changes:
adds ExpressionProcessing.allowVectorizeFallback() and ExpressionProcessingConfig.allowVectorizeFallback(), defaulting to false until few remaining bugs can be fixed (mostly complex types and some odd interactions with mixed types)
add cannotVectorizeUnlessFallback functions to make it easy to toggle the default of this config, and easy to know what to delete when we remove it in the future
* adds support for `UNNEST` expressions
* introduces `LogicalUnnestRule` to transform a `Correlate` doing UNNEST into a `LogicalUnnest`
* `UnnestInputCleanupRule` could move the final unnested expr into the `LogicalUnnest` itself (usually its an `mv_to_array` expression)
* enhanced source unwrapping to utilize `FilteredDataSource` if it looks right
This patch adds a profile of MSQ named "Dart" that runs on Brokers and
Historicals, and which is compatible with the standard SQL query API.
For more high-level description, and notes on future work, refer to #17139.
This patch contains the following changes, grouped into packages.
Controller (org.apache.druid.msq.dart.controller):
The controller runs on Brokers. Main classes are,
- DartSqlResource, which serves /druid/v2/sql/dart/.
- DartSqlEngine and DartQueryMaker, the entry points from SQL that actually
run the MSQ controller code.
- DartControllerContext, which configures the MSQ controller.
- DartMessageRelays, which sets up relays (see "message relays" below) to read
messages from workers' DartControllerClients.
- DartTableInputSpecSlicer, which assigns work based on a TimelineServerView.
Worker (org.apache.druid.msq.dart.worker)
The worker runs on Historicals. Main classes are,
- DartWorkerResource, which supplies the regular MSQ WorkerResource, plus
Dart-specific APIs.
- DartWorkerRunner, which runs MSQ worker code.
- DartWorkerContext, which configures the MSQ worker.
- DartProcessingBuffersProvider, which provides processing buffers from
sliced-up merge buffers.
- DartDataSegmentProvider, which provides segments from the Historical's
local cache.
Message relays (org.apache.druid.messages):
To avoid the need for Historicals to contact Brokers during a query, which
would create opportunities for queries to get stuck, all connections are
opened from Broker to Historical. This is made possible by a message relay
system, where the relay server (worker) has an outbox of messages.
The relay client (controller) connects to the outbox and retrieves messages.
Code for this system lives in the "server" package to keep it separate from
the MSQ extension and make it easier to maintain. The worker-to-controller
ControllerClient is implemented using message relays.
Other changes:
- Controller: Added the method "hasWorker". Used by the ControllerMessageListener
to notify the appropriate controllers when a worker fails.
- WorkerResource: No longer tries to respond more than once in the
"httpGetChannelData" API. This comes up when a response due to resolved future
is ready at about the same time as a timeout occurs.
- MSQTaskQueryMaker: Refactor to separate out some useful functions for reuse
in DartQueryMaker.
- SqlEngine: Add "queryContext" to "resultTypeForSelect" and "resultTypeForInsert".
This allows the DartSqlEngine to modify result format based on whether a "fullReport"
context parameter is set.
- LimitedOutputStream: New utility class. Used when in "fullReport" mode.
- TimelineServerView: Add getDruidServerMetadata as a performance optimization.
- CliHistorical: Add SegmentWrangler, so it can query inline data, lookups, etc.
- ServiceLocation: Add "fromUri" method, relocating some code from ServiceClientImpl.
- FixedServiceLocator: New locator for a fixed set of service locations. Useful for
URI locations.
* SQL: Use regular filters for time filtering in subqueries.
Using the "intervals" feature on subqueries, or any non-table, should be
avoided because it isn't a meaningful optimization in those cases, and
it's simpler for runtime implementations if they can assume all filters
are located in the regular filter object.
Two changes:
1) Fix the logic in DruidQuery.canUseIntervalFiltering. It was intended
to return false for QueryDataSource, but actually returned true.
2) Add a validation to ScanQueryFrameProcessor to ensure that when running
on an input channel (which would include any subquery), the query has
"intervals" set to ONLY_ETERNITY.
Prior to this patch, the new test case in testTimeFilterOnSubquery would
throw a "Can only handle a single interval" error in the native engine,
and "QueryNotSupported" in the MSQ engine.
* Mark new case as having extra columns in decoupled mode.
* Adjust test.
* enforces to only allow supported predicates in join conditions
* fixed a recursive query building issue by caching the `source` in `DruidQueryGenerator`
* moved `DruidAggregateRemoveRedundancyRule.instance` higher up; as if `CoreRules.AGGREGATE_EXPAND_DISTINCT_AGGREGATES` runs earlier the resulting `GROUPING` might become invalid
changes:
* add `ApplyFunction` support to vectorization fallback, allowing many of the remaining expressions to be vectorized
* add `CastToObjectVectorProcessor` so that vector engine can correctly cast any type
* add support for array and complex vector constants
* reduce number of cases which can block vectorization in expression planner to be unknown inputs (such as unknown multi-valuedness)
* fix array constructor expression, apply map expression to make actual evaluated type match the output type inference
* fix bug in array_contains where something like array_contains([null], 'hello') would return true if the array was a numeric array since the non-null string value would cast to a null numeric
* fix isNull/isNotNull to correctly handle any type of input argument
* enables to use DruidHook for native plan logging
* qudiem tests doesn't necessarily need to run the query to get an explain - this helps during development as if there is a runtime issue it could still be explained in the test
Text-based input formats like csv and tsv currently parse inputs only as strings, following the RFC4180Parser spec).
To workaround this, the web-console and other tools need to further inspect the sample data returned to sample data returned by the Druid sampler API to parse them as numbers.
This patch introduces a new optional config, tryParseNumbers, for the csv and tsv input formats. If enabled, any numbers present in the input will be parsed in the following manner -- long data type for integer types and double for floating-point numbers, and if parsing fails for whatever reason, the input is treated as a string. By default, this configuration is set to false, so numeric strings will be treated as strings.
There were some problematic cases
join branches are run with finalize=false instead of finalize=true like normal subqueries
this inconsistency is not good - but fixing it is a bigger thing
ensure that right hand sides of joins are always subqueries - or accessible globally
To achieve the above:
operand indexes were needed for the upstream reltree nodes in the generator
source unwrapping now takes the join situation into account as well
Register a Ser-De for RowsAndColumns so that the window operator query running on leaf operators would be transferred properly on the wire. Would fix the empty response given by window queries without group by on the native engine.
This PR #16890 introduced a change to skip adding tombstone segments to the cache.
It turns out that as a side effect tombstone segments appear unavailable in the console. This happens because availability of a segment in Broker is determined from the metadata cache.
The fix is to keep the segment in the metadata cache but skip them from refresh.
This doesn't affect any functionality as metadata query for tombstone returns empty causing continuous refresh of those segments.
* Add window function drill tests for array_concat_agg for empty over scenarios
* Cleanup sqlNativeIncompatible() as it's not needed now
* Address review comment
* transition away from StorageAdapter
changes:
* CursorHolderFactory has been renamed to CursorFactory and moved off of StorageAdapter, instead fetched directly from the segment via 'asCursorFactory'. The previous deprecated CursorFactory interface has been merged into StorageAdapter
* StorageAdapter is no longer used by any engines or tests and has been marked as deprecated with default implementations of all methods that throw exceptions indicating the new methods to call instead
* StorageAdapter methods not covered by CursorFactory (CursorHolderFactory prior to this change) have been moved into interfaces which are retrieved by Segment.as, the primary classes are the previously existing Metadata, as well as new interfaces PhysicalSegmentInspector and TopNOptimizationInspector
* added UnnestSegment and FilteredSegment that extend WrappedSegmentReference since their StorageAdapter implementations were previously provided by WrappedSegmentReference
* added PhysicalSegmentInspector which covers some of the previous StorageAdapter functionality which was primarily used for segment metadata queries and other metadata uses, and is implemented for QueryableIndexSegment and IncrementalIndexSegment
* added TopNOptimizationInspector to cover the oddly specific StorageAdapter.hasBuiltInFilters implementation, which is implemented for HashJoinSegment, UnnestSegment, and FilteredSegment
* Updated all engines and tests to no longer use StorageAdapter
This commit aims to reject MVDs in window processing as we do not support them.
Earlier to this commit, query running a window aggregate partitioned by an MVD column would fail with ClassCastException
* Segments primarily sorted by non-time columns.
Currently, segments are always sorted by __time, followed by the sort
order provided by the user via dimensionsSpec or CLUSTERED BY. Sorting
by __time enables efficient execution of queries involving time-ordering
or granularity. Time-ordering is a simple matter of reading the rows in
stored order, and granular cursors can be generated in streaming fashion.
However, for various workloads, it's better for storage footprint and
query performance to sort by arbitrary orders that do not start with __time.
With this patch, users can sort segments by such orders.
For spec-based ingestion, users add "useExplicitSegmentSortOrder: true" to
dimensionsSpec. The "dimensions" list determines the sort order. To
define a sort order that includes "__time", users explicitly
include a dimension named "__time".
For SQL-based ingestion, users set the context parameter
"useExplicitSegmentSortOrder: true". The CLUSTERED BY clause is then
used as the explicit segment sort order.
In both cases, when the new "useExplicitSegmentSortOrder" parameter is
false (the default), __time is implicitly prepended to the sort order,
as it always was prior to this patch.
The new parameter is experimental for two main reasons. First, such
segments can cause errors when loaded by older servers, due to violating
their expectations that timestamps are always monotonically increasing.
Second, even on newer servers, not all queries can run on non-time-sorted
segments. Scan queries involving time-ordering and any query involving
granularity will not run. (To partially mitigate this, a currently-undocumented
SQL feature "sqlUseGranularity" is provided. When set to false the SQL planner
avoids using "granularity".)
Changes on the write path:
1) DimensionsSpec can now optionally contain a __time dimension, which
controls the placement of __time in the sort order. If not present,
__time is considered to be first in the sort order, as it has always
been.
2) IncrementalIndex and IndexMerger are updated to sort facts more
flexibly; not always by time first.
3) Metadata (stored in metadata.drd) gains a "sortOrder" field.
4) MSQ can generate range-based shard specs even when not all columns are
singly-valued strings. It merely stops accepting new clustering key
fields when it encounters the first one that isn't a singly-valued
string. This is useful because it enables range shard specs on
"someDim" to be created for clauses like "CLUSTERED BY someDim, __time".
Changes on the read path:
1) Add StorageAdapter#getSortOrder so query engines can tell how a
segment is sorted.
2) Update QueryableIndexStorageAdapter, IncrementalIndexStorageAdapter,
and VectorCursorGranularizer to throw errors when using granularities
on non-time-ordered segments.
3) Update ScanQueryEngine to throw an error when using the time-ordering
"order" parameter on non-time-ordered segments.
4) Update TimeBoundaryQueryRunnerFactory to perform a segment scan when
running on a non-time-ordered segment.
5) Add "sqlUseGranularity" context parameter that causes the SQL planner
to avoid using granularities other than ALL.
Other changes:
1) Rename DimensionsSpec "hasCustomDimensions" to "hasFixedDimensions"
and change the meaning subtly: it now returns true if the DimensionsSpec
represents an unchanging list of dimensions, or false if there is
some discovery happening. This is what call sites had expected anyway.
* Fixups from CI.
* Fixes.
* Fix missing arg.
* Additional changes.
* Fix logic.
* Fixes.
* Fix test.
* Adjust test.
* Remove throws.
* Fix styles.
* Fix javadocs.
* Cleanup.
* Smoother handling of null ordering.
* Fix tests.
* Missed a spot on the merge.
* Fixups.
* Avoid needless Filters.and.
* Add timeBoundaryInspector to test.
* Fix tests.
* Fix FrameStorageAdapterTest.
* Fix various tests.
* Use forceSegmentSortByTime instead of useExplicitSegmentSortOrder.
* Pom fix.
* Fix doc.
* Add type coercion and null check to left, right, repeat exprs.
These exprs shouldn't validate types; they should coerce types. Coercion
is typical behavior for functions because it enables schema evolution.
The functions are also modified to check isNumericNull on the right-hand
argument. This was missing previously, which would erroneously cause
nulls to be treated as zeroes.
* Fix tests.
Reduction of nullable DATE and TIMESTAMP expressions did not perform
a necessary null check, so would in some cases reduce to
1970-01-01 00:00:00 (epoch) rather than NULL.
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`.
* SQL syntax error should target USER persona
* * revert change to queryHandler and related tests, based on review comments
* * add test
* Properly handle Druid schema blending with catalog definition and segment metadata
* * add javadocs
* SQL: Add ProjectableFilterableTable to SegmentsTable.
This allows us to skip serialization of expensive fields such as
shard_spec, dimensions, metrics, and last_compaction_state, if those
fields are not actually being queried.
* Restructure logic to avoid unnecessary toString() as well.
When a window is defined as WINDOW W AS <DEF> and using a syntax of (PARTITION BY col1 ORDER BY col2 ROWS x PRECEDING), we would need to default the other bound to CURRENT ROW
We already have implemented this earlier, but when defined as WINDOW W AS <DEF>, Calcite takes a different route to validate the window.
* 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
This patch introduces an optional cluster configuration, druid.indexing.formats.stringMultiValueHandlingMode, allowing operators to override the default mode SORTED_SET for string dimensions. The possible values for the config are SORTED_SET, SORTED_ARRAY, or ARRAY (SORTED_SET is the default). Case insensitive values are allowed.
While this cluster property allows users to manage the multi-value handling mode for string dimension types, it's recommended to migrate to using real array types instead of MVDs.
This fixes a long-standing issue where compaction will honor the configured cluster wide property instead of rewriting it as the default SORTED_ARRAY always, even if the data was originally ingested with ARRAY or SORTED_SET.
Rejects having clauses if they contain windowed expressions.
Also added a check to produce a more descriptive error if an OVER expression
reaches the filter translation layer.
---------
Co-authored-by: Benedict Jin <asdf2014@apache.org>