Compressed Big Decimal is an extension which provides support for
Mutable big decimal value that can be used to accumulate values
without losing precision or reallocating memory. This type helps in
absolute precision arithmetic on large numbers in applications,
where greater level of accuracy is required, such as financial
applications, currency based transactions. This helps avoid rounding
issues where in potentially large amount of money can be lost.
Accumulation requires that the two numbers have the same scale,
but does not require that they are of the same size. If the value
being accumulated has a larger underlying array than this value
(the result), then the higher order bits are dropped, similar to what
happens when adding a long to an int and storing the result in an
int. A compressed big decimal that holds its data with an embedded
array.
Compressed big decimal is an absolute number based complex type
based on big decimal in Java. This supports all the functionalities
supported by Java Big Decimal. Java Big Decimal is not mutable in
order to avoid big garbage collection issues. Compressed big decimal
is needed to mutate the value in the accumulator.
* KLL sketch
* added documentation
* direct static refs
* direct static refs
* fixed test
* addressed review points
* added KLL sketch related terms
* return a copy from get
* Copy unions when returning them from "get".
* Remove redundant "final".
Co-authored-by: AlexanderSaydakov <AlexanderSaydakov@users.noreply.github.com>
Co-authored-by: Gian Merlino <gianmerlino@gmail.com>
* change kafka lookups module to not commit offsets
The current behaviour of the Kafka lookup extractor is to not commit
offsets by assigning a unique ID to the consumer group and setting
auto.offset.reset to earliest. This does the job but also pollutes the
Kafka broker with a bunch of "ghost" consumer groups that will never again be
used.
To fix this, we now set enable.auto.commit to false, which prevents the
ghost consumer groups being created in the first place.
* update docs to include new enable.auto.commit setting behaviour
* update kafka-lookup-extractor documentation
Provide some additional detail on functionality and configuration.
Hopefully this will make it clearer how the extractor works for
developers who aren't so familiar with Kafka.
* add comments better explaining the logic of the code
* add spelling exceptions for kafka lookup docs
* Improved Java 17 support and Java runtime docs.
1) Add a "Java runtime" doc page with information about supported
Java versions, garbage collection, and strong encapsulation..
2) Update asm and equalsverifier to versions that support Java 17.
3) Add additional "--add-opens" lines to surefire configuration, so
tests can pass successfully under Java 17.
4) Switch openjdk15 tests to openjdk17.
5) Update FrameFile to specifically mention Java runtime incompatibility
as the cause of not being able to use Memory.map.
6) Update SegmentLoadDropHandler to log an error for Errors too, not
just Exceptions. This is important because an IllegalAccessError is
encountered when the correct "--add-opens" line is not provided,
which would otherwise be silently ignored.
7) Update example configs to use druid.indexer.runner.javaOptsArray
instead of druid.indexer.runner.javaOpts. (The latter is deprecated.)
* Adjustments.
* Use run-java in more places.
* Add run-java.
* Update .gitignore.
* Exclude hadoop-client-api.
Brought in when building on Java 17.
* Swap one more usage of java.
* Fix the run-java script.
* Fix flag.
* Include link to Temurin.
* Spelling.
* Update examples/bin/run-java
Co-authored-by: Xavier Léauté <xl+github@xvrl.net>
Co-authored-by: Xavier Léauté <xl+github@xvrl.net>
* Add TIME_IN_INTERVAL SQL operator.
The operator is implemented as a convertlet rather than an
OperatorConversion, because this allows it to be equivalent to using
the >= and < operators directly.
* SqlParserPos cannot be null here.
* Remove unused import.
* Doc updates.
* Add words to dictionary.
* Emit state of replace and append for native batch tasks
* Emit count of one depending on batch ingestion mode (APPEND, OVERWRITE, REPLACE)
* Add metric to compaction job
* Avoid null ptr exc when null emitter
* Coverage
* Emit tombstone & segment counts
* Tasks need a type
* Spelling
* Integrate BatchIngestionMode in batch ingestion tasks functionality
* Typos
* Remove batch ingestion type from metric since it is already in a dimension. Move IngestionMode to AbstractTask to facilitate having mode as a dimension. Add metrics to streaming. Add missing coverage.
* Avoid inner class referenced by sub-class inspection. Refactor computation of IngestionMode to make it more robust to null IOConfig and fix test.
* Spelling
* Avoid polluting the Task interface
* Rename computeCompaction methods to avoid ambiguous java compiler error if they are passed null. Other minor cleanup.
* ConcurrentGrouper: Add option to always slice up merge buffers thread-locally.
Normally, the ConcurrentGrouper shares merge buffers across processing
threads until spilling starts, and then switches to a thread-local model.
This minimizes memory use and reduces likelihood of spilling, which is
good, but it creates thread contention. The new mergeThreadLocal option
causes a query to start in thread-local mode immediately, and allows us
to experiment with the relative performance of the two modes.
* Fix grammar in docs.
* Fix race in ConcurrentGrouper.
* Fix issue with timeouts.
* Remove unused import.
* Add "tradeoff" to dictionary.
* SQL: Add is_active to sys.segments, update examples and docs.
is_active is short for:
(is_published = 1 AND is_overshadowed = 0) OR is_realtime = 1
It's important because this represents "all the segments that should
be queryable, whether or not they actually are right now". Most of the
time, this is the set of segments that people will want to look at.
The web console already adds this filter to a lot of its queries,
proving its usefulness.
This patch also reworks the caveat at the bottom of the sys.segments
section, so its information is mixed into the description of each result
field. This should make it more likely for people to see the information.
* Wording updates.
* Adjustments for spellcheck.
* Adjust IT.
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
* 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
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.
* GroupBy: Cap dictionary-building selector memory usage.
New context parameter "maxSelectorDictionarySize" controls when the
per-segment processing code should return early and trigger a trip
to the merge buffer.
Includes:
- Vectorized and nonvectorized implementations.
- Adjustments to GroupByQueryRunnerTest to exercise this code in
the v2SmallDictionary suite. (Both the selector dictionary and
the merging dictionary will be small in that suite.)
- Tests for the new config parameter.
* Fix issues from tests.
* Add "pre-existing" to dictionary.
* Simplify GroupByColumnSelectorStrategy interface by removing one of the writeToKeyBuffer methods.
* Adjustments from review comments.
Azure Blob storage has multiple modes of authentication. One of them is Shared access resource
. This is very useful in cases when we do not want to add the account key in the druid properties .
As part of #12078 one of the followup's was to have a specific config which does not allow accidental unnesting of multi value columns if such columns become part of the grouping key.
Added a config groupByEnableMultiValueUnnesting which can be set in the query context.
The default value of groupByEnableMultiValueUnnesting is true, therefore it does not change the current engine behavior.
If groupByEnableMultiValueUnnesting is set to false, the query will fail if it encounters a multi-value column in the grouping key.
* Moving in filter check to broker
* Adding more unit tests, making error message meaningful
* Spelling and doc changes
* Updating default to -1 and making this feature hide by default. The number of IN filters can grow upto a max limit of 100
* Removing upper limit of 100, updated docs
* Making documentation more meaningful
* Moving check outside to PlannerConfig, updating test cases and adding back max limit
* Updated with some additional code comments
* Missed removing one line during the checkin
* Addressing doc changes and one forbidden API correction
* Final doc change
* Adding a speling exception, correcting a testcase
* Reading entire filter tree to address combinations of ANDs and ORs
* Specifying in docs that, this case works only for ORs
* Revert "Reading entire filter tree to address combinations of ANDs and ORs"
This reverts commit 81ca8f8496.
* Covering a class cast exception and updating docs
* Counting changed
Co-authored-by: Jihoon Son <jihoonson@apache.org>
* refactor and link fixes
* add sql docs to left nav
* code format for needle
* updated web console script
* link fixes
* update earliest/latest functions
* edits for grammar and style
* more link fixes
* another link
* update with #12226
* update .spelling file
* Thread pool for broker
* Updating two tests to improve coverage for new method added
* Updating druidProcessingConfigTest to cover coverage
* Adding missed spelling errors caused in doc
* Adding test to cover lines of new function added
* Add jsonPath functions support
* Add jsonPath function test for Avro
* Add jsonPath function length() to Orc
* Add jsonPath function length() to Parquet
* Add more tests to ORC format
* update doc
* Fix exception during ingestion
* Add IT test case
* Revert "Fix exception during ingestion"
This reverts commit 5a5484b9ea.
* update IT test case
* Add 'keys()'
* Commit IT test case
* Fix UT
changes:
* adds new config, druid.expressions.useStrictBooleans which make longs the official boolean type of all expressions
* vectorize logical operators and boolean functions, some only if useStrictBooleans is true
* add impl
* fix checkstyle
* add test
* add test
* add unit tests
* fix unit tests
* fix unit tests
* fix unit tests
* add IT
* add IT
* add comments
* fix spelling
* IMPLY-4344: Adding safe divide function along with testcases and documentation updates
* Changing based on review comments
* Addressing review comments, fixing coding style, docs and spelling
* Checkstyle passes for all code
* Fixing expected results for infinity
* Revert "Fixing expected results for infinity"
This reverts commit 5fd5cd480d.
* Updating test result and a space in docs
Add support for hadoop 3 profiles . Most of the details are captured in #11791 .
We use a combination of maven profiles and resource filtering to achieve this. Hadoop2 is supported by default and a new maven profile with the name hadoop3 is created. This will allow the user to choose the profile which is best suited for the use case.
* Add druid.sql.approxCountDistinct.function property.
The new property allows admins to configure the implementation for
APPROX_COUNT_DISTINCT and COUNT(DISTINCT expr) in approximate mode.
The motivation for adding this setting is to enable site admins to
switch the default HLL implementation to DataSketches.
For example, an admin can set:
druid.sql.approxCountDistinct.function = APPROX_COUNT_DISTINCT_DS_HLL
* Fixes
* Fix tests.
* Remove erroneous cannotVectorize.
* Remove unused import.
* Remove unused test imports.
317brian
senthilkv
Alexander Saydakov
Victoria Lim
Clint Wylie
Rohan Garg
David Palmer
Gian Merlino
Katya Macedo
Atul Mohan
zachjsh
Tejaswini Bandlamudi
Agustin Gonzalez
Frank Chen
Lucas Capistrant
somu-imply
Adarsh Sanjeev
Gian Merlino
Karan Kumar
Frank Chen
Charles Smith
Maytas Monsereenusorn
Kashif Faraz
sthetland
Jian Wang
Arun Ramani