This patch adds "TypeCastSelectors", which is used when writing frames to
perform two coercions:
- When a numeric type is desired and the underlying type is non-numeric or
unknown, the underlying selector is wrapped, "getObject" is called and the
result is coerced using "ExprEval.ofType". This differs from the prior
behavior where the primitive methods like "getLong", "getDouble", etc, would
be called directly. This fixes an issue where a column would be read as
all-zeroes when its SQL type is numeric and its physical type is string, which
can happen when evolving a column's type from string to number.
- When an array type is desired, the underlying selector is wrapped,
"getObject" is called, and the result is coerced to Object[]. This coercion
replaces some earlier logic from #15917.
Description:
#16768 introduces new compaction APIs on the Overlord `/compact/status` and `/compact/progress`.
But the corresponding `OverlordClient` methods do not return an object compatible with the actual
endpoints defined in `OverlordCompactionResource`.
This patch ensures that the objects are compatible.
Changes:
- Add `CompactionStatusResponse` and `CompactionProgressResponse`
- Use these as the return type in `OverlordClient` methods and as the response entity in `OverlordCompactionResource`
- Add `SupervisorCleanupModule` bound on the Coordinator to perform cleanup of supervisors.
Without this module, Coordinator cannot deserialize compaction supervisors.
Currently, an alert is thrown while merging datasource schema with realtime
segment schema when the datasource schema already has update columns from the delta schema.
This isn't an error condition since the datasource schema can have those columns from a different segment.
One scenario in which this can occur is when multiple replicas for a task is run.
Currently compaction with MSQ engine doesn't work for rollup on multi-value dimensions (MVDs), the reason being the default behaviour of grouping on MVD dimensions to unnest the dimension values; for instance grouping on `[s1,s2]` with aggregate `a` will result in two rows: `<s1,a>` and `<s2,a>`.
This change enables rollup on MVDs (without unnest) by converting MVDs to Arrays before rollup using virtual columns, and then converting them back to MVDs using post aggregators. If segment schema is available to the compaction task (when it ends up downloading segments to get existing dimensions/metrics/granularity), it selectively does the MVD-Array conversion only for known multi-valued columns; else it conservatively performs this conversion for all `string` columns.
#15025 adds mergeBuffer/pendingRequests metric in QueryCountStatsMonitor. Since real-time nodes also use the same merge buffers for queries and have QueryCountStatsMonitor , the documentation is being updated to include this metric.
* MSQ: Add limitHint to global-sort shuffles.
This allows pushing down limits into the SuperSorter.
* Test fixes.
* Add limitSpec to ScanQueryKit. Fix SuperSorter tracking.
Bug: When coordinator period is less than 30s, `maxSegmentsToMove` is always computed as 0
irrespective of number of available threads.
Changes:
- Fix lower bound condition and set minimum value to 100.
- Add new test which fails without this fix
Description
-----------
Auto-compaction currently poses several challenges as it:
1. may get stuck on a failing interval.
2. may get stuck on the latest interval if more data keeps coming into it.
3. always picks the latest interval regardless of the level of compaction in it.
4. may never pick a datasource if its intervals are not very recent.
5. requires setting an explicit period which does not cater to the changing needs of a Druid cluster.
This PR introduces various improvements to compaction scheduling to tackle the above problems.
Change Summary
--------------
1. Run compaction for a datasource as a supervisor of type `autocompact` on Overlord.
2. Make compaction policy extensible and configurable.
3. Track status of recently submitted compaction tasks and pass this info to policy.
4. Add `/simulate` API on both Coordinator and Overlord to run compaction simulations.
5. Redirect compaction status APIs to the Overlord when compaction supervisors are enabled.
* Make IntelliJ's MethodIsIdenticalToSuperMethod an error
* Change codebase to follow new IntelliJ inspection
* Restore non-short-circuit boolean expressions to pass tests
* MSQ: Add CPU and thread usage counters.
The main change adds "cpu" and "wall" counters. The "cpu" counter measures
CPU time (using JvmUtils.getCurrentThreadCpuTime) taken up by processors
in processing threads. The "wall" counter measures the amount of wall time
taken up by processors in those same processing threads. Both counters are
broken down by type of processor.
This patch also includes changes to support adding new counters. Due to an
oversight in the original design, older deserializers are not forwards-compatible;
they throw errors when encountering an unknown counter type. To manage this,
the following changes are made:
1) The defaultImpl NilQueryCounterSnapshot is added to QueryCounterSnapshot's
deserialization configuration. This means that any unrecognized counter types
will be read as "nil" by deserializers. Going forward, once all servers are
on the latest code, this is enough to enable easily adding new counters.
2) A new context parameter "includeAllCounters" is added, which defaults to "false".
When this parameter is set "false", only legacy counters are included. When set
to "true", all counters are included. This is currently undocumented. In a future
version, we should set the default to "true", and at that time, include a release
note that people updating from versions prior to Druid 31 should set this to
"false" until their upgrade is complete.
* Style, coverage.
* Fix.
Changes:
- Simplify exception handling in `CryptoService` by just catching a `Exception`
- Throw a `DruidException` as the exception is user facing
- Log the exception for easier debugging
- Add a test to verify thrown exception
Currently, if we have a query with window function having PARTITION BY xyz, and we have a million unique values for xyz each having 1 row, we'd end up creating a million individual RACs for processing, each having a single row. This is unnecessary, and we can batch the PARTITION BY keys together for processing, and process them only when we can't batch further rows to adhere to maxRowsMaterialized config.
The previous iteration of this PR was simplifying WindowOperatorQueryFrameProcessor to run all operators on all the rows instead of creating smaller RACs per partition by key. That approach was discarded in favor of the batching approach, and the details are summarized here: #16823 (comment).
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
* MSQ: Fix validation of time position in collations.
It is possible for the collation to refer to a field that isn't mapped,
such as when the DML includes "CLUSTERED BY some_function(some_field)".
In this case, the collation refers to a projected column that is not
part of the field mappings. Prior to this patch, that would lead to an
out of bounds list access on fieldMappings.
This patch fixes the problem by identifying the position of __time in
the fieldMappings first, rather than retrieving each collation field
from fieldMappings.
Fixes a bug introduced in #16849.
* Fix test. Better warning message.
* Place __time in signatures according to sort order.
Updates a variety of places to put __time in row signatures according
to its position in the sort order, rather than always first, including:
- InputSourceSampler.
- ScanQueryEngine (in the default signature when "columns" is empty).
- Various StorageAdapters, which also have the effect of reordering
the column order in segmentMetadata queries, and therefore in SQL
schemas as well.
Follow-up to #16849.
* Fix compilation.
* Additional fixes.
* Fix.
* Fix style.
* Omit nonexistent columns from the row signature.
* Fix tests.
* Linked back to query granularity docs
* Update ingestion-spec.md
clairfy about query granularities in the spec.
* Update docs/design/storage.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/ingestion-spec.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/granularities.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Apply suggestions from code review
---------
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* 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.
Adarsh Sanjeev
Virushade
Gian Merlino
Edgar Melendrez
Vadim Ogievetsky
Kashif Faraz
Jill Osborne
Rishabh Singh
Hugh Evans
AmatyaAvadhanula
Katya Macedo
Laksh Singla
Vishesh Garg
Clint Wylie
Hardik Bajaj
Sree Charan Manamala
Akshat Jain
Zoltan Haindrich
Jonathan Wei
Parag Jain
317brian
Charles Smith
Pranav
George Shiqi Wu