calcite's RexSimplify. So this patch simply adds some
tests to ensure that it continues to happen.
The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information. This task encompasses addressing both realtime and finalized segments.
This modification specifically addresses the issue with realtime segments. Tasks will now routinely communicate the schema for realtime segments during the segment announcement process. The Coordinator will identify the schema alongside the segment announcement and subsequently update the schema for realtime segments in the metadata cache.
This PR enables the flag by default to queue excess query requests in the jetty queue. Still keeping the flag so that it can be turned off if necessary. But the flag will be removed in the future.
changes:
* ColumnIndexSelector now extends ColumnSelector. The only real implementation of ColumnIndexSelector, ColumnSelectorColumnIndexSelector, already has a ColumnSelector, so this isn't very disruptive
* removed getColumnNames from ColumnSelector since it was not used
* VirtualColumns and VirtualColumn getIndexSupplier method now needs argument of ColumnIndexSelector instead of ColumnSelector, which allows expression virtual columns to correctly recognize other virtual columns, fixing an issue which would incorrectly handle other virtual columns as non-existent columns instead
* fixed a bug with sql planner incorrectly not using expression filter for equality filters on columns with extractionFn and no virtual column registry
This logic error causes sarg expansion to happen twice for IN or NOT IN points.
It doesn't affect the final generated native query, because the
redundant expansions gets combined. But it slows down planning, especially
for large NOT IN.
FILTER_INTO_JOIN is mainly run along with the other rules with the Volcano planner; however if the query starts highly underdefined (join conditions in the where clauses) that generic query could give a lot of room for the other rules to play around with only enabled it for when the join uses subqueries for its inputs.
PROJECT_FILTER rule is not that useful. and could increase planning times by providing new plans. This problem worsened after we started supporting inner joins with arbitrary join conditions in https://github.com/apache/druid/pull/15302
- Rename ExprType to BaseType in CollectComparisons, since ExprType is a thing
that exists elsewhere.
- Remove unused "notInRexNodes" from SearchOperatorConversion.
* New handling for COALESCE, SEARCH, and filter optimization.
COALESCE is converted by Calcite's parser to CASE, which is largely
counterproductive for us, because it ends up duplicating expressions.
In the current code we end up un-doing it in our CaseOperatorConversion.
This patch has a different approach:
1) Add CaseToCoalesceRule to convert CASE back to COALESCE earlier, before
the Volcano planner runs, using CaseToCoalesceRule.
2) Add FilterDecomposeCoalesceRule to decompose calls like
"f(COALESCE(x, y))" into "(x IS NOT NULL AND f(x)) OR (x IS NULL AND f(y))".
This helps use indexes when available on x and y.
3) Add CoalesceLookupRule to push COALESCE into the third arg of LOOKUP.
4) Add a native "coalesce" function so we can convert 3+ arg COALESCE.
The advantage of this approach is that by un-doing the CASE to COALESCE
conversion earlier, we have flexibility to do more stuff with
COALESCE (like decomposition and pushing into LOOKUP).
SEARCH is an operator used internally by Calcite to represent matching
an argument against some set of ranges. This patch improves our handling
of SEARCH in two ways:
1) Expand NOT points (point "holes" in the range set) from SEARCH as
`!(a || b)` rather than `!a && !b`, which makes it possible to convert
them to a "not" of "in" filter later.
2) Generate those nice conversions for NOT points even if the SEARCH
is not composed of 100% NOT points. Without this change, a SEARCH
for "x NOT IN ('a', 'b') AND x < 'm'" would get converted like
"x < 'a' OR (x > 'a' AND x < 'b') OR (x > 'b' AND x < 'm')".
One of the steps we take when generating Druid queries from Calcite
plans is to optimize native filters. This patch improves this step:
1) Extract common ANDed predicates in ConvertSelectorsToIns, so we can
convert "(a && x = 'b') || (a && x = 'c')" into "a && x IN ('b', 'c')".
2) Speed up CombineAndSimplifyBounds and ConvertSelectorsToIns on
ORs with lots of children by adjusting the logic to avoid calling
"indexOf" and "remove" on an ArrayList.
3) Refactor ConvertSelectorsToIns to reduce duplicated code between the
handling for "selector" and "equals" filters.
* Not so final.
* Fixes.
* Fix test.
* Fix test.
Fixes#15072
Before this modification , the third parameter (timezone) require to be a Literal, it will throw a error when this parameter is column Identifier.
Updates ARRAY_OVERLAP to use the same ArrayContainsElement filter added in #15366 when filtering ARRAY typed columns so that it can also use indexes like ARRAY_CONTAINS.
This PR revives #14978 with a few more bells and whistles. Instead of an unconditional cross-join, we will now split the join condition such that some conditions are now evaluated post-join. To decide what sub-condition goes where, I have refactored DruidJoinRule class to extract unsupported sub-conditions. We build a postJoinFilter out of these unsupported sub-conditions and push to the join.
I think this is a problem as it discards the false return value when the putToKeyBuffer can't store the value because of the limit
Not forwarding the return value at that point may lead to the normal continuation here regardless something was not added to the dictionary like here
This PR fixes an issue where the grouping aggregator wrongly assumes that a key dimension is a virtual column and assigns a wrong name to it. This results in a mismatch between the dimensions that grouping aggregator sees and the dimension names that rows are aggregated on. And finally, grouping aggregator generates wrong result.
In pull request #14985, a bug was introduced where periodic refresh would skip rebuilding a datasource's schema after encountering a non-existent datasource. This resulted in remaining datasources having stale schema information.
This change addresses the bug and adds a unit test to validate the refresh mechanism's behaviour when a datasource is removed, and other datasources have schema changes.
In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal.
To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
* Add system fields to input sources.
Main changes:
1) The SystemField enum defines system fields "__file_uri", "__file_path",
and "__file_bucket". They are associated with each input entity.
2) The SystemFieldInputSource interface can be added to any InputSource
to make it system-field-capable. It sets up serialization of a list
of configured "systemFields" in the JSON form of the input source, and
provides a method getSystemFieldValue for computing the value of each
system field. Cloud object, HDFS, HTTP, and Local now have this.
* Fix various LocalInputSource calls.
* Fix style stuff.
* Fixups.
* Fix tests and coverage.
* better documentation for the differences between arrays and mvds
* add outputType to ExpressionPostAggregator to make docs true
* add output coercion if outputType is defined on ExpressionPostAgg
* updated post-aggregations.md to be consistent with aggregations.md and filters.md and use tables
* Use min of scheduler threads and server threads for subquery guardrails.
This allows more memory to be used for subqueries when the query scheduler
is configured to limit queries below the number of server threads. The patch
also refactors the code so SubqueryGuardrailHelper is provided by a Guice
Provider rather than being created by ClientQuerySegmentWalker, to achieve
better separation of concerns.
* Exclude provider from coverage.
Functions that accept literals also allow casted literals. This shouldn't have an impact on the queries that the user writes. It enables the SQL functions to accept explicit cast, which is required with JDBC.
- adds a new query build path: DruidQuery#toScanAndSortQuery which:
- builds a ScanQuery without considering the current ordering
- builds an operator to execute the sort
- fixes a null string to "null" literal string conversion in the frame serializer code
- fixes some DrillWindowQueryTest cases
- fix NPE in NaiveSortOperator in case there was no input
- enables back CoreRules.AGGREGATE_REMOVE
- adds a processing level OffsetLimit class and uses that instead of just the limit in the rac parts
- earlier window expressions on top of a subquery with an offset may have ignored the offset
for some exotic queries like:
SELECT
'_'||dim1,
MIN(cast(0 as double)) OVER (),
MIN(cast((cnt||cnt) as bigint)) OVER ()
FROM foo
the compilation have resulted in NPE -s mostly because VirtualColumn -s were not handled properly
This PR:
adds a flag to JsonToParquet to do the fix during conversion
updates the json files to more correct conents
some resultset mismatches were fixed by this
updates parquet to 1.13.1
* add native filters for "(filter) is true" and "(filter) is false"
changes:
* add IsTrueDimFilter, IsFalseDimFilter, and abstract IsBooleanDimFilter for native json filter implementations of `(filter) IS TRUE` and `(filter) IS FALSE`
* add IsBooleanFilter for actual filtering logic for these filters, which ignore includeUnknown to always use matches with false for true and !matches with true for false
* fix test incorrectly adjusted to wrong answer in #15058
* add tests for default value mode
* sql compatible tri-state native logical filters when druid.expressions.useStrictBooleans=true and druid.generic.useDefaultValueForNull=false, and new druid.generic.useThreeValueLogicForNativeFilters=true
* log.warn if non-default configurations are used to guide operators towards SQL complaint behavior
* fixes
* check for latest rewrite place
* Revert "check for latest rewrite place"
This reverts commit 5cf1e2c1ca.
* some stuff
(cherry picked from commit ab346d4373ea888eb8ef6115e018e7fb0d27407f)
* update test output
* updates to test ouptuts
* some stuff
* move validator
* cleanup
* fix
* change test slightly
* add apidoc cleanup warnings
* cleanup/etc
* instead of telling the story; add a fail with some reason whats the issue
* lead-lag fix
* add test
* remove unnecessary throw
* druidexception-trial
* Revert "druidexception-trial"
This reverts commit 8fa06644bc.
* undo changes to no_grouping; add no_grouping2
* add missing assert on resultcount
* rename method; update
* introduce enum/etc
* make resultmatchmode accessible from TestBuilder#expectedResults
* fix dump results to use log
* fix
* handle null correctly
* disable feature type based things for MSQ
* fix varianssqlaggtest
* use eps in other test
* fix intellij error
* add final
* addrss review
* update test/string/etc
* write concat in 3 lines :D
EARLIEST and LATEST operators implicitly reference the __time column for calculation of the aggregate value. Since the reference isn't explicit, Calcite sometimes fails to update the __time column name when there's column renaming --such as in the case of nested queries -- resulting in column not found errors.
This change rewrites these operators to EARLIEST_BY and LATEST_BY during query processing to make the reference explicit to Calcite.
- introduces a test_X method for every testcase (995 testcases)
- added a resultset parser which reads the expected resultset based on the result schema
- loaded a few more datasets
- added a testcase to ensure that all files have a corresponding testcase
- renamed DecoupledIgnore to NegativeTest
- categorized the failing 268 tests
* add a bunch of tests with array typed columns to CalciteArraysQueryTest
* fix a bug with unnest filter pushdown when filtering on unnested array columns
Instead of passing the constants around in a new parameter; InputAccessor was introduced to take care of transparently handling the constants - this new class started picking up some copy-paste debris around field accesses; and made them a little bit more readble.
The sql standard is not very restrictive regarding this:
If AVG is specified and DT is exact numeric, then the declared type of the result is an implemen-
tation-defined exact numeric type with precision not less than the precision of DT and scale not
less than the scale of DT.
so; using the same type is also ok (without patch);
however the avg of 0 and 1 is 0 right now because of the retention of the integer typ
Postgres,MySql and Oracle and Drill seem to increase precision ; mssql returns 0
http://sqlfiddle.com/#!9/6f7248/1
I think we should also increase precision as its already calculated more precisely
* Updating plans when using joins with unnest on the left
* Correcting segment map function for hashJoin
* The changes done here are not reflected into MSQ yet so these tests might not run in MSQ
* native tests
* Self joins with unnest data source
* Making this pass
* Addressing comments by adding explanation and new test
Row-based frames, and by extension, MSQ now supports numeric array types. This means that all queries consuming or producing arrays would also work with MSQ. Numeric arrays can also be ingested via MSQ. Post this patch, queries like, SELECT [1, 2] would work with MSQ since they consume a numeric array, instead of failing with an unsupported column type exception.
This change updates dependencies as needed and fixes tests to remove code incompatible with Java 21
As a result all unit tests now pass with Java 21.
* update maven-shade-plugin to 3.5.0 and follow-up to #15042
* explain why we need to override configuration when specifying outputFile
* remove configuration from dependency management in favor of explicit overrides in each module.
* update to mockito to 5.5.0 for Java 21 support when running with Java 11+
* continue using latest mockito 4.x (4.11.0) when running with Java 8
* remove need to mock private fields
* exclude incorrectly declared mockito dependency from pac4j-oidc
* remove mocking of ByteBuffer, since sealed classes can no longer be mocked in Java 21
* add JVM options workaround for system-rules junit plugin not supporting Java 18+
* exclude older versions of byte-buddy from assertj-core
* fix for Java 19 changes in floating point string representation
* fix missing InitializedNullHandlingTest
* update easymock to 5.2.0 for Java 21 compatibility
* update animal-sniffer-plugin to 1.23
* update nl.jqno.equalsverifier to 3.15.1
* update exec-maven-plugin to 3.1.0
Most of the testcases were disabled in CalciteWindowQueryTest during the Calcite-1.35 upgrade; there were some changes arising from the fact that the removal of DRUID_SUM had some unexpected sideffects:
SqlStdOperatorTable.SUM became the SUM operator
because of that SqlToRelConverter started rewriting windowed SUM -s into SUM0 -s
my opinion is that w.r.t to Druid this rewrite provides no real advantage - as SUM0 is serviced by SUM here
I believe that's not 100% correct in cases when it aggregates just null-s but that doesnt matter in this case
I propose to introduce back a local DRUID_SUM thing as an unchanged SUM and later when CALCITE-6020 is fixed ; we can drop that.
* coalesce on unnest row mismatch fix
* new example with coalesce over unnest with nested array columns
* New example with change in order which triggers the nvl
* new test plan update for useDefault=true
contains Enable already passing tests in DecoupledPlanningCalciteQueryTest #14996
enables a transpose rule to support a query plan in which the plan was in the shape:
Sort
Project
Aggregate
The aggregators had incorrect types for getResultType when shouldFinalze
is false. They had the finalized type, but they should have had the
intermediate type.
Also includes a refactor of how ExprMacroTable is handled in tests, to make
it easier to add tests for this to the MSQ module. The bug was originally
noticed because the incorrect result types caused MSQ queries with DS_HLL
to behave erratically.
These were added in #14977, but the implementations are incorrect, because they return null when the input arg is null. They should return false when the input is null. Remove them for now, rather than fixing them, since they're so new that they might as well never have existed.
This entails:
Removing the enableUnnest flag and additional machinery
Updating the datasource plan and frame processors to support unnest
Adding support in MSQ for UnnestDataSource and FilteredDataSource
CalciteArrayTest now has a MSQ test component
Additional tests for Unnest on MSQ
Currently, only the user who has submitted the async query has permission to interact with the status APIs for that async query. However, often we want an administrator to interact with these resources as well.
Druid handles these with the STATE resource traditionally, and if the requesting user has necessary permissions on it as well, alternatively, they should be allowed to interact with the status APIs, irrespective of whether they are the submitter of the query.
* Adding new function decode_base64_utf8 and expr macro
* using BaseScalarUnivariateMacroFunctionExpr
* Print stack trace in case of debug in ChainedExecutionQueryRunner
* fix static check
* Add IS [NOT] DISTINCT FROM to SQL and join matchers.
Changes:
1) Add "isdistinctfrom" and "notdistinctfrom" native expressions.
2) Add "IS [NOT] DISTINCT FROM" to SQL. It uses the new native expressions
when generating expressions, and is treated the same as equals and
not-equals when generating native filters on literals.
3) Update join matchers to have an "includeNull" parameter that determines
whether we are operating in "equals" mode or "is not distinct from"
mode.
* Main changes:
- Add ARRAY handling to "notdistinctfrom" and "isdistinctfrom".
- Include null in pushed-down filters when using "notdistinctfrom" in a join.
Other changes:
- Adjust join filter analyzer to more explicitly use InDimFilter's ValuesSets,
relying less on remembering to get it right to avoid copies.
* Remove unused "wrap" method.
* Fixes.
* Remove methods we do not need.
* Fix bug with INPUT_REF.
* SQL: Plan non-equijoin conditions as cross join followed by filter.
Druid has previously refused to execute joins with non-equality-based
conditions. This was well-intentioned: the idea was to push people to
write their queries in a different, hopefully more performant way.
But as we're moving towards fuller SQL support, it makes more sense to
allow these conditions to go through with the best plan we can come up
with: a cross join followed by a filter. In some cases this will allow
the query to run, and people will be happy with that. In other cases,
it will run into resource limits during execution. But we should at
least give the query a chance.
This patch also updates the documentation to explain how people can
tell whether their queries are being planned this way.
* cartesian is a word.
* Adjust tests.
* Update docs/querying/datasource.md
Co-authored-by: Benedict Jin <asdf2014@apache.org>
---------
Co-authored-by: Benedict Jin <asdf2014@apache.org>
This is due to the recursive filter creation in unnest storage adapter not performing correctly in case of an empty children. This PR addresses the issue
* Fix for schema mismatch to go down using the non vectorize path till we update the vectorized aggs properly
* Fixing a failed test
* Updating numericNilAgg
* Moving to use default values in case of nil agg
* Adding the same for first agg
* Fixing a test
* fixing vectorized string agg for last/first with cast if numeric
* Updating tests to remove mockito and cover the case of string first/last on non string columns
* Updating a test to vectorize
* Addressing review comments: Name change to NilVectorAggregator and using static variables now
* fixing intellij inspections
When materializing the results as frames, we defer the creation of the frames in ScanQueryQueryToolChest, which passes through the catch-all block reserved for catching cases when we don't have the complete row signature in the query (and falls back to the old code).
This PR aims to resolve it by adding the frame generation code to the try-catch block we have at the outer level.
changes:
* add back nested column v4 serializers
* 'json' schema by default still uses the newer 'nested common format' used by 'auto', but now has an optional 'formatVersion' property which can be specified to override format versions on native ingest jobs
* add system config to specify default column format stuff, 'druid.indexing.formats', and property 'druid.indexing.formats.nestedColumnFormatVersion' to specify system level preferred nested column format for friendly rolling upgrades from versions which do not support the newer 'nested common format' used by 'auto'
* update test
* update test
* format
* test
* fix0
* Revert "fix0"
This reverts commit 44992cb393.
* ok resultset
* add plan
* update test
* before rewind
* test
* fix toString/compare/test
* move test
* add timeColumn to hashCode
A new monitor SubqueryCountStatsMonitor which emits the metrics corresponding to the subqueries and their execution is now introduced. Moreover, the user can now also use the auto mode to automatically set the number of bytes available per query for the inlining of its subquery's results.
* Vectorizing earliest for numeric
* Vectorizing earliest string aggregator
* checkstyle fix
* Removing unnecessary exceptions
* Ignoring tests in MSQ as earliest is not supported for numeric there
* Fixing benchmarks
* Updating tests as MSQ does not support earliest for some cases
* Addressing review comments by adding the following:
1. Checking capabilities first before creating selectors
2. Removing mockito in tests for numeric first aggs
3. Removing unnecessary tests
* Addressing issues for dictionary encoded single string columns where we can use the dictionary ids instead of the entire string
* Adding a flag for multi value dimension selector
* Addressing comments
* 1 more change
* Handling review comments part 1
* Handling review comments and correctness fix for latest_by when the time expression need not be in sorted order
* Updating numeric first vector agg
* Revert "Updating numeric first vector agg"
This reverts commit 4291709901.
* Updating code for correctness issues
* fixing an issue with latest agg
* Adding more comments and removing an unnecessary check
* Addressing null checks for tie selector and only vectorize false for quantile sketches
Changes:
- Make ServiceMetricEvent.Builder extend ServiceEventBuilder<ServiceMetricEvent>
and thus convert it to a plain builder rather than a builder of builder.
- Add methods setCreatedTime , setMetricAndValue to the builder
* Update to Calcite 1.35.0
* Update from.ftl for Calcite 1.35.0.
* Fixed tests in Calcite upgrade by doing the following:
1. Added a new rule, CoreRules.PROJECT_FILTER_TRANSPOSE_WHOLE_PROJECT_EXPRESSIONS, to Base rules
2. Refactored the CorrelateUnnestRule
3. Updated CorrelateUnnestRel accordingly
4. Fixed a case with selector filters on the left where Calcite was eliding the virtual column
5. Additional test cases for fixes in 2,3,4
6. Update to StringListAggregator to fail a query if separators are not propagated appropriately
* Refactored for testcases to pass after the upgrade, introduced 2 new data sources for handling filters and select projects
* Added a literalSqlAggregator as the upgraded Calcite involved changes to subquery remove rule. This corrected plans for 2 queries with joins and subqueries by replacing an useless literal dimension with a post agg. Additionally a test with COUNT DISTINCT and FILTER which was failing with Calcite 1.21 is added here which passes with 1.35
* Updated to latest avatica and updated code as SqlUnknownTimeStamp is now used in Calcite which needs to be resolved to a timestamp literal
* Added a wrapper segment ref to use for unnest and filter segment reference
Fixes a case I missed in #14688 when the return type is STRING but its coming from a top level array typed column instead of a nested array column while making a vector object selector.
Also while here I noticed that the internal JSON_VALUE functions for array types were named inconsistently with the non-array functions, so I renamed them. These are not documented so it should not be disruptive in any way, since they are only used internally for rewrites while planning to make the correctly virtual column.
JSON_VALUE_RETURNING_ARRAY_VARCHAR -> JSON_VALUE_ARRAY_VARCHAR
JSON_VALUE_RETURNING_ARRAY_BIGINT -> JSON_VALUE_ARRAY_BIGINT
JSON_VALUE_RETURNING_ARRAY_DOUBLE -> JSON_VALUE_ARRAY_DOUBLE
The internal non-array functions are JSON_VALUE_VARCHAR, JSON_VALUE_BIGINT, and JSON_VALUE_DOUBLE.
* fix issue with nested virtual column array element vector selectors when input is numeric array but output is non-numeric
* add vector value selector for mixed numeric type variant and nested variant fields, tests
* fix issues with equality and range filters matching double values to long typed inputs
* adjust to ensure we never homogenize null, [], and [null] into [null] for expressions on real array columns
* Use OverlordClient for all Overlord RPCs.
Continuing the work from #12696, this patch removes HttpIndexingServiceClient
and the IndexingService flavor of DruidLeaderClient completely. All remaining
usages are migrated to OverlordClient.
Supporting changes include:
1) Add a variety of methods to OverlordClient.
2) Update MetadataTaskStorage to skip the complete-task lookup when
the caller requests zero completed tasks. This helps performance of
the "get active tasks" APIs, which don't want to see complete ones.
* Use less forbidden APIs.
* Fixes from CI.
* Add test coverage.
* Two more tests.
* Fix test.
* Updates from CR.
* Remove unthrown exceptions.
* Refactor to improve testability and test coverage.
* Add isNil tests.
* Remove unnecessary "deserialize" methods.
* Simplify bounds/range vs selectors/equality logic in SQL planning.
1) Consolidate duplicate code related to Expressions#buildTimeFloorFilter.
2) Cleaner logic in Expressions#toSimpleLeafFilter: choose bounds vs range
filter based solely on plannerContext.isUseBoundsAndSelectors, not also
considering rhs kind. Use parsed rhs in both paths (except for numerics
in the bound path).
3) Fix ArrayContains, ArrayOverlap to avoid equality filters when there is
an extractionFn present. Fixes a bug introduced in #14612.
* Avoid sending nonprimitives down the bound path.
* remove extractionFn from equality, null, and range filters
changes:
* EqualityFilter, NullFilter, and RangeFilter no longer support extractionFn
* SQL planner will use ExpressionFilter in the small number of cases where an extractionFn would have been used if sqlUseBoundsAndSelectors is set to false instead of equality/null/range filters
* fix bugs and add tests with serde, equals, and cache key for null, equality, and range filters
* test coverage fixes bugs
* adjust
* adjust again
* so persnickety
changes:
* new filters that preserve match value typing to better handle filtering different column types
* sql planner uses new filters by default in sql compatible null handling mode
* remove isFilterable from column capabilities
* proper handling of array filtering, add array processor to column processors
* javadoc for sql test filter functions
* range filter support for arrays, tons more tests, fixes
* add dimension selector tests for mixed type roots
* support json equality
* rename semantic index maker thingys to mostly have plural names since they typically make many indexes, e.g. StringValueSetIndex -> StringValueSetIndexes
* add cooler equality index maker, ValueIndexes
* fix missing string utf8 index supplier
* expression array comparator stuff
MSQ engine returns correct error codes for invalid user inputs in the query context. Also, using DruidExceptions for MSQ related errors happening in the Broker with improved error messages.
* Add aggregatorMergeStrategy property to SegmentMetadaQuery.
- Adds a new property aggregatorMergeStrategy to segmentMetadata query.
aggregatorMergeStrategy currently supports three types of merge strategies -
the legacy strict and lenient strategies, and the new latest strategy.
- The latest strategy considers the latest aggregator from the latest segment
by time order when there's a conflict when merging aggregators from different
segments.
- Deprecate lenientAggregatorMerge property; The API validates that both the new
and old properties are not set, and returns an exception.
- When merging segments as part of segmentMetadata query, the segments have a more
elaborate id -- <datasource>_<interval>_merged_<partition_number> format, similar to
the name format that segments usually contain. Previously it was simply "merged".
- Adjust unit tests to test the latest strategy, to assert the returned complete
SegmentAnalysis object instead of just the aggregators for completeness.
* Don't explicitly set strict strategy in tests
* Apply suggestions from code review
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
* Update docs/querying/segmentmetadataquery.md
* Apply suggestions from code review
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
---------
Co-authored-by: Katya Macedo <38017980+ektravel@users.noreply.github.com>
* Fix a resource leak with Window processing
Additionally, in order to find the leak, there were
adjustments to the StupidPool to track leaks a bit better.
It would appear that the pool objects get GC'd during testing
for some reason which was causing some incorrect identification
of leaks from objects that had been returned but were GC'd along
with the pool.
* Suppress unused warning
sqlJoinAlgorithm is now a hint to the planner to execute the join in the specified manner. The planner can decide to ignore the hint if it deduces that the specified algorithm can be detrimental to the performance of the join beforehand.
* Claim full support for Java 17.
No production code has changed, except the startup scripts.
Changes:
1) Allow Java 17 without DRUID_SKIP_JAVA_CHECK.
2) Include the full list of opens and exports on both Java 11 and 17.
3) Document that Java 17 is both supported and preferred.
4) Switch some tests from Java 11 to 17 to get better coverage on the
preferred version.
* Doc update.
* Update errorprone.
* Update docker_build_containers.sh.
* Update errorprone in licenses.yaml.
* Add some more run-javas.
* Additional run-javas.
* Update errorprone.
* Suppress new errorprone error.
* Add exports and opens in ForkingTaskRunner for Java 11+.
Test, doc changes.
* Additional errorprone updates.
* Update for errorprone.
* Restore old fomatting in LdapCredentialsValidator.
* Copy bin/ too.
* Fix Java 15, 17 build line in docker_build_containers.sh.
* Update busybox image.
* One more java command.
* Fix interpolation.
* IT commandline refinements.
* Switch to busybox 1.34.1-glibc.
* POM adjustments, build and test one IT on 17.
* Additional debugging.
* Fix silly thing.
* Adjust command line.
* Add exports and opens one more place.
* Additional harmonization of strong encapsulation parameters.
* Fix ColumnSignature error message and jdk17 test issue.
On jdk17, the "problem" part of the error message could change from
NullPointerException to:
Cannot invoke "String.length()" because "s" is null
Due to the new more-helpful NPEs in Java 17. This broke the expectation
and led to test failures on this case.
This patch fixes the problem by improving the error message so it isn't
a generic NullPointerException.
* Fix format.
* Add support for DML WITH AS.
* One more UT for with as subquery.
* Add a test with join query
* Use root query prepared node instead of individual SqlNode types.
- Set the explain plan attributes after the query is prepared when
the query is planned and we've the finalized output names in the root
source rel node.
- Adjust tests; add unit test for negative ordinal case.
- Remove the exception / error handling logic from resolveClusteredBy
function since the validations now happen before it comes to the function
* Update comment.
This commit borrows some test definitions from Drill's test suite
and tries to use them to flesh out the full validation of window
function capbilities.
In order to be able to run these tests, we also add the ability to
run a Scan operation against segments, which also meant an
implementation of RowsAndColumns for frames.
with a RuntimeException. Now the RuntimeException is being replaced by an user facing DruidException of Invalid category which would allow calcite not to throw an uncategorized exception.
In these other cases, stick to plain "filter". This simplifies lots of
logic downstream, and doesn't hurt since we don't have intervals-specific
optimizations outside of tables.
Fixes an issue where we couldn't properly filter on a column from an
external datasource if it was named __time.
* Support complex variance object inputs for variance SQL agg function
* Add test
* Include complexTypeChecker, address PR comments
* Checkstyle, javadoc link
This PR aims to expose a new API called
"@path("/druid/v2/sql/statements/")" which takes the same payload as the current "/druid/v2/sql" endpoint and allows users to fetch results in an async manner.
* Cache parsed expressions and binding analysis in more places.
Main changes:
1) Cache parsed and analyzed expressions within PlannerContext for a
single SQL query.
2) Cache parsed expressions together with input binding analysis using
a new class AnalyzeExpr.
This speeds up SQL planning, because SQL planning involves parsing
analyzing the same expression strings over and over again.
* Fixes.
* Fix style.
* Fix test.
* Simplify: get rid of AnalyzedExpr, focus on caching.
* Rename parse -> parseExpression.
* Updates: use the target table directly, sanitized replace time chunks and clustered by cols.
* Add DruidSqlParserUtil and tests.
* minor refactor
* Use SqlUtil.isLiteral
* Throw ValidationException if CLUSTERED BY column descending order is specified.
- Fails query planning
* Some more tests.
* fixup existing comment
* Update comment
* checkstyle fix: remove unused imports
* Remove InsertCannotOrderByDescendingFault and deprecate the fault in readme.
* minor naming
* move deprecated field to the bottom
* update docs.
* add one more example.
* Collapsible query and result
* checkstyle fixes
* Code cleanup
* order by changes
* conditionally set attributes only for explain queries.
* Cleaner ordinal check.
* Add limit test and update javadoc.
* Commentary and minor adjustments.
* Checkstyle fixes.
* One more checkArg.
* add unexpected kind to exception.
Users can now add a guardrail to prevent subquery’s results from exceeding the set number of bytes by setting druid.server.http.maxSubqueryRows in Broker's config or maxSubqueryRows in the query context. This feature is experimental for now and would default back to row-based limiting in case it fails to get the accurate size of the results consumed by the query.
* SqlResults: Coerce arrays to lists for VARCHAR.
Useful for STRING_TO_MV, which returns VARCHAR at the SQL layer and an
ExprEval with String[] at the native layer.
* Fix style.
* Improve test coverage.
* Remove unnecessary throws.
Gian Merlino
Ankit Kothari
Rishabh Singh
Abhishek Agarwal
Clint Wylie
Jonathan Wei
Zoltan Haindrich
AlbericByte
Soumyava
Adarsh Sanjeev
sb89594
Pranav
Laksh Singla
Zoltan Haindrich
Vishesh Garg
Xavier Léauté
Suneet Saldanha
Kashif Faraz
AmatyaAvadhanula
Abhishek Radhakrishnan
imply-cheddar
Karan Kumar