changes:
* Adds new `CompressedComplexColumn`, `CompressedComplexColumnSerializer`, `CompressedComplexColumnSupplier` based on `CompressedVariableSizedBlobColumn` used by JSON columns
* Adds `IndexSpec.complexMetricCompression` which can be used to specify compression for the generic compressed complex column. Defaults to uncompressed because compressed columns are not backwards compatible.
* Adds new definition of `ComplexMetricSerde.getSerializer` which accepts an `IndexSpec` argument when creating a serializer. The old signature has been marked `@Deprecated` and has a default implementation that returns `null`, but it will be used by the default implementation of the new version if it is implemented to return a non-null value. The default implementation of the new method will use a `CompressedComplexColumnSerializer` if `IndexSpec.complexMetricCompression` is not null/none/uncompressed, or will use `LargeColumnSupportedComplexColumnSerializer` otherwise.
* Removed all duplicate generic implementations of `ComplexMetricSerde.getSerializer` and `ComplexMetricSerde.deserializeColumn` into default implementations `ComplexMetricSerde` instead of being copied all over the place. The default implementation of `deserializeColumn` will check if the first byte indicates that the new compression was used, otherwise will use the `GenericIndexed` based supplier.
* Complex columns with custom serializers/deserializers are unaffected and may continue doing whatever it is they do, either with specialized compression or whatever else, this new stuff is just to provide generic implementations built around `ObjectStrategy`.
* add ObjectStrategy.readRetainsBufferReference so CompressedComplexColumn only copies on read if required
* add copyValueOnRead flag down to CompressedBlockReader to avoid buffer duplicate if the value needs copied anyway
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`.
* 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
In case of few aggregators for example BloomSqlAggregator, BaseVarianceSqlAggregator etc, the aggName is being updated from a0 to a0:agg, breaching the contract as we would expect the aggName as the name which is passed. This is causing a mismatch while creating a column accessor.
This commit aims to correct those violating sql aggregators.
* enable quidem uri support for `druidtest:///?ComponentSupplier=Nested` and similar
* changes the way `SqlTestFrameworkConfig` is being applied; all options will have their own annotation (its kinda impossible to detect that an annotation has a set value or its the default)
* enables hierarchical processing of config annotation (was needed to enable class level supplier annotation)
* moves uri processing related string2config stuff into `SqlTestFrameworkConfig`
* Update Calcite*Test to use junit5
* change the way temp dirs are handled
* add openrewrite workflow to safeguard upgrade
* replace junitparamrunner with standard junit5 parametered tests
* update a few rules to junit5 api
* lots of boring changes
* cleanup QueryLogHook
* cleanup
* fix compile error: ARRAYS_DATASOURCE
* fix test
* remove enclosed
* empty
+TEST:TDigestSketchSqlAggregatorTest,HllSketchSqlAggregatorTest,DoublesSketchSqlAggregatorTest,ThetaSketchSqlAggregatorTest,ArrayOfDoublesSketchSqlAggregatorTest,BloomFilterSqlAggregatorTest,BloomDimFilterSqlTest,CatalogIngestionTest,CatalogQueryTest,FixedBucketsHistogramQuantileSqlAggregatorTest,QuantileSqlAggregatorTest,MSQArraysTest,MSQDataSketchesTest,MSQExportTest,MSQFaultsTest,MSQInsertTest,MSQLoadedSegmentTests,MSQParseExceptionsTest,MSQReplaceTest,MSQSelectTest,InsertLockPreemptedFaultTest,MSQWarningsTest,SqlMSQStatementResourcePostTest,SqlStatementResourceTest,CalciteSelectJoinQueryMSQTest,CalciteSelectQueryMSQTest,CalciteUnionQueryMSQTest,MSQTestBase,VarianceSqlAggregatorTest,SleepSqlTest,SqlRowTransformerTest,DruidAvaticaHandlerTest,DruidStatementTest,BaseCalciteQueryTest,CalciteArraysQueryTest,CalciteCorrelatedQueryTest,CalciteExplainQueryTest,CalciteExportTest,CalciteIngestionDmlTest,CalciteInsertDmlTest,CalciteJoinQueryTest,CalciteLookupFunctionQueryTest,CalciteMultiValueStringQueryTest,CalciteNestedDataQueryTest,CalciteParameterQueryTest,CalciteQueryTest,CalciteReplaceDmlTest,CalciteScanSignatureTest,CalciteSelectQueryTest,CalciteSimpleQueryTest,CalciteSubqueryTest,CalciteSysQueryTest,CalciteTableAppendTest,CalciteTimeBoundaryQueryTest,CalciteUnionQueryTest,CalciteWindowQueryTest,DecoupledPlanningCalciteJoinQueryTest,DecoupledPlanningCalciteQueryTest,DecoupledPlanningCalciteUnionQueryTest,DrillWindowQueryTest,DruidPlannerResourceAnalyzeTest,IngestTableFunctionTest,QueryTestRunner,SqlTestFrameworkConfig,SqlAggregationModuleTest,ExpressionsTest,GreatestExpressionTest,IPv4AddressMatchExpressionTest,IPv4AddressParseExpressionTest,IPv4AddressStringifyExpressionTest,LeastExpressionTest,TimeFormatOperatorConversionTest,CombineAndSimplifyBoundsTest,FiltrationTest,SqlQueryTest,CalcitePlannerModuleTest,CalcitesTest,DruidCalciteSchemaModuleTest,DruidSchemaNoDataInitTest,InformationSchemaTest,NamedDruidSchemaTest,NamedLookupSchemaTest,NamedSystemSchemaTest,RootSchemaProviderTest,SystemSchemaTest,CalciteTestBase,SqlResourceTest
* use @Nested
* add rule to remove enclosed; upgrade surefire
* remove enclosed
* cleanup
* add comment about surefire exclude
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.
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.
Currently, Druid is using Guava 16.0.1 version. This upgrade to 31.1-jre fixes the following issues.
CVE-2018-10237 (Unbounded memory allocation in Google Guava 11.0 through 24.x before 24.1.1 allows remote attackers to conduct denial of service attacks against servers that depend on this library and deserialize attacker-provided data because the AtomicDoubleArray class (when serialized with Java serialization) and the CompoundOrdering class (when serialized with GWT serialization) perform eager allocation without appropriate checks on what a client has sent and whether the data size is reasonable). We don't use Java or GWT serializations. Despite being false positive they're causing red security scans on Druid distribution.
Latest version of google-client-api is incompatible with the existing Guava version. This PR unblocks Update google client apis to latest version #14414
The current version of jackson-databind is flagged for vulnerabilities CVE-2020-28491 (Although cbor format is not used in druid), CVE-2020-36518 (Seems genuine as deeply nested json in can cause resource exhaustion). Updating the dependency to the latest version 2.12.7 to fix these vulnerabilities.
* Fix EarliestLatestBySqlAggregator signature; Include function name for all signatures.
* Single quote function signatures, space between args and remove \n.
* fixup UT assertion
* merge druid-core, extendedset, and druid-hll into druid-processing to simplify everything
* fix poms and license stuff
* mockito is evil
* allow reset of JvmUtils RuntimeInfo if tests used static injection to override
changes:
* modified druid schema column type compution to special case COMPLEX<json> handling to choose COMPLEX<json> if any column in any segment is COMPLEX<json>
* NestedFieldVirtualColumn can now work correctly on any type of column, returning either a column selector if a root path, or nil selector if not
* fixed a random bug with NilVectorSelector when using a vector size larger than the default and druid.generic.useDefaultValueForNull=false would have the nulls vector set to all false instead of true
* fixed an overly aggressive check in ExprEval.ofType when handling complex types which would try to treat any string as base64 without gracefully falling back if it was not in fact base64 encoded, along with special handling for complex<json>
* added ExpressionVectorSelectors.castValueSelectorToObject and ExpressionVectorSelectors.castObjectSelectorToNumeric as convience methods to cast vector selectors using cast expressions without the trouble of constructing an expression. the polymorphic nature of the non-vectorized engine (and significantly larger overhead of non-vectorized expression processing) made adding similar methods for non-vectorized selectors less attractive and so have not been added at this time
* fix inconsistency between nested column indexer and serializer in handling values (coerce non primitive and non arrays of primitives using asString)
* ExprEval best effort mode now handles byte[] as string
* added test for ExprEval.bestEffortOf, and add missing conversion cases that tests uncovered
* more tests more better
SQL test framework extensions
* Capture planner artifacts: logical plan, etc.
* Planner test builder validates the logical plan
* Validation for the SQL resut schema (we already have
validation for the Druid row signature)
* Better Guice integration: properties, reuse Guice modules
* Avoid need for hand-coded expr, macro tables
* Retire some of the test-specific query component creation
* Fix query log hook race condition
We added compression to the latest/first pair storage, but
the code change was forcing new things to be persisted
with the new format, meaning that any segment created with
the new code cannot be read by the old code. Instead, we
need to default to creating the old format and then remove that default in a future version.
* Refactor Calcite test "framework" for planner tests
Refactors the current Calcite tests to make it a bit easier
to adjust the set of runtime objects used within a test.
* Move data creation out of CalciteTests into TestDataBuilder
* Move "framework" creation out of CalciteTests into
a QueryFramework
* Move injector-dependent functions from CalciteTests
into QueryFrameworkUtils
* Wrapper around the planner factory, etc. to allow
customization.
* Bulk of the "framework" created once per class rather
than once per test.
* Refactor tests to use a test builder
* Change all testQuery() methods to use the test builder.
Move test execution & verification into a test runner.
This adds min/max functions for CompressedBigDecimal. It exposes these
functions via sql (BIG_MAX, BIG_MIN--see the SqlAggFunction
implementations).
It also includes various bug fixes and cleanup to the original
CompressedBigDecimal code include the AggregatorFactories. Various null
handling was improved.
Additional test cases were added for both new and existing code
including a base test case for AggregationFactories. Other tests common
across sum,min,max may be refactored also to share the varoius cases in
the future.
This adds a sql function, "BIG_SUM", that uses
CompressedBigDecimal to do a sum. Other misc changes:
1. handle NumberFormatExceptions when parsing a string (default to set
to 0, configurable in agg factory to be strict and throw on error)
2. format pom file (whitespace) + add dependency
3. scaleUp -> scale and always require scale as a parameter
Optimizes the compareTo() function in
CompressedBigDecimal. It directly compares the int[] rather than
creating BigDecimal objects and using its compareTo.
It handles unequal sized CBDs, but does require
the scales to match.
1. remove unnecessary generic type from CompressedBigDecimal
2. support Number input types
3. support aggregator reading supported input types directly (uningested
data)
4. fix scaling bug in buffer aggregator
Compressed Big Decimal is an extension which provides support for
Mutable big decimal value that can be used to accumulate values
without losing precision or reallocating memory. This type helps in
absolute precision arithmetic on large numbers in applications,
where greater level of accuracy is required, such as financial
applications, currency based transactions. This helps avoid rounding
issues where in potentially large amount of money can be lost.
Accumulation requires that the two numbers have the same scale,
but does not require that they are of the same size. If the value
being accumulated has a larger underlying array than this value
(the result), then the higher order bits are dropped, similar to what
happens when adding a long to an int and storing the result in an
int. A compressed big decimal that holds its data with an embedded
array.
Compressed big decimal is an absolute number based complex type
based on big decimal in Java. This supports all the functionalities
supported by Java Big Decimal. Java Big Decimal is not mutable in
order to avoid big garbage collection issues. Compressed big decimal
is needed to mutate the value in the accumulator.
Abhishek Agarwal
Clint Wylie
Zoltan Haindrich
Sree Charan Manamala
Adarsh Sanjeev
Karan Kumar
Rishabh Singh
Laksh Singla
Zoltan Haindrich
Tejaswini Bandlamudi
AmatyaAvadhanula
Abhishek Radhakrishnan
Gian Merlino
Paul Rogers
Kashif Faraz
imply-cheddar
Sam Rash
Frank Chen
senthilkv