* 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.
* Scan: Add "orderBy" parameter.
This patch adds an API for requesting non-time orderings, although it
does not actually add the ability to execute such queries.
The changes are done in such a way that no matter how Scan query objects
are constructed, they will have a correct "getOrderBy". This will enable
us to switch the execution to exclusively use "getOrderBy" later on when
it's implemented.
Scan queries are serialized such that they only include "order" (time
order) if the ordering is time-based, and they only include "orderBy" if
the ordering is non-time-based. This maximizes compatibility with
the existing API while also providing a clean look for formatted queries.
Because this patch does not include execution logic, if someone actually
tries to run a query with non-time ordering, then they will get an error
like "Cannot execute query with orderBy [quality ASC]".
* SQL module fixes.
* Add spotbugs-exclude.
* Remove unused method.
* IMPLY-4344: Adding safe divide function along with testcases and documentation updates
* Changing based on review comments
* Addressing review comments, fixing coding style, docs and spelling
* Checkstyle passes for all code
* Fixing expected results for infinity
* Revert "Fixing expected results for infinity"
This reverts commit 5fd5cd480d.
* Updating test result and a space in docs
Unlike a real one, TestServerInventoryView would call segmentRemoved
any time _any_ segment was removed. It should only be called when _all_
segments have been removed.
* Use a simple class to sanitize sanitizable errors and log them
The purpose of this is to sanitize JDBC errors, but can sanitize other errors
if they implement SanitizableError Interface
add a class to log errors and sanitize them
added a simple test that tests out that the error gets sanitized
add @NonNull annotation to serverconfig's ErrorResponseTransfromStrategy
* return less information as part of too many connections, and instead only log specific details
This is so an end user gets relevant information but not too much info since they might now how
many brokers they have
* return only runtime exceptions
added new error types that need to be sanitized
also sanitize deprecated and unsupported exceptions.
* dont reqrewite exceptions unless necessary for checked exceptions
add docs
avoid blanket turning all exceptions into runtime exceptions
* address comments, to fix up docs.
add more javadocs
add support UOE sanitization
* use try catch instead and sanitize at public methods
* checkstyle fixes
* throw noSuchStatement and NoSuchConnection as Avatica is affected by those
* address comments. move log error back to druid meta
clean up bad formatting and commented code. add missed catch for NoSuchStatementException
clean up comments for error handler and add comment explainging not wanting to santize avatica exceptions
* alter test to reflect new error message
* revert ColumnAnalysis type, add typeSignature and use it for DruidSchema
* review stuffs
* maybe null
* better maybe null
* Update docs/querying/segmentmetadataquery.md
* Update docs/querying/segmentmetadataquery.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* fix null right
* sad
* oops
* Update batch_hadoop_queries.json
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* add missing json type for ListFilteredVirtualColumn, and tests to try to avoid this happening again
* fixes
* ugly, but maybe this
* oops
* too many mappers
* complex typed expressions
* add built-in hll collector expressions to get coverage on druid-processing, more types, more better
* rampage!!!
* more javadoc
* adjustments
* oops
* lol
* remove unused dependency
* contradiction?
* more test
* Add druid.sql.approxCountDistinct.function property.
The new property allows admins to configure the implementation for
APPROX_COUNT_DISTINCT and COUNT(DISTINCT expr) in approximate mode.
The motivation for adding this setting is to enable site admins to
switch the default HLL implementation to DataSketches.
For example, an admin can set:
druid.sql.approxCountDistinct.function = APPROX_COUNT_DISTINCT_DS_HLL
* Fixes
* Fix tests.
* Remove erroneous cannotVectorize.
* Remove unused import.
* Remove unused test imports.
* Revert "Require Datasource WRITE authorization for Supervisor and Task access (#11718)"
This reverts commit f2d6100124.
* Revert "Require DATASOURCE WRITE access in SupervisorResourceFilter and TaskResourceFilter (#11680)"
This reverts commit 6779c4652d.
* Fix docs for the reverted commits
* Fix and restore deleted tests
* Fix and restore SystemSchemaTest
* SQL: Allow Scans to be used as outer queries.
This has been possible in the native query system for a while, but the capability
hasn't yet propagated into the SQL layer. One example of where this is useful is
a query like:
SELECT * FROM (... LIMIT X) WHERE <filter>
Because this expands the kinds of subquery structures the SQL layer will consider,
it was also necessary to improve the cost calculations. These changes appear in
PartialDruidQuery and DruidOuterQueryRel. The ideas are:
- Attach per-column penalties to the output signature of each query, instead of to
the initial projection that starts a query. This encourages moving projections
into subqueries instead of leaving them on outer queries.
- Only attach penalties to projections if there are actually expressions happening.
So, now, projections that simply reorder or remove fields are free.
- Attach a constant penalty to every outer query. This discourages creating them
when they are not needed.
The changes are generally beneficial to the test cases we have in CalciteQueryTest.
Most plans are unchanged, or are changed in purely cosmetic ways. Two have changed
for the better:
- testUsingSubqueryWithLimit now returns a constant from the subquery, instead of
returning every column.
- testJoinOuterGroupByAndSubqueryHasLimit returns a minimal set of columns from
the innermost subquery; two unnecessary columns are no longer there.
* Fix various DS operator conversions.
These were all implemented as direct conversions, which isn't appropriate
because they do not actually map onto native functions. These are only
usable as post-aggregations.
* Test case adjustment.
* better type system
* needle in a haystack
* ColumnCapabilities is a TypeSignature instead of having one, INFORMATION_SCHEMA support
* fixup merge
* more test
* fixup
* intern
* fix
* oops
* oops again
* ...
* more test coverage
* fix error message
* adjust interning, more javadocs
* oops
* more docs more better
Follow up PR for #11680
Description
Supervisor and Task APIs are related to ingestion and must always require Datasource WRITE
authorization even if they are purely informative.
Changes
Check Datasource WRITE in SystemSchema for tables "supervisors" and "tasks"
Check Datasource WRITE for APIs /supervisor/history and /supervisor/{id}/history
Check Datasource for all Indexing Task APIs
* Add the ability to add a context to internally generated druid broker queries
* fix docs
* changes after first CI failure
* cleanup after merge with master
* change default to empty map and improve unit tests
* add doc info and fix checkstyle
* refactor DruidSchema#runSegmentMetadataQuery and add a unit test
* refactor sql authorization to get resource type from schema, refactor resource type from enum to string
* information schema auth filtering adjustments
* refactor
* minor stuff
* Update SqlResourceCollectorShuttle.java
* add MV_FILTER_ONLY SQL function, and list filter virtual column
* MV_FILTER_NONE and more tests
* formatting
* o yeah, forgot can do easy thing
* style
* hmm why was that there
* test filtering on virtual column
* style
* meh
* do it right
* good bot
The SQL "array" and "object" formats are intended to return invalid JSON
(lacking a ] terminator) if an error occurs midstream. This enables callers
to detect truncated responses. But JsonGenerators, by default, close JSON
arrays even when not explicitly told to.
This patch disables automatic array closing, which fixes the problem with
truncated response detection. It also adds tests for truncated responses
for all result formats.
* initial work
* reduce lock in sqlLifecycle
* Integration test for sql canceling
* javadoc, cleanup, more tests
* log level to debug
* fix test
* checkstyle
* fix flaky test; address comments
* rowTransformer
* cancelled state
* use lock
* explode instead of noop
* oops
* unused import
* less aggressive with state
* fix calcite charset
* don't emit metrics when you are not authorized
* Configurable maxStreamLength for doubles sketches
* fix equals/hashcode and it test failure
* fix test
* fix it test
* benchmark
* doc
* grouping key
* fix comment
* dependency check
* Update docs/development/extensions-core/datasketches-quantiles.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* add binary_byte_format/decimal_byte_format/decimal_format
* clean code
* fix doc
* fix review comments
* add spelling check rules
* remove extra param
* improve type handling and null handling
* remove extra zeros
* fix tests and add space between unit suffix and number as most size-format functions do
* fix tests
* add examples
* change function names according to review comments
* fix merge
Signed-off-by: frank chen <frank.chen021@outlook.com>
* no need to configure NullHandling explicitly for tests
Signed-off-by: frank chen <frank.chen021@outlook.com>
* fix tests in SQL-Compatible mode
Signed-off-by: frank chen <frank.chen021@outlook.com>
* Resolve review comments
* Update SQL test case to check null handling
* Fix intellij inspections
* Add more examples
* Fix example
* Improve concurrency between DruidSchema and BrokerServerView
* unused imports and workaround for error prone faiure
* count only known segments
* add comments
This PR fixes the incorrect results for query :
SELECT dim1, l1.k FROM foo LEFT JOIN (select k || '' as k from lookup.lookyloo group by 1) l1 ON foo.dim1 = l1.k WHERE l1.k IS NOT NULL (in CalciteQueryTests)
In the current code, the WHERE clause gets removed from the top of the left join and is pushed to the table foo
leading to incorrect results.
The fix for such a situation is done by :
Converting such left joins into inner joins (since logically the mentioned left join query is equivalent to an inner join) using Calcite while maintaining that the druid execution layer can execute such inner joins.
Preferring converted inner joins over original left joins in our cost model
This PR splits current SegmentLoader into SegmentLoader and SegmentCacheManager.
SegmentLoader - this class is responsible for building the segment object but does not expose any methods for downloading, cache space management, etc. Default implementation delegates the download operations to SegmentCacheManager and only contains the logic for building segments once downloaded. . This class will be used in SegmentManager to construct Segment objects.
SegmentCacheManager - this class manages the segment cache on the local disk. It fetches the segment files to the local disk, can clean up the cache, and in the future, support reserve and release on cache space. [See https://github.com/Make SegmentLoader extensible and customizable #11398]. This class will be used in ingestion tasks such as compaction, re-indexing where segment files need to be downloaded locally.
* improve groupBy query granularity translation when issued from sql layer
* fix style
* use virtual column to determine timestampResult granularity
* dont' apply postaggregators on compute nodes
* relocate constants
* fix order by correctness issue
* fix ut
* use more easier understanding code in DefaultLimitSpec
* address comment
* rollback use virtual column to determine timestampResult granularity
* fix style
* fix style
* address the comment
* add more detail document to explain the tradeoff
* address the comment
* address the comment
Users sometimes make typos when picking timezones - like `America/Los Angeles`
instead of `America/Los_Angeles` instead of defaulting to UTC, this change
makes it so that an error is thrown instead notifying the user of their mistake.
A constant expression may evaluate to Double.NEGATIVE_INFINITY/Double.POSITIVE_INFINITY/Double.NAN e.g. log10(0). When using such an expression in native queries, the user will get the corresponding value without any error. In SQL, however, the user will run into NumberFormatException because we convert the double to big-decimal while constructing a literal numeric expression. This probably should be fixed in calcite - see https://issues.apache.org/jira/browse/CALCITE-2067. This PR adds a verbose error message so that users can take corrective action without scratching their heads.
* add single input string expression dimension vector selector and better expression planning
* better
* fixes
* oops
* rework how vector processor factories choose string processors, fix to be less aggressive about vectorizing
* oops
* javadocs, renaming
* more javadocs
* benchmarks
* use string expression vector processor with vector size 1 instead of expr.eval
* better logging
* javadocs, surprising number of the the
* more
* simplify
* Fix is null selector returning incorrect value for Long data type
* Fix style errors
* Refactor getObject method to also cache null column values
* Make lastInput variable nullable
* Refactor unit test
* Use new boolean lastInputIsNull instead of Long for lastInput to avoid boxing
* Refactor to remove Long for input variable
* Make a separate null caching variable
* Cleaner null caching implementation
* fix count and average SQL aggregators on constant virtual columns
* style
* even better, why are we tracking virtual columns in aggregations at all if we have a virtual column registry
* oops missed a few
* remove unused
* this will fix it
* SQL timeseries no longer skip empty buckets with all granularity
* add comment, fix tests
* the ol switcheroo
* revert unintended change
* docs and more tests
* style
* make checkstyle happy
* docs fixes and more tests
* add docs, tests for array_agg
* fixes
* oops
* doc stuffs
* fix compile, match doc style
* Fix vectorized cardinality bug on certain string columns.
Fixes a bug introduced in #11182, related to the fact that in some cases,
ColumnProcessors.makeVectorProcessor will call "makeObjectProcessor"
instead of "makeSingleValueDimensionProcessor" or
"makeMultiValueDimensionProcessor". CardinalityVectorProcessorFactory
improperly ignored calls to "makeObjectProcessor".
In addition to fixing the bug, I added this detail to the javadocs for
VectorColumnProcessorFactory, to prevent others from running into the
same thing in the future. They do not currently call out this case.
* Improve test coverage.
* Additional fixes.
* ARRAY_AGG sql aggregator function
* add javadoc
* spelling
* review stuff, return null instead of empty when nil input
* review stuff
* Update sql.md
* use type inference for finalize, refactor some things
* Vectorize the cardinality aggregator.
Does not include a byRow implementation, so if byRow is true then
the aggregator still goes through the non-vectorized path.
Testing strategy:
- New tests that exercise both styles of "aggregate" for supported types.
- Some existing tests have also become active (note the deleted
"cannotVectorize" lines).
* Adjust whitespace.
* Enable rewriting certain inner joins as filters.
The main logic for doing the rewrite is in JoinableFactoryWrapper's
segmentMapFn method. The requirements are:
- It must be an inner equi-join.
- The right-hand columns referenced by the condition must not contain any
duplicate values. (If they did, the inner join would not be guaranteed
to return at most one row for each left-hand-side row.)
- No columns from the right-hand side can be used by anything other than
the join condition itself.
HashJoinSegmentStorageAdapter is also modified to pass through to
the base adapter (even allowing vectorization!) in the case where 100%
of join clauses could be rewritten as filters.
In support of this goal:
- Add Query getRequiredColumns() method to help us figure out whether
the right-hand side of a join datasource is being used or not.
- Add JoinConditionAnalysis getRequiredColumns() method to help us
figure out if the right-hand side of a join is being used by later
join clauses acting on the same base.
- Add Joinable getNonNullColumnValuesIfAllUnique method to enable
retrieving the set of values that will form the "in" filter.
- Add LookupExtractor canGetKeySet() and keySet() methods to support
LookupJoinable in its efforts to implement the new Joinable method.
- Add "enableRewriteJoinToFilter" feature flag to
JoinFilterRewriteConfig. The default is disabled.
* Test improvements.
* Test fixes.
* Avoid slow size() call.
* Remove invalid test.
* Fix style.
* Fix mistaken default.
* Small fixes.
* Fix logic error.
* add round test
* code style
* handle null val for round function
* handle null val for round function
* support null for round
* fix compatiblity
* fix test
* fix test
* code style
* optimize format
* Add a planner rule to handle empty tables
* adjust comment
* type handling
* add tests
* unused imports and fix test
* fix more tests
* fix more test
* javadoc
Size HashMap and HashSet appropriately. Perf analysis of the queries
revealed that over 25% of the query time was spent in resizing HashMap and HashSet
collections. Also, prevent the need to examine and authorize all resources when
AllowAllAuthorizer is the configured authorizer.
* expression filter support for vectorized query engines
* remove unused codes
* more tests
* refactor, more tests
* suppress
* more
* more
* more
* oops, i was wrong
* comment
* remove decorate, object dimension selector, more javadocs
* style
* fix SQL issue for group by queries with time filter that gets optimized to false
* short circuit always false in CombineAndSimplifyBounds
* adjust
* javadocs
* add preconditions for and/or filters to ensure they have children
* add comments, remove preconditions
* where filter left first draft
* Revert changes in calcite test
* Refactor a bit
* Fixing the Tests
* Changes
* Adding tests
* Add tests for correlated queries
* Add comment
* Fix typos
* add druid jdbc handler config for minimum number of rows per frame
* javadocs and docs adjustments
* spelling
* adjust docs per review with minor tweaks
* adjust more
* Support segmentGranularity for auto-compaction
* Support segmentGranularity for auto-compaction
* Support segmentGranularity for auto-compaction
* Support segmentGranularity for auto-compaction
* resolve conflict
* Support segmentGranularity for auto-compaction
* Support segmentGranularity for auto-compaction
* fix tests
* fix more tests
* fix checkstyle
* add unit tests
* fix checkstyle
* fix checkstyle
* fix checkstyle
* add unit tests
* add integration tests
* fix checkstyle
* fix checkstyle
* fix failing tests
* address comments
* address comments
* fix tests
* fix tests
* fix test
* fix test
* fix test
* fix test
* fix test
* fix test
* fix test
* fix test
* before i leaped i should've seen, the view from halfway down
* fixes
* fixes, more test
* rename
* fix style
* further refactoring
* review stuffs
* rename
* more javadoc and comments
* enhance the logic of Start up DruidSchema immediately if there are no segments.
* add UT to test DruidSchema init
Co-authored-by: yuezhang <yuezhang@freewheel.tv>
* Tidy up query error codes
* fix tests
* Restore query exception type in JsonParserIterator
* address review comments; add a comment explaining the ugly switch
* fix test
* integration test for coordinator and overlord leadership, added sys.servers is_leader column
* docs
* remove not needed
* fix comments
* fix compile heh
* oof
* revert unintended
* fix tests, split out docker-compose file selection from starting cluster, use docker-compose down to stop cluster
* fixes
* style
* dang
* heh
* scripts are hard
* fix spelling
* fix thing that must not matter since was already wrong ip, log when test fails
* needs more heap
* fix merge
* less aggro
* fix race condition with DruidSchema tables and dataSourcesNeedingRebuild
* rework to see if it passes analysis
* more better
* maybe this
* re-arrange and comments
* First draft of grouping_id function
* Add more tests and documentation
* Add calcite tests
* Fix travis failures
* bit of a change
* Add documentation
* Fix typos
* typo fix
* Two fixes related to encoding of % symbols.
1) TaskResourceFilter: Don't double-decode task ids. request.getPathSegments()
returns already-decoded strings. Applying StringUtils.urlDecode on
top of that causes erroneous behavior with '%' characters.
2) Update various ThreadFactoryBuilder name formats to escape '%'
characters. This fixes situations where substrings starting with '%'
are erroneously treated as format specifiers.
ITs are updated to include a '%' in extra.datasource.name.suffix.
* Avoid String.replace.
* Work around surefire bug.
* Fix xml encoding.
* Another try at the proper encoding.
* Give up on the emojis.
* Less ambitious testing.
* Fix an additional problem.
* Adjust encodeForFormat to return null if the input is null.
* support for vectorizing expressions with non-existent inputs, more consistent type handling for non-vectorized expressions
* inspector
* changes
* more test
* clean
* fix JSON format
* Change all columns in sys segments to be JSON
* Change all columns in sys segments to be JSON
* add tests
* fix failing tests
* fix failing tests
* vectorize remaining math expressions
* fixes
* remove cannotVectorize() where no longer true
* disable vectorized groupby for numeric columns with nulls
* fixes
* push down ValueType to ExprType conversion, tidy up
* determine expr output type for given input types
* revert unintended name change
* add nullable
* tidy up
* fixup
* more better
* fix signatures
* naming things is hard
* fix inspection
* javadoc
* make default implementation of Expr.getOutputType that returns null
* rename method
* more test
* add output for contains expr macro, split operation and function auto conversion
* Add IndexMergerRollupTest
This changelist adds a test to merge indexes with StringFirst/StringLast aggregator.
* Fix StringFirstAggregateCombiner/StringLastAggregateCombiner
The segment-level type for stringFirst/stringLast is SerializablePairLongString,
not String. This changelist fixes it.
* Fix EarliestLatestAnySqlAggregator to handle COMPLEX type
This changelist allows EarliestLatestAnySqlAggregator to accept COMPLEX
type as an operand. For its return type, we set it to VARCHAR, since
COMPLEX column is only generated by stringFirst/stringLast during ingestion
rollup.
* Return value with smaller timestamp in StringFirstAggregatorFactory.combine function
* Add integration tests for stringFirst/stringLast during ingestion
* Use one EarliestLatestReturnTypeInference instance
Co-authored-by: Joy Kent <joy@automonic.ai>
* SQL support for union datasources.
Exposed via the "UNION ALL" operator. This means that there are now two
different implementations of UNION ALL: one at the top level of a query
that works by concatenating subquery results, and one at the table level
that works by creating a UnionDataSource.
The SQL documentation is updated to discuss these two use cases and how
they behave.
Future work could unify these by building support for a native datasource
that represents the union of multiple subqueries. (Today, UnionDataSource
can only represent the union of tables, not subqueries.)
* Fixes.
* Error message for sanity check.
* Additional test fixes.
* Add some error messages.
* better type tracking: add typed postaggs, finalized types for agg factories
* more javadoc
* adjustments
* transition to getTypeName to be used exclusively for complex types
* remove unused fn
* adjust
* more better
* rename getTypeName to getComplexTypeName
* setup expression post agg for type inference existing
* more javadocs
* fixup
* oops
* more test
* more test
* more comments/javadoc
* nulls
* explicitly handle only numeric and complex aggregators for incremental index
* checkstyle
* more tests
* adjust
* more tests to showcase difference in behavior
* timeseries longsum array
* Add SQL "OFFSET" clause.
Under the hood, this uses the new offset features from #10233 (Scan)
and #10235 (GroupBy). Since Timeseries and TopN queries do not currently
have an offset feature, SQL planning will switch from one of those to
Scan or GroupBy if users add an OFFSET.
Includes a refactoring to harmonize offset and limit planning using an
OffsetLimit wrapper class. This is useful because it ensures that the
various places that need to deal with offset and limit collapsing all
behave the same way, using its "andThen" method.
* Fix test and add another test.
* Segment backed broadcast join IndexedTable
* fix comments
* fix tests
* sharing is caring
* fix test
* i hope this doesnt fix it
* filter by schema to maybe fix test
* changes
* close join stuffs so it does not leak, allow table to directly make selector factory
* oops
* update comment
* review stuffs
* better check
* remove DruidLeaderClient.goAsync(..) that does not follow redirect.
Replace its usage by DruidLeaadereClient.go(..) with
InputStreamFullResponseHandler
* remove ByteArrayResponseHolder dependency from JsonParserIterator
* add UT to cover lines in InputStreamFullResponseHandler
* refactor SystemSchema to reduce branches
* further reduce branches
* Revert "add UT to cover lines in InputStreamFullResponseHandler"
This reverts commit 330aba3dd9.
* UTs for InputStreamFullResponseHandler
* remove unused imports
* Add "offset" parameter to the Scan query.
It works by doing the query as normal and then throwing away the first
"offset" number of rows on the broker.
* Fix constructor call.
* Fix up JSONs.
* Fix call to ScanQuery.
* Doc update.
* Fix javadocs.
* Spotbugs, LGTM suppressions.
* Javadocs.
* Fix suppression.
* Stabilize Scan query result order, add tests.
* Update LGTM comment.
* Fixup.
* Test different batch sizes too.
* Nicer tests.
* Fix comment.
* LongMaxVectorAggregator support and test case.
* DoubleMinVectorAggregator and test cases.
* DoubleMaxVectorAggregator and unit test.
* FloatMinVectorAggregator and FloatMaxVectorAggregator.
* Documentation update to include the other vector aggregators.
* Bug fix.
* checkstyle formatting fixes.
* CalciteQueryTest cases update.
* Separate test classes for FloatMaxAggregation and FloatMniAggregation.
* remove the cannotVectorize for float max/min aggregator in test.
* Tests in GroupByQueryRunner, GroupByTimeseriesQueryRunner and TimeseriesQueryRunner.
* Add "offset" parameter to GroupBy query.
It works by doing the query as normal and then throwing away the first
"offset" number of rows on the broker.
* Stabilize GroupBy sorts.
* Fix inspections.
* Fix suppression.
* Fixups.
* Move TopNSequence to druid-core.
* Addl comments.
* NumberedElement equals verification.
* Changes from review.
* Fix minor formatting in docs.
* Add Nullhandling initialization for test to run from IDE.
* Vectorize longMin aggregator.
- A new vectorized class for the vectorized long min aggregator.
- Changes to AggregatorFactory to support vectorize functionality.
- Few changes to schema evolution test to add LongMinAggregatorFactory.
* Add longSum to the supported vectorized aggregator implementations.
* Add MIN() long min to calcite query test that can vectorize.
* Add simple long aggregations test.
* Fixup formatting per checkstyle guide.
* fixup and add more tests for long min aggregator.
* Override test for groupBy since timestamps are handled differently.
* Null compatibility check in test.
* Review comment: Add a test case to LongMinAggregationTest.
* Fix timeseries query constructor when postAggregator has an expression reading timestamp result column
* fix npe
* Fix postAgg referencing timestampResultField and add a test for it
* fix test
* doc
* revert doc
* new average aggregator
* method to create count aggregator factory
* test everything
* update other usages
* fix style
* fix more tests
* fix datasketches tests
* Ensure that join filter pre-analysis operates on optimized filters, add DimFilter.toOptimizedFilter
* Remove aggressive equality check that was used for testing
* Use Suppliers.memoize
* Checkstyle
* ROUND and having comparators correctly handle doubles
Double.NaN, Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY are not real
numbers. Because of this, they can not be converted to BigDecimal and instead
throw a NumberFormatException.
This change adds support for calculations that produce these numbers either
for use in the `ROUND` function or the HavingSpecMetricComparator by not
attempting to convert the number to a BigDecimal.
The bug in ROUND was first introduced in #7224 where we added the ability to
round to any decimal place. This PR changes the behavior back to using
`Math.round` if we recognize a number that can not be converted to a
BigDecimal.
* Add tests and fix spellcheck
* update error message in ExpressionsTest
* Address comments
* fix up round for infinity
* round non numeric doubles returns a double
* fix spotbugs
* Update docs/misc/math-expr.md
* Update docs/querying/sql.md
* make joinables closeable
* tests and adjustments
* refactor to make join stuffs impelement ReferenceCountedObject instead of Closable, more tests
* fixes
* javadocs and stuff
* fix bugs
* more test
* fix lgtm alert
* simplify
* fixup javadoc
* review stuffs
* safeguard against exceptions
* i hate this checkstyle rule
* make IndexedTable extend Closeable
* fix groupBy with literal in subquery grouping
* fix groupBy with literal in subquery grouping
* fix groupBy with literal in subquery grouping
* address comments
* update javadocs
* Fix join
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* Fix Subquery could not be converted to groupBy query
* add tests
* address comments
* fix failing tests
* Add REGEXP_LIKE, fix empty-pattern bug in REGEXP_EXTRACT.
- Add REGEXP_LIKE function that returns a boolean, and is useful in
WHERE clauses.
- Fix REGEXP_EXTRACT return type (should be nullable; causes incorrect
filter elision).
- Fix REGEXP_EXTRACT behavior for empty patterns: should always match
(previously, they threw errors).
- Improve error behavior when REGEXP_EXTRACT and REGEXP_LIKE are passed
non-literal patterns.
- Improve documentation of REGEXP_EXTRACT.
* Changes based on PR review.
* Fix arg check.
* Important fixes!
* Add speller.
* wip
* Additional tests.
* Fix up tests.
* Add validation error tests.
* Additional tests.
* Remove useless call.
* Refactor JoinFilterAnalyzer
This patch attempts to make it easier to follow the join filter analysis code
with the hope of making it easier to add rewrite optimizations in the future.
To keep the patch small and easy to review, this is the first of at least 2
patches that are planned.
This patch adds a builder to the Pre-Analysis, so that it is easier to
instantiate the preAnalysis. It also moves some of the filter normalization
code out to Fitlers with associated tests.
* fix tests
* Refactor JoinFilterAnalyzer - part 2
This change introduces the following components:
* RhsRewriteCandidates - a wrapper for a list of candidates and associated
functions to operate on the set of candidates.
* JoinableClauses - a wrapper for the list of JoinableClause that represent
a join condition and the associated functions to operate on the clauses.
* Equiconditions - a wrapper representing the equiconditions that are used
in the join condition.
And associated test changes.
This refactoring surfaced 2 bugs:
- Missing equals and hashcode implementation for RhsRewriteCandidate, thus
allowing potential duplicates in the rhs rewrite candidates
- Missing Filter#supportsRequiredColumnRewrite check in
analyzeJoinFilterClause, which could result in UnsupportedOperationException
being thrown by the filter
* fix compile error
* remove unused class
* Refactor JoinFilterAnalyzer - Correlations
Move the correlation related code out into it's own class so it's easier
to maintain.
Another patch should follow this one so that the query path uses the
correlation object instead of it's underlying maps.
* Optimize join queries where filter matches nothing
Fixes#9787
This PR changes the Joinable interface to return an Optional set of correlated
values for a column.
This allows the JoinFilterAnalyzer to differentiate between the case where the
column has no matching values and when the column could not find matching
values.
This PR chose not to distinguish between cases where correlated values could
not be computed because of a config that has this behavior disabled or because
of user error - like a column that could not be found. The reasoning was that
the latter is likely an error and the non filter pushdown path will surface the
error if it is.
* Add ingestion specs for CalciteQueryTests
This PR introduces ingestion specs that can be used for local testing
so that CalciteQueryTests can be built on a druid cluster.
* Add README
* Update sql/src/test/resources/calcite/tests/README.md
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* Bad plan for table-lookup-lookup join with filter on first lookup and outer limit
* address comments
* address comments
* fix checkstyle
* address comments
* address comments
* Fix potential NPEs in joins
intelliJ reported issues with potential NPEs. This was first hit in testing
with a filter being pushed down to the left hand table when joining against
an indexed table.
* More null check cleanup
* Optimize filter value rewrite for IndexedTable
* Add unit tests for LookupJoinable
* Add tests for IndexedTableJoinable
* Add non null assert for dimension selector
* Supress null warning in LookupJoinMatcher
* remove some null checks on hot path
* fix issue with group by limit pushdown for extractionFn, expressions, joins, etc
* remove unused
* fix test
* revert unintended change
* more tests
* consider capabilities for StringGroupByColumnSelectorStrategy
* fix test
* fix and more test
* revert because im scared
* SQL: More straightforward handling of join planning.
Two changes that simplify how joins are planned:
1) Stop using JoinProjectTransposeRule as a way of guiding subquery
removal. Instead, add logic to DruidJoinRule that identifies removable
subqueries and removes them at the point of creating a DruidJoinQueryRel.
This approach reduces the size of the planning space and allows the
planner to complete quickly.
2) Remove rules that reorder joins. Not because of an impact on the
planning time (it seems minimal), but because the decisions that the
planner was making in the new tests were sometimes worse than the
user-provided order. I think we'll need to go with the user-provided
order for now, and revisit reordering when we can add more smarts to
the cost estimator.
A third change updates numeric ExprEval classes to store their
value as a boxed type that corresponds to what it is supposed to be.
This is useful because it affects the behavior of "asString", and
is included in this patch because it is needed for the new test
"testInnerJoinTwoLookupsToTableUsingNumericColumnInReverse". This
test relies on CAST('6', 'DOUBLE') stringifying to "6.0" like an
actual double would.
Fixes#9646.
* Fix comments.
* Fix tests.
* SQL support for joins on subqueries.
Changes to SQL module:
- DruidJoinRule: Allow joins on subqueries (left/right are no longer
required to be scans or mappings).
- DruidJoinRel: Add cost estimation code for joins on subqueries.
- DruidSemiJoinRule, DruidSemiJoinRel: Removed, since DruidJoinRule can
handle this case now.
- DruidRel: Remove Nullable annotation from toDruidQuery, because
it is no longer needed (it was used by DruidSemiJoinRel).
- Update Rules constants to reflect new rules available in our current
version of Calcite. Some of these are useful for optimizing joins on
subqueries.
- Rework cost estimation to be in terms of cost per row, and place all
relevant constants in CostEstimates.
Other changes:
- RowBasedColumnSelectorFactory: Don't set hasMultipleValues. The lack
of isComplete is enough to let callers know that columns might have
multiple values, and explicitly setting it to true causes
ExpressionSelectors to think it definitely has multiple values, and
treat the inputs as arrays. This behavior interfered with some of the
new tests that involved queries on lookups.
- QueryContexts: Add maxSubqueryRows parameter, and use it in druid-sql
tests.
* Fixes for tests.
* Adjustments.
* Broker: Add ability to inline subqueries.
The main changes:
- ClientQuerySegmentWalker: Add ability to inline queries.
- Query: Add "getSubQueryId" and "withSubQueryId" methods.
- QueryMetrics: Add "subQueryId" dimension.
- ServerConfig: Add new "maxSubqueryRows" parameter, which is used by
ClientQuerySegmentWalker to limit how many rows can be inlined per
query.
- IndexedTableJoinMatcher: Allow creating keys on top of unknown types,
by assuming they are strings. This is useful because not all types are
known for fields in query results.
- InlineDataSource: Store RowSignature rather than component parts. Add
more zealous "equals" and "hashCode" methods to ease testing.
- Moved QuerySegmentWalker test code from CalciteTests and
SpecificSegmentsQueryWalker in druid-sql to QueryStackTests in
druid-server. Use this to spin up a new ClientQuerySegmentWalkerTest.
* Adjustments from CI.
* Fix integration test.
* Match GREATEST/LEAST function behavior
Change the behavior of the GREATEST / LEAST functions to be similar to
how it is implemented in other databases (as functions instead of
aggregators). The GREATEST/LEAST functions are not in the SQL standard,
but users will expect behavior similar to what other databases provide.
* Match postgres behavior & handle more SQL types
* Fix imports
* Move RowSignature from druid-sql to druid-processing and make use of it.
1) Moved (most of) RowSignature from sql to processing. Left behind the SQL-specific
stuff in a RowSignatures utility class. It also picked up some new convenience
methods along the way.
2) There were a lot of places in the code where Map<String, ValueType> was used to
associate columns with type info. These are now all replaced with RowSignature.
3) QueryToolChest's resultArrayFields method is replaced with resultArraySignature,
and it now provides type info.
* Fix up extensions.
* Various fixes
* Link up row-based datasources to serving layer.
- Add SegmentWrangler interface that allows linking of DataSources to Segments.
- Add LocalQuerySegmentWalker that uses SegmentWranglers to compute queries on
data that is available locally.
- Modify ClientQuerySegmentWalker to use LocalQuerySegmentWalker when the base
datasource is concrete and not a table.
- Add SegmentWranglerModule to the Broker so it has them available and can
properly instantiate . LocalQuerySegmentWalkers.
- Set InlineDataSource and LookupDataSource to concrete, since they can be
directly queried now.
* Fix tests.
Clint Wylie
Laksh Singla
Rohan Garg
Jonathan Wei
somu-imply
Abhishek Agarwal
Jihoon Son
Gian Merlino
Paul Rogers
Kashif Faraz
Maytas Monsereenusorn
TSFenwick
Lucas Capistrant
hqx871
frank chen
kaijianding
Suneet Saldanha
dependabot[bot]
Maria Sitkovets
chenyuzhi459
Lasse Krogh Mammen
Samarth Jain
zhangyue19921010
Franklyn Dsouza
Atul Mohan
Himanshu
Joy Kent
Abhishek Radhakrishnan
Yuanli Han
Suneet Saldanha
Maytas Monsereenusorn
Chi Cao Minh