* add new doc
* Apply suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* reorder query laning properties
* rename doc
* new name in doc header
* organize material into "service tiering" section
* text edits and update sidebars.json
* update query laning
* how queries get assigned to lanes
* add more details to intro; use more consistent terminology
* more content
* Apply suggestions from code review
Co-authored-by: Jihoon Son <jihoonson@apache.org>
* Update docs/operations/mixed-workloads.md
* Apply suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* typo
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Jihoon Son <jihoonson@apache.org>
Based on profiling data, about 25% of the time de-serializing DataSchema
is spent on formatting strings in validateId.
This can add up quickly, especially when de-serializing task information
in the overlord, where in can consume almost 2% of CPU if there are many
tasks.
Since the formatting is unnecessary unless the checks fail, we can
leverage the built-in formatting of Preconditions.checkArgument instead
to avoid the cost.
* Pass VirtualColumnRegistry in PlannerContext for join expression planning
* Allow for including VCs from join fact table expression
* Optmize MV_FILTER functions to use a VC when in join fact table expression
* fixup! Allow for including VCs from join fact table expression
* Address review comments
* Ingestion will fail for HLLSketchBuild instead of creating with incorrect values
* Addressing review comments for HLL< updated error message introduced test case
This change mimics what was done in PR #11917 to
fix the incompatibilities produced by #11713. #11917
fixed it with AggregatorFactory by creating default
methods to allow for extensions built against old
jars to still work. This does the same for PostAggregator
* fix delegated smoosh writer and some new facilities for segment writeout medium
changes:
* fixed issue with delegated `SmooshedWriter` when writing files that look like paths, causing `NoSuchFileException` exceptions when attempting to open a channel to the file
* `FileSmoosher.addWithSmooshedWriter` when _not_ delegating now checks that it is still open when closing, making it a no-op if already closed (allowing column serializers to add additional files and avoid delegated mode if they are finished writing out their own content and ned to add additional files)
* add `makeChildWriteOutMedium` to `SegmentWriteOutMedium` interface, which allows users of a shared medium to clean up `WriteOutBytes` if they fully control the lifecycle. there are no callers of this yet, adding for future functionality
* `OnHeapByteBufferWriteOutBytes` now can be marked as not open so it `OnHeapMemorySegmentWriteOutMedium` can now behave identically to other medium implementations
* fix to address nit - use AtomicLong
Related to #11188
The above mentioned PR allowed timeseries queries to return a default result, when queries of type: select count(*) from table where dim1="_not_present_dim_" were executed. Before the PR, it returned no row, after the PR, it would return a row with value of count(*) as 0 (as expected by SQL standards of different dbs).
In Grouping#applyProject, we can sometimes perform optimization of a groupBy query to a timeseries query if possible (when the keys of the groupBy are constants, as generated by automated tools). For example, in select count(*) from table where dim1="_present_dim_" group by "dummy_key", the groupBy clause can be removed. However, in the case when the filter doesn't return anything, i.e. select count(*) from table where dim1="_not_present_dim_" group by "dummy_key", the behavior of general databases would be to return nothing, while druid (due to above change) returns an empty row. This PR aims to fix this divergence of behavior.
Example cases:
select count(*) from table where dim1="_not_present_dim_" group by "dummy_key".
CURRENT: Returns a row with count(*) = 0
EXPECTED: Return no row
select 'A', dim1 from foo where m1 = 123123 and dim1 = '_not_present_again_' group by dim1
CURRENT: Returns a row with ('A', 'wat')
EXPECTED: Return no row
To do this, a boolean droppedDimensionsWhileApplyingProject has been added to Grouping which is true whenever we make changes to the original shape with optimization. Hence if a timeseries query has a grouping with this set to true, we set skipEmptyBuckets=true in the query context (i.e. donot return any row).
* Add http response status code to org.eclipse.jetty.server.RequestLog
* http response code is expressed as an int. Set log msg interpolation based on digit
* trying to add an unit test to verify if the logger.debug method is called
* trying to add an unit test to verify if the logger.debug method is called
* fix compilation issues
* remove test
* Use Druid's extension loading for integration test instead of maven
* fix maven command
* override config path
* load input format extensions and kafka by default; add prepopulated-data group
* all docker-composes are overridable
* fix s3 configs
* override config for all
* fix docker_compose_args
* fix security tests
* turn off debug logs for overlord api calls
* clean up stuff
* revert docker-compose.yml
* fix override config for query error test; fix circular dependency in docker compose
* add back some dependencies in docker compose
* new maven profile for integration test
* example file filter
* 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
Segment pruning for multi-dim partitioning for a given query
DimensionRangeShardSpec#possibleInDomain has been modified to enhance pruning when multi-dim partitioning is used.
Idea
While iterating through each dimension,
If query domain doesn't overlap with the set of permissible values in the segment, the segment is pruned.
If the overlap happens on a boundary, consider the next dimensions.
If there is an overlap within the segment boundaries, the segment cannot be pruned.
This index helps in faster query results during kill task's query on interval based unused segment listing. This can become a bottleneck in some production loads causing coordinator to wait longer for metadata db replies and impacting Kafka ingestion. The modified index has helped reduce the query times for such queries.
DruidLogicalValuesRule while transforming to DruidRel can return incorrect values, if during the creation of the literal it was created from a float value. The BigDecimal representation stores 123.0, and it seems that using RexLiteral's method while conversion returns the inflated value (which is 1230). I am unsure if this is intentional from Calcite's perspective, and the actual change should be done somewhere else.
Extract the values of INT/LONG from the RexLiteral in the DruidLogicalValuesRule, via BigDecimal.longValue() method.
Gian Merlino
Abhishek Agarwal
Maytas Monsereenusorn
Benedict Jin
Victoria Lim
Ivan Vankovich
Clint Wylie
aggarwalakshay
Jonathan Wei
Xavier Léauté
Jihoon Son
Vadim Ogievetsky
Laksh Singla
Rohan Garg
imply-cheddar
somu-imply
Frank Chen
Marcelo R Costa
AmatyaAvadhanula
lokesh-lingarajan
Karan Kumar
Lucas Capistrant