* Improved docs for range partitioning.
1) Clarify the benefits of range partitioning.
2) Clarify which filters support pruning.
3) Include the fact that multi-value dimensions cannot be used for partitioning.
* Additional clarification.
* Update other section.
* Another adjustment.
* Updates from review.
* docs(fix): clarify how worker.version and minWorkerVersion comparison works
* Revert "docs(fix): clarify how worker.version and minWorkerVersion comparison works"
This reverts commit cadd1fdc60.
* docs(fix): clarify how worker.version and minWorkerVersion comparison works
* Apply suggestions from code review
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* Update docs/configuration/index.md
fix spelling
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In the majority of cases, this improves performance.
There's only one case I'm aware of where this may be a net negative: for time_floor(__time, <period>) where there are many repeated __time values. In nonvectorized processing, SingleLongInputCachingExpressionColumnValueSelector implements an optimization to avoid computing the time_floor function on every row. There is no such optimization in vectorized processing.
IMO, we shouldn't mention this in the docs. Rationale: It's too fiddly of a thing: it's not guaranteed that nonvectorized processing will be faster due to the optimization, because it would have to overcome the inherent speed advantage of vectorization. So it'd always require testing to determine the best setting for a specific dataset. It would be bad if users disabled vectorization thinking it would speed up their queries, and it actually slowed them down. And even if users do their own testing, at some point in the future we'll implement the optimization for vectorized processing too, and it's likely that users that explicitly disabled vectorization will continue to have it disabled. I'd like to avoid this outcome by encouraging all users to enable vectorization at all times. Really advanced users would be following development activity anyway, and can read this issue
Currently all Druid processes share the same log4j2 configuration file located in _common directory. Since peon processes are spawned by middle manager process, they derivate the environment variables from the middle manager. These variables include those in the log4j2.xml controlling to which file the logger writes the log.
But current task logging mechanism requires the peon processes to output the log to console so that the middle manager can redirect the console output to a file and upload this file to task log storage.
So, this PR imposes this requirement to peon processes, whatever the configuration is in the shared log4j2.xml, peon processes always write the log to console.
setting thread names takes a measurable amount of time in the case where segment scans are very quick. In high-QPS testing we found a slight performance boost from turning off processing thread renaming. This option makes that possible.
Allow a Druid cluster to kill segments whose interval_end is a date in the future. This can be done by setting druid.coordinator.kill.durationToRetain to a negative period. For example PT-24H would allow segments to be killed if their interval_end date was 24 hours or less into the future at the time that the kill task is generated by the system.
A cluster operator can also disregard the druid.coordinator.kill.durationToRetain entirely by setting a new configuration, druid.coordinator.kill.ignoreDurationToRetain=true. This ignores interval_end date when looking for segments to kill, and instead is capable of killing any segment marked unused. This new configuration is off by default, and a cluster operator should fully understand and accept the risks if they enable it.
* Add feature flag for sql planning of TimeBoundary queries
* fixup! Add feature flag for sql planning of TimeBoundary queries
* Add documentation for enableTimeBoundaryPlanning
* fixup! Add documentation for enableTimeBoundaryPlanning
This PR is to measure how long a task stays in the pending queue and emits the value with the metric task/pending/time. The metric is measured in RemoteTaskRunner and HttpRemoteTaskRunner.
An example of the metric:
```
2022-04-26T21:59:09,488 INFO [rtr-pending-tasks-runner-0] org.apache.druid.java.util.emitter.core.LoggingEmitter - {"feed":"metrics","timestamp":"2022-04-26T21:59:09.487Z","service":"druid/coordinator","host":"localhost:8081","version":"2022.02.0-iap-SNAPSHOT","metric":"task/pending/time","value":8,"dataSource":"wikipedia","taskId":"index_parallel_wikipedia_gecpcglg_2022-04-26T21:59:09.432Z","taskType":"index_parallel"}
```
------------------------------------------
Key changed/added classes in this PR
Emit metric task/pending/time in classes RemoteTaskRunner and HttpRemoteTaskRunner.
Update related factory classes and tests.
* Reduce allocations due to Jackson serialization.
This patch attacks two sources of allocations during Jackson
serialization:
1) ObjectMapper.writeValue and JsonGenerator.writeObject create a new
DefaultSerializerProvider instance for each call. It has lots of
fields and creates pressure on the garbage collector. So, this patch
adds helper functions in JacksonUtils that enable reuse of
SerializerProvider objects and updates various call sites to make
use of this.
2) GroupByQueryToolChest copies the ObjectMapper for every query to
install a special module that supports backwards compatibility with
map-based rows. This isn't needed if resultAsArray is set and
all servers are running Druid 0.16.0 or later. This release was a
while ago. So, this patch disables backwards compatibility by default,
which eliminates the need to copy the heavyweight ObjectMapper. The
patch also introduces a configuration option that allows admins to
explicitly enable backwards compatibility.
* Add test.
* Update additional call sites and add to forbidden APIs.
* Update caching.md
Knowledge from https://the-asf.slack.com/archives/CJ8D1JTB8/p1597781107153900
Update caching.md
A few additional updates OTBO https://the-asf.slack.com/archives/CJ8D1JTB8/p1608669046041300
* Update caching.md
Typos
* Amendments on the segment cache
Significant updates on content around the segment cache, pull process, and in-memory cache
* Update docs/design/historical.md
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* Update docs/operations/basic-cluster-tuning.md
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* Whole-query caching update
Made more succinct and removed specific config to change.
* Update docs/design/historical.md
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* Update ingestion-spec.md
Added indexSpecForIntermediatePersists as a common configuration property.
* Update ingestion-spec.md
Amended to remove "below" and add link to the table.
* Update ingestion-spec.md
Removed passive.
* Optionally load segment index files into page cache on bootstrap and new segment download
* Fix unit test failure
* Fix test case
* fix spelling
* fix spelling
* fix test and test coverage issues
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* fix(docs): clarify what s3 permissions are needed based on the permissions model
* fix typo
* Update docs/development/extensions-core/s3.md
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* add data format and example for featureSpec
* add second feature in example
* Apply suggestions from code review
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amazon-kinesis-client was not covered undered the apache license and required separate insertion in the kinesis extension.
This can now be avoided since it is covered, and including it within druid helps prevent incompatibilities.
Allows enabling of deaggregation out of the box by packaging amazon-kinesis-client (1.14.4) with druid for kinesis ingestion.
The current default value of inputSegmentSizeBytes is 400MB, which is pretty
low for most compaction use cases. Thus most users are forced to override the
default.
The default value is now increased to Long.MAX_VALUE.
listShards API was used to get all the shards for kinesis ingestion to improve its resiliency as part of #12161.
However, this may require additional permissions in the IAM policy where the stream is present. (Please refer to: https://docs.aws.amazon.com/kinesis/latest/APIReference/API_ListShards.html).
A dynamic configuration useListShards has been added to KinesisSupervisorTuningConfig to control the usage of this API and prevent issues upon upgrade. It can be safely turned on (and is recommended when using kinesis ingestion) by setting this configuration to true.
* Counting nulls in String cardinality with a config
* Adding tests for the new config
* Wrapping the vectorize part to allow backward compatibility
* Adding different tests, cleaning the code and putting the check at the proper position, handling hasRow() and hasValue() changes
* Updating testcase and code
* Adding null handling test to improve coverage
* Checkstyle fix
* Adding 1 more change in docs
* Making docs clearer
* Docs: Masking S3 creds and some rewording
Knowledge transfer from https://groups.google.com/g/druid-user/c/FydcpFrA688
* Removed bold in one of the quote sections
* Update s3.md
* Update s3.md
Quick grammar change
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* Update s3.md
Active lang
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LAng nit
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LAng nit
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* Grammar tidy-up and link fix
Corrected 2 x links to old page H2s, resolved the question around precedence, and some other grammatical changes.
* Update docs/development/extensions-core/s3.md
* Update s3.md
Removed an Erroneous E
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* Update math-expr.md
Link back to transformSpec
* Update ingestion-spec.md
Moved info about using the timestamp inside transforms into the actual timestamp section.
* Update ingestion-spec.md
Active language.
* Update ingestion-spec.md
Added best practice point to dimensions description.
* Update docs/ingestion/ingestion-spec.md
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* add docs for request logging
* remove stray character
* Update docs/operations/request-logging.md
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Added Calcites InQueryThreshold as a query context parameter. Setting this parameter appropriately reduces the time taken for queries with large number of values in their IN conditions.
Add config for eager / lazy connection initialization in ResourcePool
Description
Currently, when multiple tasks are launched, each of them eagerly initializes a full pool's worth of connections to the coordinator.
While this is acceptable when the parameter for number of eagerConnections (== maxSize) is small, this can be problematic in environments where it's a large value (say 1000) and multiple tasks are launched simultaneously, which can cause a large number of connections to be created to the coordinator, thereby overwhelming it.
Patch
Nodes like the broker may require eager initialization of resources and do not create connections with the Coordinator.
It is unnecessary to do this with other types of nodes.
A config parameter eagerInitialization is added, which when set to true, initializes the max permissible connections when ResourcePool is initialized.
If set to false, lazy initialization of connection resources takes place.
NOTE: All nodes except the broker have this new parameter set to false in the quickstart as part of this PR
Algorithm
The current implementation relies on the creation of maxSize resources eagerly.
The new implementation's behaviour is as follows:
If a resource has been previously created and is available, lend it.
Else if the number of created resources is less than the allowed parameter, create and lend it.
Else, wait for one of the lent resources to be returned.
* Tombstone support for replace functionality
* A used segment interval is the interval of a current used segment that overlaps any of the input intervals for the spec
* Update compaction test to match replace behavior
* Adapt ITAutoCompactionTest to work with tombstones rather than dropping segments. Add support for tombstones in the broker.
* Style plus simple queriableindex test
* Add segment cache loader tombstone test
* Add more tests
* Add a method to the LogicalSegment to test whether it has any data
* Test filter with some empty logical segments
* Refactor more compaction/dropexisting tests
* Code coverage
* Support for all empty segments
* Skip tombstones when looking-up broker's timeline. Discard changes made to tool chest to avoid empty segments since they will no longer have empty segments after lookup because we are skipping over them.
* Fix null ptr when segment does not have a queriable index
* Add support for empty replace interval (all input data has been filtered out)
* Fixed coverage & style
* Find tombstone versions from lock versions
* Test failures & style
* Interner was making this fail since the two segments were consider equal due to their id's being equal
* Cleanup tombstone version code
* Force timeChunkLock whenever replace (i.e. dropExisting=true) is being used
* Reject replace spec when input intervals are empty
* Documentation
* Style and unit test
* Restore test code deleted by mistake
* Allocate forces TIME_CHUNK locking and uses lock versions. TombstoneShardSpec added.
* Unused imports. Dead code. Test coverage.
* Coverage.
* Prevent killer from throwing an exception for tombstones. This is the killer used in the peon for killing segments.
* Fix OmniKiller + more test coverage.
* Tombstones are now marked using a shard spec
* Drop a segment factory.json in the segment cache for tombstones
* Style
* Style + coverage
* style
* Add TombstoneLoadSpec.class to mapper in test
* Update core/src/main/java/org/apache/druid/segment/loading/TombstoneLoadSpec.java
Typo
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* Update docs/configuration/index.md
Missing
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* Typo
* Integrated replace with an existing test since the replace part was redundant and more importantly, the test file was very close or exceeding the 10 min default "no output" CI Travis threshold.
* Range does not work with multi-dim
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Charles Smith
Katya Macedo
Gian Merlino
Hellmar Becker
317brian
Frank Chen
Lucas Capistrant
Kashif Faraz
Rohan Garg
Victoria Lim
Rocky Chen
Gian Merlino
zachjsh
Peter Marshall
Apoorv Gupta
jacobtolar
Alexandre BERTHIOT
Maytas Monsereenusorn
Parag Jain
mark-imply
AmatyaAvadhanula
Tejaswini Bandlamudi
somu-imply
Adarsh Sanjeev
Frank Chen
Dr. Sizzles
Agustin Gonzalez