After #13197 , several coordinator configs are now redundant as they are not being
used anymore, neither with `smartSegmentLoading` nor otherwise.
Changes:
- Remove dynamic configs `emitBalancingStats`: balancer error stats are always
emitted, debug stats can be logged by using `debugDimensions`
- `useBatchedSegmentSampler`, `percentOfSegmentsToConsiderPerMove`:
batched segment sampling is always used
- Add test to verify deserialization with unknown properties
- Update `CoordinatorRunStats` to always track stats, this can be optimized later.
* combine string column implementations
changes:
* generic indexed, front-coded, and auto string columns now all share the same column and index supplier implementations
* remove CachingIndexed implementation, which I think is largely no longer needed by the switch of many things to directly using ByteBuffer, avoiding the cost of creating Strings
* remove ColumnConfig.columnCacheSizeBytes since CachingIndexed was the only user
Adds support for automatic cleaning of a "query-results" directory in durable storage. This directory will be cleaned up only if the task id is not known to the overlord. This will allow the storage of query results after the task has finished running.
Changes:
- Throw an `InsertCannotAllocateSegmentFault` if the allocated segment is not aligned with
the requested granularity.
- Tests to verify new behaviour
* Updates: use the target table directly, sanitized replace time chunks and clustered by cols.
* Add DruidSqlParserUtil and tests.
* minor refactor
* Use SqlUtil.isLiteral
* Throw ValidationException if CLUSTERED BY column descending order is specified.
- Fails query planning
* Some more tests.
* fixup existing comment
* Update comment
* checkstyle fix: remove unused imports
* Remove InsertCannotOrderByDescendingFault and deprecate the fault in readme.
* minor naming
* move deprecated field to the bottom
* update docs.
* add one more example.
* Collapsible query and result
* checkstyle fixes
* Code cleanup
* order by changes
* conditionally set attributes only for explain queries.
* Cleaner ordinal check.
* Add limit test and update javadoc.
* Commentary and minor adjustments.
* Checkstyle fixes.
* One more checkArg.
* add unexpected kind to exception.
* Add OverlordStatusMonitor and CoordinatorStatusMonitor to monitor service leader status
* make the monitor more general
* resolve conflict
* use Supplier pattern to provide metrics
* reformat code and doc
* move service specific tag to dimension
* minor refine
* update doc
* reformat code
* address comments
* remove declared exception
* bind HeartbeatSupplier conditionally in Coordinator
Users can now add a guardrail to prevent subquery’s results from exceeding the set number of bytes by setting druid.server.http.maxSubqueryRows in Broker's config or maxSubqueryRows in the query context. This feature is experimental for now and would default back to row-based limiting in case it fails to get the accurate size of the results consumed by the query.
* Clarify compaction docs.
The prior wording made it sound like segmentGranularity, queryGranularity,
and rollup are always required for granularitySpec. They are not required,
but they are strongly recommended. The adjusted wording hopefully does
a better job of making that clear.
* Fix link.
* Wording adjustments.
New metrics:
- `segment/metadatacache/refresh/time`: time taken to refresh segments per datasource
- `segment/metadatacache/refresh/count`: number of segments being refreshed per datasource
Changes:
- Add property `useDefaultTierForNull` for all load rules. This property determines the default
value of `tieredReplicants` if it is not specified. When true, the default is `_default_tier => 2 replicas`.
When false, the default is empty, i.e. no replicas on any tier.
- Fix validation to allow empty replicants map, so that the segment is used but not loaded anywhere.
Description:
Druid allows a configuration of load rules that may cause a used segment to not be loaded
on any historical. This status is not tracked in the sys.segments table on the broker, which
makes it difficult to determine if the unavailability of a segment is expected and if we should
not wait for it to be loaded on a server after ingestion has finished.
Changes:
- Track replication factor in `SegmentReplicantLookup` during evaluation of load rules
- Update API `/druid/coordinator/v1metadata/segments` to return replication factor
- Add column `replication_factor` to the sys.segments virtual table and populate it in
`MetadataSegmentView`
- If this column is 0, the segment is not assigned to any historical and will not be loaded.
* Throw ValidationException if CLUSTERED BY column descending order is specified.
- Fails query planning
* Some more tests.
* fixup existing comment
* Update comment
* checkstyle fix: remove unused imports
* Remove InsertCannotOrderByDescendingFault and deprecate the fault in readme.
* move deprecated field to the bottom
* Limit select results in MSQ
* reduce number of files in test
* add truncated flag
* avoid materializing select results to list, use iterable instead
* javadocs
* Add INFORMATION_SCHEMA.ROUTINES to expose Druid operators and functions.
* checkstyle
* remove IS_DETERMISITIC.
* test
* cleanup test
* remove logs and simplify
* fixup unit test
* Add docs for INFORMATION_SCHEMA.ROUTINES table.
* Update test and add another SQL query.
* add stuff to .spelling and checkstyle fix.
* Add more tests for custom operators.
* checkstyle and comment.
* Some naming cleanup.
* Add FUNCTION_ID
* The different Calcite function syntax enums get translated to FUNCTION
* Update docs.
* Cleanup markdown table.
* fixup test.
* fixup intellij inspection
* Review comment: nullable column; add a function to determine function syntax.
* More tests; add non-function syntax operators.
* More unit tests. Also add a separate test for DruidOperatorTable.
* actually just validate non-zero count.
* switch up the order
* checkstyle fixes.
This PR adds the following to the ATTRIBUTES column in the explain plan output:
- partitionedBy
- clusteredBy
- replaceTimeChunks
This PR leverages the work done in #14074, which added a new column ATTRIBUTES
to encapsulate all the statement-related attributes.
In this PR, we are enhancing KafkaEmitter, to emit metadata about published segments (SegmentMetadataEvent) into a Kafka topic. This segment metadata information that gets published into Kafka, can be used by any other downstream services to query Druid intelligently based on the segments published. The segment metadata gets published into kafka topic in json string format similar to other events.
### Description
This change allows for consideration of the input format and compression when computing how to split the input files among available tasks, in MSQ ingestion, when considering the value of the `maxInputBytesPerWorker` query context parameter. This query parameter allows users to control the maximum number of bytes, with granularity of input file / object, that ingestion tasks will be assigned to ingest. With this change, this context parameter now denotes the estimated weighted size in bytes of the input to split on, with consideration for input format and compression format, rather than the actual file size, reported by the file system. We assume uncompressed newline delimited json as a baseline, with scaling factor of `1`. This means that when computing the byte weight that a file has towards the input splitting, we take the file size as is, if uncompressed json, 1:1. It was found during testing that gzip compressed json, and parquet, has scale factors of `4` and `8` respectively, meaning that each byte of data is weighted 4x and 8x respectively, when computing input splits. This weighted byte scaling is only considered for MSQ ingestion that uses either LocalInputSource or CloudObjectInputSource at the moment. The default value of the `maxInputBytesPerWorker` query context parameter has been updated from 10 GiB, to 512 MiB
The defaults of the following config values in the `CoordinatorDynamicConfig` are being updated.
1. `maxSegmentsInNodeLoadingQueue = 500` (previous = 100)
2. `replicationThrottleLimit = 500` (previous = 10)
Rationale: With round-robin segment assignment now being the default assignment technique,
the Coordinator can assign a large number of under-replicated/unavailable segments very quickly,
without getting stuck in `RunRules` duty due to very slow strategy-based cost computations.
3. `maxSegmentsToMove = 100` (previous = 5)
Rationale: A very low value (say 5) is ineffective in balancing especially if there are many segments
to balance. A very large value can cause excessive moves, which has these disadvantages:
- Load of moving segments competing with load of unavailable/under-replicated segments
- Unnecessary network costs due to constant download and delete of segments
These defaults will be revisited after #13197 is merged.
This PR adds a new interface to control how SegmentMetadataCache chooses ColumnType when faced with differences between segments for SQL schemas which are computed, exposed as druid.sql.planner.metadataColumnTypeMergePolicy and adds a new 'least restrictive type' mode to allow choosing the type that data across all segments can best be coerced into and sets this as the default behavior.
This is a behavior change around when segment driven schema migrations take effect for the SQL schema. With latestInterval, the SQL schema will be updated as soon as the first job with the new schema has published segments, while using leastRestrictive, the schema will only be updated once all segments are reindexed to the new type. The benefit of leastRestrictive is that it eliminates a bunch of type coercion errors that can happen in SQL when types are varied across segments with latestInterval because the newest type is not able to correctly represent older data, such as if the segments have a mix of ARRAY and number types, or any other combinations that lead to odd query plans.
* Make resources an ordered collection so it's deterministic.
* test cleanup
* fixup docs.
* Replace deprecated ObjectNode#put() calls with ObjectNode#set().
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Victoria Lim <vtlim@users.noreply.github.com>
Co-authored-by: Victoria Lim <lim.t.victoria@gmail.com>
* Be able to load segments on Peons
This change introduces a new config on WorkerConfig
that indicates how many bytes of each storage
location to use for storage of a task. Said config
is divided up amongst the locations and slots
and then used to set TaskConfig.tmpStorageBytesPerTask
The Peons use their local task dir and
tmpStorageBytesPerTask as their StorageLocations for
the SegmentManager such that they can accept broadcast
segments.
* Make LoggingEmitter more useful
* Skip code coverage for facade classes
* fix spellcheck
* code review
* fix dependency
* logging.md
* fix checkstyle
* Add back jacoco version to main pom
* fix typo in s3 docs. add readme to s3 module.
* Update extensions-core/s3-extensions/README.md
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
* cleanup readme for s3 extension and link to repo markdown doc instead of web docs
---------
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
Hadoop 2 often causes red security scans on Druid distribution because of the dependencies it brings. We want to move away from Hadoop 2 and provide Hadoop 3 distribution available. Switch druid to building with Hadoop 3 by default. Druid will still be compatible with Hadoop 2 and users can build hadoop-2 compatible distribution using hadoop2 profile.
* Compaction: Block input specs not aligned with segmentGranularity.
When input intervals are not aligned with segmentGranularity, data may be
overshadowed if it lies in the space between the input intervals and the
output segmentGranularity.
In MSQ REPLACE, this is a validation error. IMO the same behavior makes
sense for compaction tasks. In case anyone was depending on the ability
to compact nonaligned intervals, a configuration parameter
allowNonAlignedInterval is provided. I don't expect it to be used much.
* Remove unused.
* ITCompactionTaskTest uses non-aligned intervals.
* MSQ: Subclass CalciteJoinQueryTest, other supporting changes.
The main change is the new tests: we now subclass CalciteJoinQueryTest
in CalciteSelectJoinQueryMSQTest twice, once for Broadcast and once for
SortMerge.
Two supporting production changes for default-value mode:
1) InputNumberDataSource is marked as concrete, to allow leftFilter to
be pushed down to it.
2) In default-value mode, numeric frame field readers can now return nulls.
This is necessary when stacking joins on top of joins: nulls must be
preserved for semantics that match broadcast joins and native queries.
3) In default-value mode, StringFieldReader.isNull returns true on empty
strings in addition to nulls. This is more consistent with the behavior
of the selectors, which map empty strings to null as well in that mode.
As an effect of change (2), the InsertTimeNull change from #14020 (to
replace null timestamps with default timestamps) is reverted. IMO, this
is fine, as either behavior is defensible, and the change from #14020
hasn't been released yet.
* Adjust tests.
* Style fix.
* Additional tests.
* Allow for Log4J to be configured for peons but still ensure console logging is enforced
This change will allow for log4j to be configured for peons but require console logging is still
configured for them to ensure peon logs are saved to deep storage.
Also fixed the test ConsoleLoggingEnforcementTest to use a valid appender for the non console
Config as the previous config was incorrect and would never return a logger.
* fix checkstyle
* add warning to logger when it overwrites all loggers to be console
* optimize calls for altering logging config for ConsoleLoggingEnforcementConfigurationFactory
add getName to the druid logger class
* update docs, and error message
* edit docs to be more clear
* fix checkstyle issues
* CI fixes - LoggerTest code coverage and fix spelling issue for logging docs
*
Adds new run time parameter druid.indexer.task.tmpStorageBytesPerTask. This sets a limit for the amount of temporary storage disk space used by tasks. This limit is currently only respected by MSQ tasks.
* Removes query context parameters intermediateSuperSorterStorageMaxLocalBytes and composedIntermediateSuperSorterStorageEnabled. Composed intermediate super sorter (which was enabled by composedIntermediateSuperSorterStorageEnabled) is now enabled automatically if durableShuffleStorage is set to true. intermediateSuperSorterStorageMaxLocalBytes is calculated from the limit set by the run time parameter druid.indexer.task.tmpStorageBytesPerTask.
* "maxResultsSize" has been removed from the S3OutputConfig and a default "chunkSize" of 100MiB is now present. This change primarily affects users who wish to use durable storage for MSQ jobs.
This commit adds attributes that contain metadata information about the query
in the EXPLAIN PLAN output. The attributes currently contain two items:
- `statementTyp`: SELECT, INSERT or REPLACE
- `targetDataSource`: provides the target datasource name for DML statements
It is added to both the legacy and native query plan outputs.
* Make the tasks run with only a single directory
There was a change that tried to get indexing to run on multiple disks
It made a bunch of changes to how tasks run, effectively hiding the
"safe" directory for tasks to write files into from the task code itself
making it extremely difficult to do anything correctly inside of a task.
This change reverts those changes inside of the tasks and makes it so that
only the task runners are the ones that make decisions about which
mount points should be used for storing task-related files.
It adds the config druid.worker.baseTaskDirs which can be used by the
task runners to know which directories they should schedule tasks inside of.
The TaskConfig remains the authoritative source of configuration for where
and how an individual task should be operating.
* Frames: Ensure nulls are read as default values when appropriate.
Fixes a bug where LongFieldWriter didn't write a properly transformed
zero when writing out a null. This had no meaningful effect in SQL-compatible
null handling mode, because the field would get treated as a null anyway.
But it does have an effect in default-value mode: it would cause Long.MIN_VALUE
to get read out instead of zero.
Also adds NullHandling checks to the various frame-based column selectors,
allowing reading of nullable frames by servers in default-value mode.
* use new sampler features
* supprot kafka format
* update DQT, fix tests
* prefer non numeric formats
* fix input format step
* boost SQL data loader
* delete dimension in auto discover mode
* inline example specs
* feedback updates
* yeet the format into valueFormat when switching to kafka
* kafka format is now a toggle
* even better form layout
* rename
* Update api.md
I have created changes in api call of python according to latest version of requests 2.28.1 library. Along with this there are some irregularities between use of <your-instance> and <hostname> so I have tried to fix that also.
* Update api.md
made some changes in declaring USER and PASSWORD
* Add a new fault "QueryRuntimeError" to MSQ engine to capture native query errors.
* Fixed bug in MSQ fault tolerance where worker were being retried if `UnexpectedMultiValueDimensionException` was thrown.
* An exception from the query runtime with `org.apache.druid.query` as the package name is thrown as a QueryRuntimeError
This PR is a follow-up to #13819 so that the Tuple sketch functionality can be used in SQL for both ingestion using Multi-Stage Queries (MSQ) and also for analytic queries against Tuple sketch columns.
Document how to report security issues on the security overview page, so we can link this page from the homepage. That should make all the other important security information easier to find as well.
Expands the OIDC based auth in Druid by adding a JWT Authenticator that validates ID Tokens associated with a request. The existing pac4j authenticator works for authenticating web users while accessing the console, whereas this authenticator is for validating Druid API requests made by Direct clients. Services already supporting OIDC can attach their ID tokens to the Druid requests
under the Authorization request header.
* Hook up PodTemplateTaskAdapter
* Make task adapter TYPE parameters final
* Rename adapters types
* Include specified adapter name in exception message
* Documentation for sidecarSupport deprecation
* Fix order
* Set TASK_ID as environment variable in PodTemplateTaskAdapter (#13969)
* Update docs/development/extensions-contrib/k8s-jobs.md
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Hook up PodTemplateTaskAdapter
* Make task adapter TYPE parameters final
* Rename adapters types
* Include specified adapter name in exception message
* Documentation for sidecarSupport deprecation
* Fix order
* fix spelling errors
---------
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Add segment generator counters to reports
* Remove unneeded annotation
* Fix checkstyle and coverage
* Add persist and merged as new metrics
* Address review comments
* Fix checkstyle
* Create metrics class to handle updating counters
* Address review comments
* Add rowsPushed as a new metrics
* Removing intermediateSuperSorterStorageMaxLocalBytes, maxInputBytesPerWorker, composedIntermediateSuperSorterStorageEnabled, clusterStatisticsMergeMode from docs
* Adding documentation in the context class.
* Refactoring and bug fixes on top of unnest. The filter now is passed inside the unnest cursors. Added tests for scenarios such as
1. filter on unnested column which involves a left filter rewrite
2. filter on unnested virtual column which pushes the filter to the right only and involves no rewrite
3. not filters
4. SQL functions applied on top of unnested column
5. null present in first row of the column to be unnested
* Various changes and fixes to UNNEST.
Native changes:
1) UnnestDataSource: Replace "column" and "outputName" with "virtualColumn".
This enables pushing expressions into the datasource. This in turn
allows us to do the next thing...
2) UnnestStorageAdapter: Logically apply query-level filters and virtual
columns after the unnest operation. (Physically, filters are pulled up,
when possible.) This is beneficial because it allows filters and
virtual columns to reference the unnested column, and because it is
consistent with how the join datasource works.
3) Various documentation updates, including declaring "unnest" as an
experimental feature for now.
SQL changes:
1) Rename DruidUnnestRel (& Rule) to DruidUnnestRel (& Rule). The rel
is simplified: it only handles the UNNEST part of a correlated join.
Constant UNNESTs are handled with regular inline rels.
2) Rework DruidCorrelateUnnestRule to focus on pulling Projects from
the left side up above the Correlate. New test testUnnestTwice verifies
that this works even when two UNNESTs are stacked on the same table.
3) Include ProjectCorrelateTransposeRule from Calcite to encourage
pushing mappings down below the left-hand side of the Correlate.
4) Add a new CorrelateFilterLTransposeRule and CorrelateFilterRTransposeRule
to handle pulling Filters up above the Correlate. New tests
testUnnestWithFiltersOutside and testUnnestTwiceWithFilters verify
this behavior.
5) Require a context feature flag for SQL UNNEST, since it's undocumented.
As part of this, also cleaned up how we handle feature flags in SQL.
They're now hooked into EngineFeatures, which is useful because not
all engines support all features.
* Improve memory efficiency of WrappedRoaringBitmap.
Two changes:
1) Use an int[] for sizes 4 or below.
2) Remove the boolean compressRunOnSerialization. Doesn't save much
space, but it does save a little, and it isn't adding a ton of value
to have it be configurable. It was originally configurable in case
anything broke when enabling it, but it's been a while and nothing
has broken.
* Slight adjustment.
* Adjust for inspection.
* Updates.
* Update snaps.
* Update test.
* Adjust test.
* Fix snaps.
* Sort-merge join and hash shuffles for MSQ.
The main changes are in the processing, multi-stage-query, and sql modules.
processing module:
1) Rename SortColumn to KeyColumn, replace boolean descending with KeyOrder.
This makes it nicer to model hash keys, which use KeyOrder.NONE.
2) Add nullability checkers to the FieldReader interface, and an
"isPartiallyNullKey" method to FrameComparisonWidget. The join
processor uses this to detect null keys.
3) Add WritableFrameChannel.isClosed and OutputChannel.isReadableChannelReady
so callers can tell which OutputChannels are ready for reading and which
aren't.
4) Specialize FrameProcessors.makeCursor to return FrameCursor, a random-access
implementation. The join processor uses this to rewind when it needs to
replay a set of rows with a particular key.
5) Add MemoryAllocatorFactory, which is embedded inside FrameWriterFactory
instead of a particular MemoryAllocator. This allows FrameWriterFactory
to be shared in more scenarios.
multi-stage-query module:
1) ShuffleSpec: Add hash-based shuffles. New enum ShuffleKind helps callers
figure out what kind of shuffle is happening. The change from SortColumn
to KeyColumn allows ClusterBy to be used for both hash-based and sort-based
shuffling.
2) WorkerImpl: Add ability to handle hash-based shuffles. Refactor the logic
to be more readable by moving the work-order-running code to the inner
class RunWorkOrder, and the shuffle-pipeline-building code to the inner
class ShufflePipelineBuilder.
3) Add SortMergeJoinFrameProcessor and factory.
4) WorkerMemoryParameters: Adjust logic to reserve space for output frames
for hash partitioning. (We need one frame per partition.)
sql module:
1) Add sqlJoinAlgorithm context parameter; can be "broadcast" or
"sortMerge". With native, it must always be "broadcast", or it's a
validation error. MSQ supports both. Default is "broadcast" in
both engines.
2) Validate that MSQs do not use broadcast join with RIGHT or FULL join,
as results are not correct for broadcast join with those types. Allow
this in native for two reasons: legacy (the docs caution against it,
but it's always been allowed), and the fact that it actually *does*
generate correct results in native when the join is processed on the
Broker. It is much less likely that MSQ will plan in such a way that
generates correct results.
3) Remove subquery penalty in DruidJoinQueryRel when using sort-merge
join, because subqueries are always required, so there's no reason
to penalize them.
4) Move previously-disabled join reordering and manipulation rules to
FANCY_JOIN_RULES, and enable them when using sort-merge join. Helps
get to better plans where projections and filters are pushed down.
* Work around compiler problem.
* Updates from static analysis.
* Fix @param tag.
* Fix declared exception.
* Fix spelling.
* Minor adjustments.
* wip
* Merge fixups
* fixes
* Fix CalciteSelectQueryMSQTest
* Empty keys are sortable.
* Address comments from code review. Rename mux -> mix.
* Restore inspection config.
* Restore original doc.
* Reorder imports.
* Adjustments
* Fix.
* Fix imports.
* Adjustments from review.
* Update header.
* Adjust docs.
Python Druid API for use in notebooks
Revises existing notebooks and readme to reference
the new API.
Notebook to explain the new API.
Split README into a console version and a notebook
version to work around lack of a nice display for
md files.
Update the REST API notebook to use simpler Requests calls
Converted the SQL tutorial to use the Python library
README file, converted to using properties
---------
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Victoria Lim <vtlim@users.noreply.github.com>
You can now do the following operations with TupleSketches in Post Aggregation Step
Get the Sketch Output as Base64 String
Provide a constant Tuple Sketch in post-aggregation step that can be used in Set Operations
Get the Estimated Value(Sum) of Summary/Metrics Objects associated with Tuple Sketch
The FiniteFirehoseFactory and InputRowParser classes were deprecated in 0.17.0 (#8823) in favor of InputSource & InputFormat. This PR removes the FiniteFirehoseFactory and all its implementations along with classes solely used by them like Fetcher (Used by PrefetchableTextFilesFirehoseFactory). Refactors classes including tests using FiniteFirehoseFactory to use InputSource instead.
Removing InputRowParser may not be as trivial as many classes that aren't deprecated depends on it (with no alternatives), like EventReceiverFirehoseFactory. Hence FirehoseFactory, EventReceiverFirehoseFactory, and Firehose are marked deprecated.
*When running REPLACE queries, the segments which contain no data are dropped (marked as unused). This PR aims to generate tombstones in place of segments which contain no data to mark their deletion, as is the behavior with the native ingestion.
This will cause InsertCannotReplaceExistingSegmentFault to be removed since it was generated if the interval to be marked unused didn't fully overlap one of the existing segments to replace.
* docs: add juptyer API tutorial for API and jupyter tutorial index (#3)
(cherry picked from commit aeb8d9e3390fa26d9c533dce0862295b80c58583)
* update prereqs and fix jupyterlab name
* Removing notebook since 13345 has it
13345 should be merged first
* update contributing instructions
* docs: link to the Druid SQL tutorial
* Add link to partitioning
* fix merge conflict
* Saving
* Update docs/tutorials/tutorial-jupyter-index.md
* Remove partitioning
---------
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
Co-authored-by: brian.le <brian.le@imply.io>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Better sidecar support
* remove un-thrown exception from test
* Druid you are such a stickler about spelling :)
* Only require the primaryContainerName, no need to exclude containers
Without perl 5 I was unable to start druid using the instructions in the quickstart guide. I'm not certain what versions it might require, but the one that I got working was perl 5
> This is perl 5, version 36, subversion 0 (v5.36.0) built for x86_64-linux-thread-multi
### Description
This change adds a new config property `druid.sql.planner.operatorConversion.denyList`, which allows a user to specify
any operator conversions that they wish to disallow. A user may want to do this for a number of reasons, including security concerns. The default value of this property is the empty list `[]`, which does not disallow any operator conversions.
An example usage of this property is `druid.sql.planner.operatorConversion.denyList=["extern"]`, which disallows the usage of the `extern` operator conversion. If the property is configured this way, and a user of the Druid cluster tries to submit a query that uses the `extern` function, such as the example given [here](https://druid.apache.org/docs/latest/multi-stage-query/examples.html#insert-with-no-rollup), a response with http response code `400` is returned with en error body similar to the following:
```
{
"taskId": "4ec5b0b6-fa9b-4c3a-827d-2308294e9985",
"state": "FAILED",
"error": {
"error": "Plan validation failed",
"errorMessage": "org.apache.calcite.runtime.CalciteContextException: From line 28, column 5 to line 32, column 5: No match found for function signature EXTERN(<CHARACTER>, <CHARACTER>, <CHARACTER>)",
"errorClass": "org.apache.calcite.tools.ValidationException",
"host": null
}
}
```
* Allow users to add additional metadata to ingestion metrics
When submitting an ingestion spec, users may pass a map of metadata
in the ingestion spec config that will be added to ingestion metrics.
This will make it possible for operators to tag metrics with other
metadata that doesn't necessarily line up with the existing tags
like taskId.
Druid clusters that ingest these metrics can take advantage of the
nested data columns feature to process this additional metadata.
* rename to tags
* docs
* tests
* fix test
* make code cov happy
* checkstyle
Merging regardless of nit since topic is in better shape.
* refresh the update data tutorial
* Apply suggestions from code review
Co-authored-by: Jill Osborne <jill.osborne@imply.io>
---------
Co-authored-by: Jill Osborne <jill.osborne@imply.io>
* Fix lookup docs
* Fix spelling
* Apply suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
---------
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Add a new API to return the history of changes to automatic compaction config history to make it easy for users to see what changes have been made to their auto-compaction config.
The API is scoped per dataSource to allow users to triage issues with an individual dataSource. The API responds with a list of configs when there is a change to either the settings that impact all auto-compaction configs on a cluster or the dataSource in question.
Much improved table functions
* Revises properties, definitions in the catalog
* Adds a "table function" abstraction to model such functions
* Specific functions for HTTP, inline, local and S3.
* Extended SQL types in the catalog
* Restructure external table definitions to use table functions
* EXTEND syntax for Druid's extern table function
* Support for array-valued table function parameters
* Support for array-valued SQL query parameters
* Much new documentation
* Kinesis: More robust default fetch settings.
1) Default recordsPerFetch and recordBufferSize based on available memory
rather than using hardcoded numbers. For this, we need an estimate
of record size. Use 10 KB for regular records and 1 MB for aggregated
records. With 1 GB heaps, 2 processors per task, and nonaggregated
records, recordBufferSize comes out to the same as the old
default (10000), and recordsPerFetch comes out slightly lower (1250
instead of 4000).
2) Default maxRecordsPerPoll based on whether records are aggregated
or not (100 if not aggregated, 1 if aggregated). Prior default was 100.
3) Default fetchThreads based on processors divided by task count on
Indexers, rather than overall processor count.
4) Additionally clean up the serialized JSON a bit by adding various
JsonInclude annotations.
* Updates for tests.
* Additional important verify.
* reword single server page
* fix typo
* Update docs/operations/single-server.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* spelling
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Changes:
- Remove specification of a Druid version in the quickstart, because the previous step
instructs downloading the latest version anyway.
- Mention usage of memory parameter in the quickstart
Main change: clarify that the "default value" for casts only applies if
druid.generic.useDefaultValueForNull = true.
Secondary change: adjust a bunch of wording from future to present tense.
Follow up to #13520
Bytes processed are currently tracked for intermediate stages in MSQ ingestion.
This patch adds the capability to track the bytes processed by an MSQ controller
task while reading from an external input source or a segment source.
Changes:
- Track `processedBytes` for every `InputSource` read in `ExternalInputSliceReader`
- Update `ChannelCounters` with the above obtained `processedBytes` when incrementing
the input file count.
- Update task report structure in docs
The total input processed bytes can be obtained by summing the `processedBytes` as follows:
totalBytes = 0
for every root stage (i.e. a stage which does not have another stage as an input):
for every worker in that stage:
for every input channel: (i.e. channels with prefix "input", e.g. "input0", "input1", etc.)
totalBytes += processedBytes
* Add validation checks to worker chat handler apis
* Merge things and polishing the error messages.
* Minor error message change
* Fixing race and adding some tests
* Fixing controller fetching stats from wrong workers.
Fixing race
Changing default mode to Parallel
Adding logging.
Fixing exceptions not propagated properly.
* Changing to kernel worker count
* Added a better logic to figure out assigned worker for a stage.
* Nits
* Moving to existing kernel methods
* Adding more coverage
Co-authored-by: cryptoe <karankumar1100@gmail.com>
* Zero-copy local deep storage.
This is useful for local deep storage, since it reduces disk usage and
makes Historicals able to load segments instantaneously.
Two changes:
1) Introduce "druid.storage.zip" parameter for local storage, which defaults
to false. This changes default behavior from writing an index.zip to writing
a regular directory. This is safe to do even during a rolling update, because
the older code actually already handled unzipped directories being present
on local deep storage.
2) In LocalDataSegmentPuller and LocalDataSegmentPusher, use hard links
instead of copies when possible. (Generally this is possible when the
source and destination directory are on the same filesystem.)
* Druid automated quickstart
* remove conf/druid/single-server/quickstart/_common/historical/jvm.config
* Minor changes in python script
* Add lower bound memory for some services
* Additional runtime properties for services
* Update supervise script to accept command arguments, corresponding changes in druid-quickstart.py
* File end newline
* Limit the ability to start multiple instances of a service, documentation changes
* simplify script arguments
* restore changes in medium profile
* run-druid refactor
* compute and pass middle manager runtime properties to run-druid
supervise script changes to process java opts array
use argparse, leave free memory, logging
* Remove extra quotes from mm task javaopts array
* Update logic to compute minimum memory
* simplify run-druid
* remove debug options from run-druid
* resolve the config_path provided
* comment out service specific runtime properties which are computed in the code
* simplify run-druid
* clean up docs, naming changes
* Throw ValueError exception on illegal state
* update docs
* rename args, compute_only -> compute, run_zk -> zk
* update help documentation
* update help documentation
* move task memory computation into separate method
* Add validation checks
* remove print
* Add validations
* remove start-druid bash script, rename start-druid-main
* Include tasks in lower bound memory calculation
* Fix test
* 256m instead of 256g
* caffeine cache uses 5% of heap
* ensure min task count is 2, task count is monotonic
* update configs and documentation for runtime props in conf/druid/single-server/quickstart
* Update docs
* Specify memory argument for each profile in single-server.md
* Update middleManager runtime.properties
* Move quickstart configs to conf/druid/base, add bash launch script, support python2
* Update supervise script
* rename base config directory to auto
* rename python script, changes to pass repeated args to supervise
* remove exmaples/conf/druid/base dir
* add docs
* restore changes in conf dir
* update start-druid-auto
* remove hashref for commands in supervise script
* start-druid-main java_opts array is comma separated
* update entry point script name in python script
* Update help docs
* documentation changes
* docs changes
* update docs
* add support for running indexer
* update supported services list
* update help
* Update python.md
* remove dir
* update .spelling
* Remove dependency on psutil and pathlib
* update docs
* Update get_physical_memory method
* Update help docs
* update docs
* update method to get physical memory on python
* udpate spelling
* update .spelling
* minor change
* Minor change
* memory comptuation for indexer
* update start-druid
* Update python.md
* Update single-server.md
* Update python.md
* run python3 --version to check if python is installed
* Update supervise script
* start-druid: echo message if python not found
* update anchor text
* minor change
* Update condition in supervise script
* JVM not jvm in docs
1) Edited the TooManyBuckets error message to mention PARTITIONED BY
instead of segmentGranularity.
2) Added error-code-specific anchors in the docs.
3) Add information to various error codes in the docs about common
causes and solutions.
* add padding and keywords
* add arrayOfDoubles
* Update docs/development/extensions-core/datasketches-tuple.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/development/extensions-core/datasketches-tuple.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/development/extensions-core/datasketches-tuple.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/development/extensions-core/datasketches-tuple.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/development/extensions-core/datasketches-tuple.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* partiton int
* fix docs
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Changes:
- Limit max batch size in `SegmentAllocationQueue` to 500
- Rename `batchAllocationMaxWaitTime` to `batchAllocationWaitTime` since the actual
wait time may exceed this configured value.
- Replace usage of `SegmentInsertAction` in `TaskToolbox` with `SegmentTransactionalInsertAction`
* Switching emitter. This will allow for a per feed emitter designation.
This will work by looking at an event's feed and direct it to a specific emitter. If no specific feed is specified for a feed.
The emitter can direct the event to a default emitter.
* fix checkstyle issues and make docs for switching emitter use basic event feeds
* fix broken docs, add test, and guard against misconfigurations
* add module test
add switching emitter module test
* fix broken SwitchingEmitterModuleTest
* add apache license to top of test
* fix checkstyle issues
* address comments by adding javadocs, removing a todo, and making druid docs more clear
* initial commit for jdbc tutorial
(cherry picked from commit 04c4adad71e5436b76c3425fe369df03aaaf0acb)
* add commentary
* address comments from charles
* add query context to example
* fix typo
* add links
* Apply suggestions from code review
Co-authored-by: Frank Chen <frankchen@apache.org>
* fix datatype
* address feedback
* add parameterize to spelling file. the past tense version was already there
Co-authored-by: Frank Chen <frankchen@apache.org>
Main changes:
1) Convert SeekableStreamIndexTaskClient to an interface, move old code
to SeekableStreamIndexTaskClientSyncImpl, and add new implementation
SeekableStreamIndexTaskClientAsyncImpl that uses ServiceClient.
2) Add "chatAsync" parameter to seekable stream supervisors that causes
the supervisor to use an async task client.
3) In SeekableStreamSupervisor.discoverTasks, adjust logic to avoid making
blocking RPC calls in workerExec threads.
4) In SeekableStreamSupervisor generally, switch from Futures.successfulAsList
to FutureUtils.coalesce, so we can better capture the errors that occurred
with contacting individual tasks.
Other, related changes:
1) Add ServiceRetryPolicy.retryNotAvailable, which controls whether
ServiceClient retries unavailable services. Useful since we do not
want to retry calls unavailable tasks within the service client. (The
supervisor does its own higher-level retries.)
2) Add FutureUtils.transformAsync, a more lambda friendly version of
Futures.transform(f, AsyncFunction).
3) Add FutureUtils.coalesce. Similar to Futures.successfulAsList, but
returns Either instead of using null on error.
4) Add JacksonUtils.readValue overloads for JavaType and TypeReference.
* Use standard library to correctly glob and stop at the correct folder structure when filtering cloud objects.
Removed:
import org.apache.commons.io.FilenameUtils;
Add:
import java.nio.file.FileSystems;
import java.nio.file.PathMatcher;
import java.nio.file.Paths;
* Forgot to update CloudObjectInputSource as well.
* Fix tests.
* Removed unused exceptions.
* Able to reduced user mistakes, by removing the protocol and the bucket on filter.
* add 1 more test.
* add comment on filterWithoutProtocolAndBucket
* Fix lint issue.
* Fix another lint issue.
* Replace all mention of filter -> objectGlob per convo here:
https://github.com/apache/druid/pull/13027#issuecomment-1266410707
* fix 1 bad constructor.
* Fix the documentation.
* Don’t do anything clever with the object path.
* Remove unused imports.
* Fix spelling error.
* Fix incorrect search and replace.
* Addressing Gian’s comment.
* add filename on .spelling
* Fix documentation.
* fix documentation again
Co-authored-by: Didip Kerabat <didip@apple.com>
* Fix typo
* Fix some spacing
* Add missing fields
* Cleanup table spacing
* Remove durable storage docs again
Thanks Brian for pointing out previous discussions.
* Update docs/multi-stage-query/reference.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Mark codes as code
* And even more codes as code
* Another set of spaces
* Combine `ColumnTypeNotSupported`
Thanks Karan.
* More whitespaces and typos
* Add spelling and fix links
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Changes:
- Add a metric for partition-wise kafka/kinesis lag for streaming ingestion.
- Emit lag metrics for streaming ingestion when supervisor is not suspended and state is in {RUNNING, IDLE, UNHEALTHY_TASKS, UNHEALTHY_SUPERVISOR}
- Document metrics
* scratch
* s3 ls fix, add docs
* add documentation, update method name
* Add tests, address commits, change default value of the helper
* fix test
* update the default value of config, remove initial delay config
* Trigger Build
* update class
* add more tests
* docs update
* spellcheck
* remove ioe from the signature
* add back dmmy constructor for initialization
* fix guice bindings, intellij inspections
`cachingCost` strategy has some discrepancies when compared to cost strategy.
This commit addresses two of these by retaining the same behaviour as the `cost` strategy
when computing the cost of moving a segment to a server:
- subtract the self cost of a segment if it is being served by the target server
- subtract the cost of segments that are marked to be dropped
Other changes:
- Add tests to verify fixed strategy. These tests would fail without the fixes made to `CachingCostStrategy.computeCost()`
- Fix the definition of the segment related metrics in the docs.
- Fix some docs issues introduced in #13181
* MSQ: Fix task lock checking during publish, fix lock priority.
Fixes two issues:
1) ControllerImpl did not properly check the return value of
SegmentTransactionalInsertAction when doing a REPLACE. This could cause
it to not realize that its locks were preempted.
2) Task lock priority was the default of 0. It should be the higher
batch default of 50. The low priority made it possible for MSQ tasks
to be preempted by compaction tasks, which is not desired.
* Restructuring, add docs.
* Add performSegmentPublish tests.
* Fix tests.
* Compaction: Fetch segments one at a time on main task; skip when possible.
Compact tasks include the ability to fetch existing segments and determine
reasonable defaults for granularitySpec, dimensionsSpec, and metricsSpec.
This is a useful feature that makes compact tasks work well even when the
user running the compaction does not have a clear idea of what they want
the compacted segments to be like.
However, this comes at a cost: it takes time, and disk space, to do all
of these fetches. This patch improves the situation in two ways:
1) When segments do need to be fetched, download them one at a time and
delete them when we're done. This still takes time, but minimizes the
required disk space.
2) Don't fetch segments on the main compact task when they aren't needed.
If the user provides a full granularitySpec, dimensionsSpec, and
metricsSpec, we can skip it.
* Adjustments.
* Changes from code review.
* Fix logic for determining rollup.
* MSQ: Consider PARTITION_STATS_MAX_BYTES in WorkerMemoryParameters.
This consideration is important, because otherwise we can run out of
memory due to large statistics-tracking objects.
* Improved calculations.
* Always return sketches from DS_HLL, DS_THETA, DS_QUANTILES_SKETCH.
These aggregation functions are documented as creating sketches. However,
they are planned into native aggregators that include finalization logic
to convert the sketch to a number of some sort. This creates an
inconsistency: the functions sometimes return sketches, and sometimes
return numbers, depending on where they lie in the native query plan.
This patch changes these SQL aggregators to _never_ finalize, by using
the "shouldFinalize" feature of the native aggregators. It already
existed for theta sketches. This patch adds the feature for hll and
quantiles sketches.
As to impact, Druid finalizes aggregators in two cases:
- When they appear in the outer level of a query (not a subquery).
- When they are used as input to an expression or finalizing-field-access
post-aggregator (not any other kind of post-aggregator).
With this patch, the functions will no longer be finalized in these cases.
The second item is not likely to matter much. The SQL functions all declare
return type OTHER, which would be usable as an input to any other function
that makes sense and that would be planned into an expression.
So, the main effect of this patch is the first item. To provide backwards
compatibility with anyone that was depending on the old behavior, the
patch adds a "sqlFinalizeOuterSketches" query context parameter that
restores the old behavior.
Other changes:
1) Move various argument-checking logic from runtime to planning time in
DoublesSketchListArgBaseOperatorConversion, by adding an OperandTypeChecker.
2) Add various JsonIgnores to the sketches to simplify their JSON representations.
3) Allow chaining of ExpressionPostAggregators and other PostAggregators
in the SQL layer.
4) Avoid unnecessary FieldAccessPostAggregator wrapping in the SQL layer,
now that expressions can operate on complex inputs.
5) Adjust return type to thetaSketch (instead of OTHER) in
ThetaSketchSetBaseOperatorConversion.
* Fix benchmark class.
* Fix compilation error.
* Fix ThetaSketchSqlAggregatorTest.
* Hopefully fix ITAutoCompactionTest.
* Adjustment to ITAutoCompactionTest.
* Use lookup memory footprint in MSQ memory computations.
Two main changes:
1) Add estimateHeapFootprint to LookupExtractor.
2) Use this in MSQ's IndexerWorkerContext when determining the total
amount of available memory. It's taken off the top.
This prevents MSQ tasks from running out of memory when there are lookups
defined in the cluster.
* Updates from code review.
* Support for middle manager less druid, tasks launch as k8s jobs
* Fixing forking task runner test
* Test cleanup, dependency cleanup, intellij inspections cleanup
* Changes per PR review
Add configuration option to disable http/https proxy for the k8s client
Update the docs to provide more detail about sidecar support
* Removing un-needed log lines
* Small changes per PR review
* Upon task completion we callback to the overlord to update the status / locaiton, for slower k8s clusters, this reduces locking time significantly
* Merge conflict fix
* Fixing tests and docs
* update tiny-cluster.yaml
changed `enableTaskLevelLogPush` to `encapsulatedTask`
* Apply suggestions from code review
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* Minor changes per PR request
* Cleanup, adding test to AbstractTask
* Add comment in peon.sh
* Bumping code coverage
* More tests to make code coverage happy
* Doh a duplicate dependnecy
* Integration test setup is weird for k8s, will do this in a different PR
* Reverting back all integration test changes, will do in anotbher PR
* use StringUtils.base64 instead of Base64
* Jdk is nasty, if i compress in jdk 11 in jdk 17 the decompressed result is different
Co-authored-by: Rahul Gidwani <r_gidwani@apple.com>
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* introduce a "tree" type to the flattenSpec
* feedback - rename exprs to nodes, use CollectionsUtils.isNullOrEmpty for guard
* feedback - expand docs to more clearly capture limitations of "tree" flattenSpec
* feedback - fix for typo on docs
* introduce a comment to explain defensive copy, tweak null handling
* fix: part of rebase
* mark ObjectFlatteners.FlattenerMaker as an ExtensionPoint and provide default for new tree type
* fix: objectflattener restore previous behavior to call getRootField for root type
* docs: ingestion/data-formats add note that ORC only supports path expressions
* chore: linter remove unused import
* fix: use correct newer form for empty DimensionsSpec in FlattenJSONBenchmark
* add FrontCodedIndexed for delta string encoding
* now for actual segments
* fix indexOf
* fixes and thread safety
* add bucket size 4, which seems generally better
* fixes
* fixes maybe
* update indexes to latest interfaces
* utf8 support
* adjust
* oops
* oops
* refactor, better, faster
* more test
* fixes
* revert
* adjustments
* fix prefixing
* more chill
* sql nested benchmark too
* refactor
* more comments and javadocs
* better get
* remove base class
* fix
* hot rod
* adjust comments
* faster still
* minor adjustments
* spatial index support
* spotbugs
* add isSorted to Indexed to strengthen indexOf contract if set, improve javadocs, add docs
* fix docs
* push into constructor
* use base buffer instead of copy
* oops
Tracking additional improvements requested by @paul-rogers: #13239
* api: refactor page so that indented bullet is child and unindented portion is parent
* get rid of post etc headings and combine them with the endpoint
* Update docs/operations/api-reference.md
Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
* fix broken links
* fix typo
Co-authored-by: Kashif Faraz <kashif.faraz@gmail.com>
Async reads for JDBC:
Prevents JDBC timeouts on long queries by returning empty batches
when a batch fetch takes too long. Uses an async model to run the
result fetch concurrently with JDBC requests.
Fixed race condition in Druid's Avatica server-side handler
Fixed issue with no-user connections
Druid currently uses Zookeeper dependent options as the default.
This commit updates the following to use HTTP as the default instead.
- task runner. `druid.indexer.runner.type=remote -> httpRemote`
- load queue peon. `druid.coordinator.loadqueuepeon.type=curator -> http`
- server inventory view. `druid.serverview.type=curator -> http`
* add a note to the documentation about pre-built HLLSketches
Druid actually supports ingesting a pre-generated sketch column by using
the HLLSketchMerge aggregator. However, this functionality was
previously not made clear in the documentation.
* copyedit from the King's English to American English
* add suggested style changes
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* update log4j example
* fix some style issues
* Update docs/configuration/logging.md
Co-authored-by: Frank Chen <frankchen@apache.org>
Co-authored-by: Frank Chen <frankchen@apache.org>
* Clarified the behaviour of COUNT(DISTINCT column) on multi-value columns
* Update docs/querying/sql-aggregations.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Vadim Ogievetsky <vadimon@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Kashif Faraz
Victoria Lim
Jakub Matyszewski
Clint Wylie
Gian Merlino
Adarsh Sanjeev
Laksh Singla
Abhishek Radhakrishnan
Nhi Pham
Katya Macedo
YongGang
Rishabh Singh
George Shiqi Wu
Maytas Monsereenusorn
317brian
Harini Rajendran
Andreas Maechler
zachjsh
Pramod Immaneni
Peter Marshall
imply-cheddar
Shingo Kitagawa
Karan Kumar
Vadim Ogievetsky
Suneet Saldanha
Jill Osborne
TSFenwick
Tejaswini Bandlamudi
Atul Mohan
Charles Smith
Suraj Sanjay Kadam
Paul Rogers
Nicholas Lippis
frankgrimes97
Arnout Engelen
somu-imply
Abhishek Agarwal
Anshu Makkar
Apoorv Gupta
AdheipSingh
tejasparbat
Win Min Soe
benkrug
Churro
Guy ☀️ Moore
AmatyaAvadhanula
drudi-at-coffee
Sergio Ferragut
Tijo Thomas
sairam devarashetty
Rohan Garg
Eyal Yurman
Didip Kerabat
Jason Koch
cristian-popa
arvindanugula
Jonathan Wei
David Palmer
hosswald