* 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.
* SQL OperatorConversions: Introduce.aggregatorBuilder, allow CAST-as-literal.
Four main changes:
1) Provide aggregatorBuilder, a more consistent way of defining the
SqlAggFunction we need for all of our SQL aggregators. The mechanism
is analogous to the one we already use for SQL functions
(OperatorConversions.operatorBuilder).
2) Allow CASTs of constants to be considered as "literalOperands". This
fixes an issue where various of our operators are defined with
OperandTypes.LITERAL as part of their checkers, which doesn't allow
casts. However, in these cases we generally _do_ want to allow casts.
The important piece is that the value must be reducible to a constant,
not that the SQL text is literally a literal.
3) Update DataSketches SQL aggregators to use the new aggregatorBuilder
functionality. The main user-visible effect here is [2]: the aggregators
would now accept, for example, "CAST(0.99 AS DOUBLE)" as a literal
argument. Other aggregators could be updated in a future patch.
4) Rename "requiredOperands" to "requiredOperandCount", because the
old name was confusing. (It rhymes with "literalOperands" but the
arguments mean different things.)
* Adjust method calls.
New metrics:
- `segment/metadatacache/refresh/time`: time taken to refresh segments per datasource
- `segment/metadatacache/refresh/count`: number of segments being refreshed per datasource
Add a new planning strategy that explicitly decouples the DAG from building the native query.
With this mode, it is Calcite's job to generate a "logical DAG" which is all of the various
DruidProject, DruidFilter, etc. nodes. We then take those nodes and use them to build a native
query. The current commit doesn't pass all tests, but it does work for some things and is a
decent starting baseline.
Introduce DruidException, an exception whose goal in life is to be delivered to a user.
DruidException itself has javadoc on it to describe how it should be used. This commit both introduces the Exception and adjusts some of the places that are generating exceptions to generate DruidException objects instead, as a way to show how the Exception should be used.
This work was a 3rd iteration on top of work that was started by Paul Rogers. I don't know if his name will survive the squash-and-merge, so I'm calling it out here and thanking him for starting on this.
Description:
Druid allows a configuration of load rules that may cause a used segment to not be loaded
on any historical. This status is not tracked in the sys.segments table on the broker, which
makes it difficult to determine if the unavailability of a segment is expected and if we should
not wait for it to be loaded on a server after ingestion has finished.
Changes:
- Track replication factor in `SegmentReplicantLookup` during evaluation of load rules
- Update API `/druid/coordinator/v1metadata/segments` to return replication factor
- Add column `replication_factor` to the sys.segments virtual table and populate it in
`MetadataSegmentView`
- If this column is 0, the segment is not assigned to any historical and will not be loaded.
* 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.
* move deprecated field to the bottom
changes:
* auto columns no longer participate in generic 'null column' handling, this was a mistake to try to support and caused ingestion failures due to mismatched ColumnFormat, and will be replaced in the future with nested common format constant column functionality (not in this PR)
* fix bugs with auto columns which contain empty objects, empty arrays, or primitive types mixed with either of these empty constructs
* fix bug with bound filter when upper is null equivalent but is strict
* Add INFORMATION_SCHEMA.ROUTINES to expose Druid operators and functions.
* checkstyle
* remove IS_DETERMISITIC.
* test
* cleanup test
* remove logs and simplify
* fixup unit test
* Add docs for INFORMATION_SCHEMA.ROUTINES table.
* Update test and add another SQL query.
* add stuff to .spelling and checkstyle fix.
* Add more tests for custom operators.
* checkstyle and comment.
* Some naming cleanup.
* Add FUNCTION_ID
* The different Calcite function syntax enums get translated to FUNCTION
* Update docs.
* Cleanup markdown table.
* fixup test.
* fixup intellij inspection
* Review comment: nullable column; add a function to determine function syntax.
* More tests; add non-function syntax operators.
* More unit tests. Also add a separate test for DruidOperatorTable.
* actually just validate non-zero count.
* switch up the order
* checkstyle fixes.
This PR adds the following to the ATTRIBUTES column in the explain plan output:
- partitionedBy
- clusteredBy
- replaceTimeChunks
This PR leverages the work done in #14074, which added a new column ATTRIBUTES
to encapsulate all the statement-related attributes.
* Fix EarliestLatestBySqlAggregator signature; Include function name for all signatures.
* Single quote function signatures, space between args and remove \n.
* fixup UT assertion
It was found that several supported tasks / input sources did not have implementations for the methods used by the input source security feature, causing these tasks and input sources to fail when used with this feature. This pr adds the needed missing implementations. Also securing the sampling endpoint with input source security, when enabled.
This PR adds a new interface to control how SegmentMetadataCache chooses ColumnType when faced with differences between segments for SQL schemas which are computed, exposed as druid.sql.planner.metadataColumnTypeMergePolicy and adds a new 'least restrictive type' mode to allow choosing the type that data across all segments can best be coerced into and sets this as the default behavior.
This is a behavior change around when segment driven schema migrations take effect for the SQL schema. With latestInterval, the SQL schema will be updated as soon as the first job with the new schema has published segments, while using leastRestrictive, the schema will only be updated once all segments are reindexed to the new type. The benefit of leastRestrictive is that it eliminates a bunch of type coercion errors that can happen in SQL when types are varied across segments with latestInterval because the newest type is not able to correctly represent older data, such as if the segments have a mix of ARRAY and number types, or any other combinations that lead to odd query plans.
* Make resources an ordered collection so it's deterministic.
* test cleanup
* fixup docs.
* Replace deprecated ObjectNode#put() calls with ObjectNode#set().
Soumyava
Pranav
Zoltan Haindrich
Clint Wylie
Laksh Singla
Xavier Léauté
Gian Merlino
Suneet Saldanha
Kashif Faraz
Zoltan Haindrich
Rishabh Singh
Adarsh Sanjeev
AmatyaAvadhanula
Abhishek Radhakrishnan
imply-cheddar
Jonathan Wei
Karan Kumar
Rohan Garg
zachjsh