Upstream release: https://github.com/delta-io/delta/releases/tag/v3.2.0
- Upgrade kernel dependency to 3.2.0
- Notable breaking changes introduced in upstream that affects the Druid extension:
- Rename TableClient -> Engine
- Rename DefaultTableClient -> DefaultEngine
- Exceptions moved to a separate package
- Table.getPath() doesn't throw TableNotFoundException. Instead the exception is thrown
when getting snapshot info from the Table object
* enable quidem uri support for `druidtest:///?ComponentSupplier=Nested` and similar
* changes the way `SqlTestFrameworkConfig` is being applied; all options will have their own annotation (its kinda impossible to detect that an annotation has a set value or its the default)
* enables hierarchical processing of config annotation (was needed to enable class level supplier annotation)
* moves uri processing related string2config stuff into `SqlTestFrameworkConfig`
* Delta Lake support for filters.
* Updates
* cleanup comments
* Docs
* Remmove Enclosed runner
* Rename
* Cleanup test
* Serde test for the Delta input source and fix jackson annotation.
* Updates and docs.
* Update error messages to be clearer
* Fixes
* Handle NumberFormatException to provide a nicer error message.
* Apply suggestions from code review
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
* Doc fixes based on feedback
* Yes -> yes in docs; reword slightly.
* Update docs/ingestion/input-sources.md
Co-authored-by: Laksh Singla <lakshsingla@gmail.com>
* Update docs/ingestion/input-sources.md
Co-authored-by: Laksh Singla <lakshsingla@gmail.com>
* Documentation, javadoc and more updates.
* Not with an or expression end-to-end test.
* Break up =, >, >=, <, <= into its own types instead of sub-classing.
---------
Co-authored-by: 317brian <53799971+317brian@users.noreply.github.com>
Co-authored-by: Laksh Singla <lakshsingla@gmail.com>
Changes:
1) Check for handoff of upgraded realtime segments.
2) Drop sink only when all associated realtime segments have been abandoned.
3) Delete pending segments upon commit to prevent unnecessary upgrades and
partition space exhaustion when a concurrent replace happens. This also prevents
potential data duplication.
4) Register pending segment upgrade only on those tasks to which the segment is associated.
Issue: #14989
The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Thereafter, we addressed the problem of publishing schema for realtime segments (#15475). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information.
This is the final change which involves publishing segment schema for finalized segments from task and periodically polling them in the Coordinator.
Statsd client sometimes drops metrics when this queueSize of statsd client with max unprocessed messages is completely full. This causes some high cardinality metrics like per partition lag being droppped.
There are multiple parameters of statsdclient that can be initialized and can help increase the load/capacity of client to not to drop metrics more frequently.
Properties like queueSize, poolSize, processorWorkers and senderWorkers will now be configurable at runtime
Changes:
- Use error code `internalServerError` for failures of this type
- Remove the error code argument from `InternalServerError.exception()` methods
thus fixing a bug in the callers.
Changes:
Add the following indexer level task metrics:
- `worker/task/running/count`
- `worker/task/assigned/count`
- `worker/task/completed/count`
These metrics will provide more visibility into the tasks distribution across indexers
(We often see a task skew issue across indexers and with this issue it would be easier
to catch the imbalance)
* Update Calcite*Test to use junit5
* change the way temp dirs are handled
* add openrewrite workflow to safeguard upgrade
* replace junitparamrunner with standard junit5 parametered tests
* update a few rules to junit5 api
* lots of boring changes
* cleanup QueryLogHook
* cleanup
* fix compile error: ARRAYS_DATASOURCE
* fix test
* remove enclosed
* empty
+TEST:TDigestSketchSqlAggregatorTest,HllSketchSqlAggregatorTest,DoublesSketchSqlAggregatorTest,ThetaSketchSqlAggregatorTest,ArrayOfDoublesSketchSqlAggregatorTest,BloomFilterSqlAggregatorTest,BloomDimFilterSqlTest,CatalogIngestionTest,CatalogQueryTest,FixedBucketsHistogramQuantileSqlAggregatorTest,QuantileSqlAggregatorTest,MSQArraysTest,MSQDataSketchesTest,MSQExportTest,MSQFaultsTest,MSQInsertTest,MSQLoadedSegmentTests,MSQParseExceptionsTest,MSQReplaceTest,MSQSelectTest,InsertLockPreemptedFaultTest,MSQWarningsTest,SqlMSQStatementResourcePostTest,SqlStatementResourceTest,CalciteSelectJoinQueryMSQTest,CalciteSelectQueryMSQTest,CalciteUnionQueryMSQTest,MSQTestBase,VarianceSqlAggregatorTest,SleepSqlTest,SqlRowTransformerTest,DruidAvaticaHandlerTest,DruidStatementTest,BaseCalciteQueryTest,CalciteArraysQueryTest,CalciteCorrelatedQueryTest,CalciteExplainQueryTest,CalciteExportTest,CalciteIngestionDmlTest,CalciteInsertDmlTest,CalciteJoinQueryTest,CalciteLookupFunctionQueryTest,CalciteMultiValueStringQueryTest,CalciteNestedDataQueryTest,CalciteParameterQueryTest,CalciteQueryTest,CalciteReplaceDmlTest,CalciteScanSignatureTest,CalciteSelectQueryTest,CalciteSimpleQueryTest,CalciteSubqueryTest,CalciteSysQueryTest,CalciteTableAppendTest,CalciteTimeBoundaryQueryTest,CalciteUnionQueryTest,CalciteWindowQueryTest,DecoupledPlanningCalciteJoinQueryTest,DecoupledPlanningCalciteQueryTest,DecoupledPlanningCalciteUnionQueryTest,DrillWindowQueryTest,DruidPlannerResourceAnalyzeTest,IngestTableFunctionTest,QueryTestRunner,SqlTestFrameworkConfig,SqlAggregationModuleTest,ExpressionsTest,GreatestExpressionTest,IPv4AddressMatchExpressionTest,IPv4AddressParseExpressionTest,IPv4AddressStringifyExpressionTest,LeastExpressionTest,TimeFormatOperatorConversionTest,CombineAndSimplifyBoundsTest,FiltrationTest,SqlQueryTest,CalcitePlannerModuleTest,CalcitesTest,DruidCalciteSchemaModuleTest,DruidSchemaNoDataInitTest,InformationSchemaTest,NamedDruidSchemaTest,NamedLookupSchemaTest,NamedSystemSchemaTest,RootSchemaProviderTest,SystemSchemaTest,CalciteTestBase,SqlResourceTest
* use @Nested
* add rule to remove enclosed; upgrade surefire
* remove enclosed
* cleanup
* add comment about surefire exclude
Changes:
- Remove deprecated `DruidException` (old one) and `EntryExistsException`
- Use newly added comprehensive `DruidException` instead
- Update error message in `SqlMetadataStorageActionHandler` when max packet limit is violated.
- Factor out common code from several faults into `BaseFault`.
- Slightly update javadoc in `DruidException` to render it correctly
- Remove unused classes `SegmentToMove`, `SegmentToDrop`
- Move `ServletResourceUtils` from module `druid-processing` to `druid-server`
- Add utility method to build error Response from `DruidException`.
* thrust of the fix to allow for the json values to be out of order
The existing problem is that toMap doesn't turn some values into json primitive
values, for example segmentMetadata just has DateTime objects for it's time in
the EventMap, but Alert event converts those into strings when calling toMap.
This creates an issue because when we check the emitted events the mapper
deserializing the string value for dateTime leaves it as a string in the
EventMap. So the question is do we alter the events toMap() to return string/map
version of objects or to make the expected events do a round trip of
eventMap -> string -> eventMap to turn everything into json primitives
* fix issue by making toMap events convert Objects into strings, or maps
* fix linting errors
* use method of using mapper to round trip expected data to make it have same type
as those of the events emitted
* remove unnecessary comment
* Address review comment: add test javadocs
* Fix flaky assertion failure.
Use ConcurrentHashMap instead of HashMap because the producer callback
can trigger concurrently and override the map initialization.
* fixup intellij inspection
* Clean up kafka emitter tests a bit and add more validations.
The test wasn't validating what events were sent, but simply the dropped counters, which
aren't that useful.
Additionally, this module has fewer tests, so folks often run into code coverage issue
in this extension. Hopefully this change helps with that too.
* Change things to feed-based rather than topic-based.
* Another test for shared topic
* Switch to DruidException, add test dependencies and sad path config tests.
* missing test dependency
* minor renames.
* Add more tests - to test unknown events and drop when queue is full
* allow for kafka-emitter to have extra dimensions be set for each event it emits
* fix checktsyle issue in kafkaemitterconfig
* make changes to fix docs, and cleanup copy paste error in #toString()
* undo formatting to markdown table
* add more branches so test passes
* fix checkstyle issue
* Update the group id to org.apache.druid.extensions.contrib for contrib exts.
* Note iceberg and delta lake extensions in extensions.md
* properties and shell backticks
* Update groupId in distribution/pom.xml
* remove delta-lake from dist.
* Add note on downloading extension.
During ingestion, incremental segments are created in memory for the different time chunks and persisted to disk when certain thresholds are reached (max number of rows, max memory, incremental persist period etc). In the case where there are a lot of dimension and metrics (1000+) it was observed that the creation/serialization of incremental segment file format for persistence and persisting the file took a while and it was blocking ingestion of new data. This affected the real-time ingestion. This serialization and persistence can be parallelized across the different time chunks. This update aims to do that.
The patch adds a simple configuration parameter to the ingestion tuning configuration to specify number of persistence threads. The default value is 1 if it not specified which makes it the same as it is today.
This patch bumps Delta Lake Kernel dependency from 3.0.0 to 3.1.0, which released last week - please see https://github.com/delta-io/delta/releases/tag/v3.1.0 for release notes.
There were a few "breaking" API changes in 3.1.0, you can find the rationale for some of those changes here.
Next-up in this extension: add and expose filter predicates.
* something
* test commit
* compilation fix
* more compilation fixes (fixme placeholders)
* Comment out druid-kereberos build since it conflicts with newly added transitive deps from delta-lake
Will need to sort out the dependencies later.
* checkpoint
* remove snapshot schema since we can get schema from the row
* iterator bug fix
* json json json
* sampler flow
* empty impls for read(InputStats) and sample()
* conversion?
* conversion, without timestamp
* Web console changes to show Delta Lake
* Asset bug fix and tile load
* Add missing pieces to input source info, etc.
* fix stuff
* Use a different delta lake asset
* Delta lake extension dependencies
* Cleanup
* Add InputSource, module init and helper code to process delta files.
* Test init
* Checkpoint changes
* Test resources and updates
* some fixes
* move to the correct package
* More tests
* Test cleanup
* TODOs
* Test updates
* requirements and javadocs
* Adjust dependencies
* Update readme
* Bump up version
* fixup typo in deps
* forbidden api and checkstyle checks
* Trim down dependencies
* new lines
* Fixup Intellij inspections.
* Add equals() and hashCode()
* chain splits, intellij inspections
* review comments and todo placeholder
* fix up some docs
* null table path and test dependencies. Fixup broken link.
* run prettify
* Different test; fixes
* Upgrade pyspark and delta-spark to latest (3.5.0 and 3.0.0) and regenerate tests
* yank the old test resource.
* add a couple of sad path tests
* Updates to readme based on latest.
* Version support
* Extract Delta DateTime converstions to DeltaTimeUtils class and add test
* More comprehensive split tests.
* Some test renames.
* Cleanup and update instructions.
* add pruneSchema() optimization for table scans.
* Oops, missed the parquet files.
* Update default table and rename schema constants.
* Test setup and misc changes.
* Add class loader logic as the context class loader is unaware about extension classes
* change some table client creation logic.
* Add hadoop-aws, hadoop-common and related exclusions.
* Remove org.apache.hadoop:hadoop-common
* Apply suggestions from code review
Co-authored-by: Victoria Lim <vtlim@users.noreply.github.com>
* Add entry to .spelling to fix docs static check
---------
Co-authored-by: abhishekagarwal87 <1477457+abhishekagarwal87@users.noreply.github.com>
Co-authored-by: Laksh Singla <lakshsingla@gmail.com>
Co-authored-by: Victoria Lim <vtlim@users.noreply.github.com>
* Possibly stabilize intellij-inspections
* remove `integration-tests-ex/cases` from excluded projects from initial build
* enable ErrorProne's `CheckedExceptionNotThrown` to get earlier errors than intellij-inspections
* fix ddsketch pom.xml
* fix spellcheck
* New: Add DDSketch-Druid extension
- Based off of http://www.vldb.org/pvldb/vol12/p2195-masson.pdf and uses
the corresponding https://github.com/DataDog/sketches-java library
- contains tests for post building and using aggregation/post
aggregation.
- New aggregator: `ddSketch`
- New post aggregators: `quantileFromDDSketch` and
`quantilesFromDDSketch`
* Fixing easy CodeQL warnings/errors
* Fixing docs, and dependencies
Also moved aggregator ids to AggregatorUtil and PostAggregatorIds
* Adding more Docs and better null/empty handling for aggregators
* Fixing docs, and pom version
* DDSketch documentation format and wording
### Description
Our Kinesis consumer works by using the [GetRecords API](https://docs.aws.amazon.com/kinesis/latest/APIReference/API_GetRecords.html) in some number of `fetchThreads`, each fetching some number of records (`recordsPerFetch`) and each inserting into a shared buffer that can hold a `recordBufferSize` number of records. The logic is described in our documentation at: https://druid.apache.org/docs/27.0.0/development/extensions-core/kinesis-ingestion/#determine-fetch-settings
There is a problem with the logic that this pr fixes: the memory limits rely on a hard-coded “estimated record size” that is `10 KB` if `deaggregate: false` and `1 MB` if `deaggregate: true`. There have been cases where a supervisor had `deaggregate: true` set even though it wasn’t needed, leading to under-utilization of memory and poor ingestion performance.
Users don’t always know if their records are aggregated or not. Also, even if they could figure it out, it’s better to not have to. So we’d like to eliminate the `deaggregate` parameter, which means we need to do memory management more adaptively based on the actual record sizes.
We take advantage of the fact that GetRecords doesn’t return more than 10MB (https://docs.aws.amazon.com/streams/latest/dev/service-sizes-and-limits.html ):
This pr:
eliminates `recordsPerFetch`, always use the max limit of 10000 records (the default limit if not set)
eliminate `deaggregate`, always have it true
cap `fetchThreads` to ensure that if each fetch returns the max (`10MB`) then we don't exceed our budget (`100MB` or `5% of heap`). In practice this means `fetchThreads` will never be more than `10`. Tasks usually don't have that many processors available to them anyway, so in practice I don't think this will change the number of threads for too many deployments
add `recordBufferSizeBytes` as a bytes-based limit rather than records-based limit for the shared queue. We do know the byte size of kinesis records by at this point. Default should be `100MB` or `10% of heap`, whichever is smaller.
add `maxBytesPerPoll` as a bytes-based limit for how much data we poll from shared buffer at a time. Default is `1000000` bytes.
deprecate `recordBufferSize`, use `recordBufferSizeBytes` instead. Warning is logged if `recordBufferSize` is specified
deprecate `maxRecordsPerPoll`, use `maxBytesPerPoll` instead. Warning is logged if maxRecordsPerPoll` is specified
Fixed issue that when the record buffer is full, the fetchRecords logic throws away the rest of the GetRecords result after `recordBufferOfferTimeout` and starts a new shard iterator. This seems excessively churny. Instead, wait an unbounded amount of time for queue to stop being full. If the queue remains full, we’ll end up right back waiting for it after the restarted fetch.
There was also a call to `newQ::offer` without check in `filterBufferAndResetBackgroundFetch`, which seemed like it could cause data loss. Now checking return value here, and failing if false.
### Release Note
Kinesis ingestion memory tuning config has been greatly simplified, and a more adaptive approach is now taken for the configuration. Here is a summary of the changes made:
eliminates `recordsPerFetch`, always use the max limit of 10000 records (the default limit if not set)
eliminate `deaggregate`, always have it true
cap `fetchThreads` to ensure that if each fetch returns the max (`10MB`) then we don't exceed our budget (`100MB` or `5% of heap`). In practice this means `fetchThreads` will never be more than `10`. Tasks usually don't have that many processors available to them anyway, so in practice I don't think this will change the number of threads for too many deployments
add `recordBufferSizeBytes` as a bytes-based limit rather than records-based limit for the shared queue. We do know the byte size of kinesis records by at this point. Default should be `100MB` or `10% of heap`, whichever is smaller.
add `maxBytesPerPoll` as a bytes-based limit for how much data we poll from shared buffer at a time. Default is `1000000` bytes.
deprecate `recordBufferSize`, use `recordBufferSizeBytes` instead. Warning is logged if `recordBufferSize` is specified
deprecate `maxRecordsPerPoll`, use `maxBytesPerPoll` instead. Warning is logged if maxRecordsPerPoll` is specified
This change intelligently provisions the correct number of threads per scheduled task. 1 for each event type, and 1 for logging the lost events.
This is a change to make this work. But in the future it would be worthwhile to make each task not be greedy and share threads so there isn't a need of a thread per task.
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Adarsh Sanjeev
Kashif Faraz
AmatyaAvadhanula
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Rishabh Singh
Hardik Bajaj
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Rushikesh Bankar
YongGang
Clint Wylie
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