1) Align "Assigning task" log messages between RTR and HRTR.
2) Remove confusing reference to "Coordinator".
3) Move "Not assigning task" message from INFO to DEBUG. It's not super
important to see this message: we mainly want to see what _does_ get
assigned.
4) Reword "Task switched from pending to running" message to better
match the structure of the "Assigning task" message from the same
method.
* Add builder for TaskToolbox.
The main purpose of this change is to make it easier to create
TaskToolboxes in tests. However, the builder is used in production
too, by TaskToolboxFactory.
* Fix imports, adjust formatting.
* Fix import.
* Ensure ByteBuffers allocated in tests get freed.
Many tests had problems where a direct ByteBuffer would be allocated
and then not freed. This is bad because it causes flaky tests.
To fix this:
1) Add ByteBufferUtils.allocateDirect(size), which returns a ResourceHolder.
This makes it easy to free the direct buffer. Currently, it's only used
in tests, because production code seems OK.
2) Update all usages of ByteBuffer.allocateDirect (off-heap) in tests either
to ByteBuffer.allocate (on-heap, which are garbaged collected), or to
ByteBufferUtils.allocateDirect (wherever it seemed like there was a good
reason for the buffer to be off-heap). Make sure to close all direct
holders when done.
* Changes based on CI results.
* A different approach.
* Roll back BitmapOperationTest stuff.
* Try additional surefire memory.
* Revert "Roll back BitmapOperationTest stuff."
This reverts commit 49f846d9e3.
* Add TestBufferPool.
* Revert Xmx change in tests.
* Better behaved NestedQueryPushDownTest. Exit tests on OOME.
* Fix TestBufferPool.
* Remove T1C from ARM tests.
* Somewhat safer.
* Fix tests.
* Fix style stuff.
* Additional debugging.
* Reset null / expr configs better.
* ExpressionLambdaAggregatorFactory thread-safety.
* Alter forkNode to try to get better info when a JVM crashes.
* Fix buffer retention in ExpressionLambdaAggregatorFactory.
* Remove unused import.
- Add user friendly error messages for missing or incorrect OVERWRITE clause for REPLACE SQL query
- Move validation of missing OVERWRITE clause at code level instead of parser for custom error message
* 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
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/configuration/index.md
fix spelling
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
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.
* concurrency: introduce GuardedBy to TaskQueue
* perf: Introduce TaskQueueScaleTest to test performance of TaskQueue with large task counts
This introduces a test case to confirm how long it will take to launch and manage (aka shutdown)
a large number of threads in the TaskQueue.
h/t to @gianm for main implementation.
* perf: improve scalability of TaskQueue with large task counts
* linter fixes, expand test coverage
* pr feedback suggestion; swap to different linter
* swap to use SuppressWarnings
* Fix TaskQueueScaleTest.
Co-authored-by: Gian Merlino <gian@imply.io>
Relevant Issue: #11929
- Add custom replace statement to Druid SQL parser.
- Edit DruidPlanner to convert relevant fields to Query Context.
- Refactor common code with INSERT statements to reuse them for REPLACE where possible.
* Add ipaddress library as dependency.
* IPv4 functions to use the inet.ipaddr package.
* Remove unused imports.
* Add new function.
* Minor rename.
* Add more unit tests.
* IPv4 address expr utils unit tests and address options.
* Adjust the IPv4Util functions.
* Move the UTs a bit around.
* Javadoc comments.
* Add license info for IPAddress.
* Fix groupId, artifact and version in license.yaml.
* Remove redundant subnet in messages - fixes UT.
* Remove unused commons-net dependency for /processing project.
* Make class and methods public so it can be accessed.
* Add initial version of benchmark
* Add subnetutils package for benchmarks.
* Auto generate ip addresses.
* Add more v4 address representations in setup to avoid bias.
* Use ThreadLocalRandom to avoid forbidden API usage.
* Adjust IPv4AddressBenchmark to adhere to codestyle rules.
* Update ipaddress library to latest 5.3.4
* Add ipaddress package dependency to benchmarks project.
Following up on #12315, which pushed most of the logic of building ImmutableBitmap into BitmapIndex in order to hide the details of how column indexes are implemented from the Filter implementations, this PR totally refashions how Filter consume indexes. The end result, while a rather dramatic reshuffling of the existing code, should be extraordinarily flexible, eventually allowing us to model any type of index we can imagine, and providing the machinery to build the filters that use them, while also allowing for other column implementations to implement the built-in index types to provide adapters to make use indexing in the current set filters that Druid provides.
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
* Vectorized version of string last aggregator
* Updating string last and adding testcases
* Updating code and adding testcases for serializable pairs
* Addressing review comments
Fixes#11303
WebIdentityTokenProvider in the defaultAWSCredentialsProviderChain can not actually be used because the aws-java-sdk-sts jar is not in the classpath of S3 extension at runtime, since each extension has its own classpath. This results in the inability to assume STS role before generating authentication token.
The error message from getCredentials() is:
"Unable to load credentials from WebIdentityTokenCredentialsProvider: To use assume role profiles the aws-java-sdk-sts module must be on the class path"
This PR will fix multiple authentication modules that are dependent on the WebIdentityTokenProvider, including AWS IAM based RDS authentication and S3 authentication.
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.
* GroupBy: Reduce allocations by reusing entry and key holders.
Two main changes:
1) Reuse Entry objects returned by various implementations of
Grouper.iterator.
2) Reuse key objects contained within those Entry objects.
This is allowed by the contract, which states that entries must be
processed and immediately discarded. However, not all call sites
respected this, so this patch also updates those call sites.
One particularly sneaky way that the old code retained entries too long
is due to Guava's MergingIterator and CombiningIterator. Internally,
these both advance to the next value prior to returning the current
value. So, this patch addresses that in two ways:
1) For merging, we have our own implementation MergeIterator already,
although it had the same problem. So, this patch updates our
implementation to return the current item prior to advancing to the
next item. It also adds a forbidden-api entry to ensure that this
safer implementation is used instead of Guava's.
2) For combining, we address the problem in a different way: by copying
the key when creating the new, combined entry.
* Attempt to fix test.
* Remove unused import.
* DimensionRangeShardSpec speed boost.
Calling isEmpty() and equals() on RangeSets is expensive, because these
fall back on default implementations that call size(). And size() is
_also_ a default implementation that iterates the entire collection.
* Fix and test from code review.
* 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.
* SQL: Create millisecond precision timestamp literals.
Fixes a bug where implicit casts of strings to timestamps would use seconds
precision rather than milliseconds. The new test case
testCountStarWithBetweenTimeFilterUsingMillisecondsInStringLiterals
exercises this.
* Update sql/src/main/java/org/apache/druid/sql/calcite/planner/Calcites.java
Co-authored-by: Frank Chen <frankchen@apache.org>
* Correct precision handling.
- Set default precision to 3 (millis) for things involving timestamps.
- Respect precision specified in types when available.
* Silence, checkstyle.
Co-authored-by: Frank Chen <frankchen@apache.org>
* JvmMonitor: Handle more generation and collector scenarios.
ZGC on Java 11 only has a generation 1 (there is no 0). This causes
a NullPointerException when trying to extract the spacesCount for
generation 0. In addition, ZGC on Java 15 has a collector number 2
but no spaces in generation 2, which breaks the assumption that
collectors always have same-numbered spaces.
This patch adjusts things to be more robust, enabling the JvmMonitor
to work properly for ZGC on both Java 11 and 15.
* Test adjustments.
* Improve surefire arglines.
* Need a placeholder
machine424
Xavier Léauté
Gian Merlino
Tejaswini Bandlamudi
AmatyaAvadhanula
Charles Smith
Katya Macedo
Adarsh Sanjeev
Clint Wylie
Hellmar Becker
317brian
Frank Chen
Jason Koch
Kashif Faraz
Abhishek Radhakrishnan
Lucas Capistrant
Rohan Garg
somu-imply
Atul Mohan
Vadim Ogievetsky
Victoria Lim
Naya Chen
zachjsh
Rocky Chen
Nishant Bangarwa
aggarwalakshay
MC-JY
Gian Merlino
Frank Chen
Abhishek Agarwal