* Fix error message for groupByEnableMultiValueUnnesting.
It referred to the incorrect context parameter.
Also, create a dedicated exception class, to allow easier detection of this
specific error.
* Fix other test.
* More better error messages.
* Test getDimensionName method.
* upgrade Airline to Airline 2
https://github.com/airlift/airline is no longer maintained, updating to
https://github.com/rvesse/airline (Airline 2) to use an actively
maintained version, while minimizing breaking changes.
Note, this is a backwards incompatible change, and extensions relying on
the CliCommandCreator extension point will also need to be updated.
* fix dependency checks where jakarta.inject is now resolved first instead
of javax.inject, due to Airline 2 using jakarta
As part of #12078 one of the followup's was to have a specific config which does not allow accidental unnesting of multi value columns if such columns become part of the grouping key.
Added a config groupByEnableMultiValueUnnesting which can be set in the query context.
The default value of groupByEnableMultiValueUnnesting is true, therefore it does not change the current engine behavior.
If groupByEnableMultiValueUnnesting is set to false, the query will fail if it encounters a multi-value column in the grouping key.
* Moving in filter check to broker
* Adding more unit tests, making error message meaningful
* Spelling and doc changes
* Updating default to -1 and making this feature hide by default. The number of IN filters can grow upto a max limit of 100
* Removing upper limit of 100, updated docs
* Making documentation more meaningful
* Moving check outside to PlannerConfig, updating test cases and adding back max limit
* Updated with some additional code comments
* Missed removing one line during the checkin
* Addressing doc changes and one forbidden API correction
* Final doc change
* Adding a speling exception, correcting a testcase
* Reading entire filter tree to address combinations of ANDs and ORs
* Specifying in docs that, this case works only for ORs
* Revert "Reading entire filter tree to address combinations of ANDs and ORs"
This reverts commit 81ca8f8496.
* Covering a class cast exception and updating docs
* Counting changed
Co-authored-by: Jihoon Son <jihoonson@apache.org>
#12163 makes PARTITIONED BY a required clause in INSERT queries. While this is required, if a user accidentally omits the clause, it emits a JavaCC/Calcite error, since it's syntactically incorrect. The error message is cryptic. Since it's a custom clause, this PR aims to make the clause optional on the syntactic side, but move the validation to DruidSqlInsert where we can surface a friendlier error.
* rework sql planner expression and virtual column handling
* simplify a bit
* add back and deprecate old methods, more tests, fix multi-value string coercion bug and associated tests
* spotbugs
* fix bugs with multi-value string array expression handling
* javadocs and adjust test
* better
* fix tests
* array_concat_agg and array_agg support for array inputs
changes:
* added array_concat_agg to aggregate arrays into a single array
* added array_agg support for array inputs to make nested array
* added 'shouldAggregateNullInputs' and 'shouldCombineAggregateNullInputs' to fix a correctness issue with STRING_AGG and ARRAY_AGG when merging results, with dual purpose of being an optimization for aggregating
* fix test
* tie capabilities type to legacy mode flag about coercing arrays to strings
* oops
* better javadoc
* changes:
* remove SystemSchema duplicate ServerInventoryView in broker
* suppress duplicate segment added/removed warnings in HttpServerInventoryView when doing a full sync
* fixes
Fixes a bug because of which some SQL queries cannot be parsed using druid convention. Specifically, these queries translate to an inline datasource and have some null values. Calcite internally uses NULL as SQL type for these literals and that is not supported by the druid.
I am now allowing null column types to be returned while building RowSignature in org.apache.druid.sql.calcite.table.RowSignatures#fromRelDataType. RowSignature already allows null column type for any column. Doing so should also fix bindable queries such as select (1,2). When such queries are run with headers set to true, we get an exception in org.apache.druid.sql.http.ArrayWriter#writeHeader. This is again a similar exception to the one addressed in this PR. Because SQL type for the result column is RECORD and that doesn't have a corresponding columnType.
* init multiValue column group by
* Changing sorting to Lexicographic as default
* Adding initial tests
* 1.Fixing test cases adding
2.Optimized inmem structs
* Linking SQL layer to native layer
* Adding multiDimension support to group by column strategy
* 1. Removing array coercion in Calcite layer
2. Removing ResultRowDeserializer
* 1. Supporting all primitive array types
2. Removing dimension spec as part of columnSelector
* 1. Supporting all primitive array types
2. Removing dimension spec as part of columnSelector
* 1. Checkstyle things
2. Removing flag
* Minor naming things
* CheckStyle Things
* Fixing test case
* Fixing hashing
* 1. Adding the MV function
2. Added few test cases
* 1. Adding MV function test cases
* Adding Selector strategy function test cases
* Fixing ClientQuerySegmentWalkerTest
* Adding GroupByQueryRunnerTest test cases
* Fixing test cases
* Adding few more test cases
* Fixing Exception asset statement and intellij inspection
* Adding null compatibility tests
* Review comments
* Fixing few failing tests
* Fixing few failing tests
* Do no convert to topN Q incase of group by on array
* Fixing checkstyle
* Fixing differences between jdk's class cast exception message
* 1. Fixing ordering if the grouping key is an array
* Fixing DefaultLimitSpec
* Fixing CalciteArraysQueryTest
* Dummy commit for LGTM
* changes:
* only coerce multi-value string null values when `ExpressionPlan.Trait.NEEDS_APPLIED` is set
* correct return type inference for ARRAY_APPEND,ARRAY_PREPEND,ARRAY_SLICE,ARRAY_CONCAT
* fix bug with ExprEval.ofType when actual type of object from binding doesn't match its claimed type
* Review comments
* Fixing test cases
* Fixing spot bugs
* Fixing strict compile
Co-authored-by: Clint Wylie <cwylie@apache.org>
This PR changes the value of the property `druid.sql.planner.useGroupingSetForExactDistinct` from `false` to `true` in the runtime.properties files, so that newer installations have this property as `true`, while the default still remains as `false`.
The flag determines how queries which contain an aggregation over `DISTINCT` like `SELECT COUNT(DISTINCT foo.dim1) FILTER(WHERE foo.cnt = 1), SUM(foo.cnt) FROM druid.foo` get planned by Calcite. With the flag being set to false, it plans it via joins, whereas with it being set to true, the query is set using grouping sets.
There is a known issue with Calcite (https://github.com/apache/druid/issues/7953), where an NPE is thrown while planning the above query with joins. There is no such issue while planning the query using grouping sets.
* Pass VirtualColumnRegistry in PlannerContext for join expression planning
* Allow for including VCs from join fact table expression
* Optmize MV_FILTER functions to use a VC when in join fact table expression
* fixup! Allow for including VCs from join fact table expression
* Address review comments
Related to #11188
The above mentioned PR allowed timeseries queries to return a default result, when queries of type: select count(*) from table where dim1="_not_present_dim_" were executed. Before the PR, it returned no row, after the PR, it would return a row with value of count(*) as 0 (as expected by SQL standards of different dbs).
In Grouping#applyProject, we can sometimes perform optimization of a groupBy query to a timeseries query if possible (when the keys of the groupBy are constants, as generated by automated tools). For example, in select count(*) from table where dim1="_present_dim_" group by "dummy_key", the groupBy clause can be removed. However, in the case when the filter doesn't return anything, i.e. select count(*) from table where dim1="_not_present_dim_" group by "dummy_key", the behavior of general databases would be to return nothing, while druid (due to above change) returns an empty row. This PR aims to fix this divergence of behavior.
Example cases:
select count(*) from table where dim1="_not_present_dim_" group by "dummy_key".
CURRENT: Returns a row with count(*) = 0
EXPECTED: Return no row
select 'A', dim1 from foo where m1 = 123123 and dim1 = '_not_present_again_' group by dim1
CURRENT: Returns a row with ('A', 'wat')
EXPECTED: Return no row
To do this, a boolean droppedDimensionsWhileApplyingProject has been added to Grouping which is true whenever we make changes to the original shape with optimization. Hence if a timeseries query has a grouping with this set to true, we set skipEmptyBuckets=true in the query context (i.e. donot return any row).
DruidLogicalValuesRule while transforming to DruidRel can return incorrect values, if during the creation of the literal it was created from a float value. The BigDecimal representation stores 123.0, and it seems that using RexLiteral's method while conversion returns the inflated value (which is 1230). I am unsure if this is intentional from Calcite's perspective, and the actual change should be done somewhere else.
Extract the values of INT/LONG from the RexLiteral in the DruidLogicalValuesRule, via BigDecimal.longValue() method.
changes:
* IncrementalIndex is now a ColumnInspector
* fixes performance regression from using map of ColumnCapabilities from IncrementalIndex as a RowSignature
In this PR, we will now return 400 instead of 500 when SQL query cannot be planned. I also fixed a bug where error messages were not getting sent to the users in case the rules throw UnsupportSQLQueryException.
DruidSchema consists of a concurrent HashMap of DataSource -> Segement -> AvailableSegmentMetadata. AvailableSegmentMetadata contains RowSignature of the segment, and for each segment, a new object is getting created. RowSignature is an immutable class, and hence it can be interned, and this can lead to huge savings of memory being used in broker, since a lot of the segments of a table would potentially have same RowSignature.
This PR does two things
1. It adds the capability to surface missing features in SQL to users - The calcite planner will explore through multiple rules to convert a logical SQL query to a druid native query. Some rules change the shape of the query itself, optimize it and some rules are responsible for translating the query into a druid native query. These are DruidQueryRule, DruidOuterQueryRule, DruidJoinRule, DruidUnionDataSourceRule, DruidUnionRule etc. These rules will look at SQL and will do the necessary transformation. But if the rule can't transform the query, it returns back the control to the calcite planner without recording why was it not able to transform. E.g. there is a join query with a non-equal join condition. DruidJoinRule will look at the condition, see that it is not supported, and return back the control. The reason can be that a query can be planned in many different ways so if one rule can't parse it, the query may still be parseable by other rules. In this PR, we are intercepting these gaps and passing them back to the user if the query could not be planned at all.
2. The said capability has been used to generate actionable errors for some common unsupported SQL features. However, not all possible errors are covered and we can keep adding more in the future.
Druid currently has 2 serverViews, regular serverView and filtered serverView. The regular serverView is used to monitor all segment announcements from all data nodes (historicals, tasks, indexers). The filtered serverView is used when you want to watch segment announcements from particular tiers. Since these server views keep track of different sets of druidServers and segments in memory, they should be maintained separately. However, they currently share the same name for their executorService, which can cause confusion and make debugging harder especially in the broker since it is using both serverViews, the filtered view for normal query processing and the regular view to serve the servers table (I'm unsure whether this is intended or whether this is a good behavior). This PR changes it to a more obvious name.
This PR also removes SingleServerInventoryView. This view was deprecated a long time ago and has not been documented at least since 0.13 (#6127). I also don't think this can be better in any case than BatchServerInventoryView. Finally, I merged AbstractCuratorServerInventoryView and BatchServerInventoryView as we no longer need AbstractCuratorServerInventoryView after SingleServerInventoryView is removed.
* Enhancements to IndexTaskClient.
1) Ability to use handlers other than StringFullResponseHandler. This
functionality is not used in production code yet, but is useful
because it will allow tasks to communicate with each other in
non-string-based formats and in streaming fashion. In the future,
we'll be able to use this to make task-to-task communication
more efficient.
2) Truncate server errors at 1KB, so long errors do not pollute logs.
3) Change error log level for retryable errors from WARN to INFO. (The
final error is still WARN.)
4) Harmonize log and exception messages to have a more consistent format.
* Additional tests and improvements.
* allow `DruidSchema` to fallback to segment metadata type if typeSignature is null, to avoid producing incorrect SQL schema if broker is upgraded to 0.23 before historicals
* mmm, forbidden tests
changes:
* adds new config, druid.expressions.useStrictBooleans which make longs the official boolean type of all expressions
* vectorize logical operators and boolean functions, some only if useStrictBooleans is true
* Code cleanup from query profile project
* Fix spelling errors
* Fix Javadoc formatting
* Abstract out repeated test code
* Reuse constants in place of some string literals
* Fix up some parameterized types
* Reduce warnings reported by Eclipse
* Reverted change due to lack of tests
Currently, when we try to do EXPLAIN PLAN FOR, it returns the structure of the SQL parsed (via Calcite's internal planner util), which is verbose (since it tries to explain about the nodes in the SQL, instead of the Druid Query), and not representative of the native Druid query which will get executed on the broker side.
This PR aims to change the format when user tries to EXPLAIN PLAN FOR for queries which are executed by converting them into Druid's native queries (i.e. not sys schemas).
Add the ability to pass time column in first/last aggregator (and latest/earliest SQL functions). It is to support cases where the time to query upon is stored as a part of a column different than __time. Also, some other logical time column can be specified.
* SQL INSERT planner support.
The main changes are:
1) DruidPlanner is able to validate and authorize INSERT queries. They
require WRITE permission on the target datasource.
2) QueryMaker is now an interface, and there is a QueryMakerFactory that
creates instances of it. There is only one production implementation
of each (NativeQueryMaker and NativeQueryMakerFactory), which
together behave the same way as the former QueryMaker class. But this
opens the door to executing queries in ways other than the Druid
query stack, and is used by unit tests (CalciteInsertDmlTest) to
test the INSERT planning functionality.
3) Adds an EXTERN table macro that allows references external data using
InputSource and InputFormat from Druid's batch ingestion API. This is
not exposed in production yet, but is used by unit tests.
4) Adds a QueryFeature concept that enables the planner to change its
behavior slightly depending on the capabilities of the execution
system.
5) Adds an "AuthorizableOperator" concept that enables SqlOperators
to require additional permissions. This is used by the EXTERN table
macro.
Related odds and ends:
- Add equals, hashCode, toString methods to InlineInputSource. Aids in
the "from external" tests in CalciteInsertDmlTest.
- Add JSON-serializability to RowSignature.
- Move the SQL string inside PlannerContext so it is "baked into" the
planner when the planner is created. Cleans up the code a bit, since
in practice, the same query is passed in every time to the
same planner anyway.
* Fix up calls to CalciteTests.createMockQueryLifecycleFactory.
* Fix checkstyle issues.
* Adjustments for CI.
* Adjust DruidAvaticaHandlerTest for stricter test authorizations.
* add impl
* fix checkstyle
* add test
* add test
* add unit tests
* fix unit tests
* fix unit tests
* fix unit tests
* add IT
* add IT
* add comments
* fix spelling
DruidRexExecutor while reducing Arrays, specially numeric arrays, doesn't convert the value from ExprResult's type to BigDecimal, which causes makeLiteral to cast the values. Also, if NaN or Infinite values are present in the array, the error is a generic NumberFormatException. For example:
SELECT ARRAY[1.11, 2.22] returns [1, 2]
SELECT SQRT(-1) throws a generic NumberFormatException instead of IAE
This PR introduces change to cast the numeric values to BigDecimal since Calcite's library understands that easily, and doesn't perform casts.
Gian Merlino
Rohan Garg
Clint Wylie
Xavier Léauté
Jihoon Son
Jonathan Wei
Karan Kumar
Laksh Singla
somu-imply
Maytas Monsereenusorn
Abhishek Agarwal
Gian Merlino
Paul Rogers
Kashif Faraz
TSFenwick