* 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.
### Description
Today we ingest a number of high cardinality metrics into Druid across dimensions. These metrics are rolled up on a per minute basis, and are very useful when looking at metrics on a partition or client basis. Events is another class of data that provides useful information about a particular incident/scenario inside a Kafka cluster. Events themselves are carried inside kafka payload, but nonetheless there are some very useful metadata that is carried in kafka headers that can serve as useful dimension for aggregation and in turn bringing better insights.
PR(https://github.com/apache/druid/pull/10730) introduced support of Kafka headers in InputFormats.
We still need an input format to parse out the headers and translate those into relevant columns in Druid. Until that’s implemented, none of the information available in the Kafka message headers would be exposed. So first there is a need to write an input format that can parse headers in any given format(provided we support the format) like we parse payloads today. Apart from headers there is also some useful information present in the key portion of the kafka record. We also need a way to expose the data present in the key as druid columns. We need a generic way to express at configuration time what attributes from headers, key and payload need to be ingested into druid. We need to keep the design generic enough so that users can specify different parsers for headers, key and payload.
This PR is designed to solve the above by providing wrapper around any existing input formats and merging the data into a single unified Druid row.
Lets look at a sample input format from the above discussion
"inputFormat":
{
"type": "kafka", // New input format type
"headerLabelPrefix": "kafka.header.", // Label prefix for header columns, this will avoid collusions while merging columns
"recordTimestampLabelPrefix": "kafka.", // Kafka record's timestamp is made available in case payload does not carry timestamp
"headerFormat": // Header parser specifying that values are of type string
{
"type": "string"
},
"valueFormat": // Value parser from json parsing
{
"type": "json",
"flattenSpec": {
"useFieldDiscovery": true,
"fields": [...]
}
},
"keyFormat": // Key parser also from json parsing
{
"type": "json"
}
}
Since we have independent sections for header, key and payload, it will enable parsing each section with its own parser, eg., headers coming in as string and payload as json.
KafkaInputFormat will be the uber class extending inputFormat interface and will be responsible for creating individual parsers for header, key and payload, blend the data resolving conflicts in columns and generating a single unified InputRow for Druid ingestion.
"headerFormat" will allow users to plug parser type for the header values and will add default header prefix as "kafka.header."(can be overridden) for attributes to avoid collision while merging attributes with payload.
Kafka payload parser will be responsible for parsing the Value portion of the Kafka record. This is where most of the data will come from and we should be able to plugin existing parser. One thing to note here is that if batching is performed, then the code is augmenting header and key values to every record in the batch.
Kafka key parser will handle parsing Key portion of the Kafka record and will ingest the Key with dimension name as "kafka.key".
## KafkaInputFormat Class:
This is the class that orchestrates sending the consumerRecord to each parser, retrieve rows, merge the columns into one final row for Druid consumption. KafkaInputformat should make sure to release the resources that gets allocated as a part of reader in CloseableIterator<InputRow> during normal and exception cases.
During conflicts in dimension/metrics names, the code will prefer dimension names from payload and ignore the dimension either from headers/key. This is done so that existing input formats can be easily migrated to this new format without worrying about losing information.
* Configurable maxStreamLength for doubles sketches
* fix equals/hashcode and it test failure
* fix test
* fix it test
* benchmark
* doc
* grouping key
* fix comment
* dependency check
* Update docs/development/extensions-core/datasketches-quantiles.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/querying/sql.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Add details to the Docker tutorial
Added links, explanations and other details to the Docker
tutorial to make it easier for first-time users.
* Fix spelling error
And add "Jupyter" to the spelling dictionary.
* Update docs/tutorials/docker.md
* Update docs/tutorials/docker.md
Co-authored-by: sthetland <steve.hetland@imply.io>
* Update docs/tutorials/docker.md
Co-authored-by: sthetland <steve.hetland@imply.io>
* Update docs/tutorials/docker.md
* Update docs/tutorials/docker.md
Co-authored-by: sthetland <steve.hetland@imply.io>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: sthetland <steve.hetland@imply.io>
Fixes#11297.
Description
Description and design in the proposal #11297
Key changed/added classes in this PR
*DataSegmentPusher
*ShuffleClient
*PartitionStat
*PartitionLocation
*IntermediaryDataManager
* add binary_byte_format/decimal_byte_format/decimal_format
* clean code
* fix doc
* fix review comments
* add spelling check rules
* remove extra param
* improve type handling and null handling
* remove extra zeros
* fix tests and add space between unit suffix and number as most size-format functions do
* fix tests
* add examples
* change function names according to review comments
* fix merge
Signed-off-by: frank chen <frank.chen021@outlook.com>
* no need to configure NullHandling explicitly for tests
Signed-off-by: frank chen <frank.chen021@outlook.com>
* fix tests in SQL-Compatible mode
Signed-off-by: frank chen <frank.chen021@outlook.com>
* Resolve review comments
* Update SQL test case to check null handling
* Fix intellij inspections
* Add more examples
* Fix example
This change allows the selection of a specific broker service (or broker tier) by the Router.
The newly added ManualTieredBrokerSelectorStrategy works as follows:
Check for the parameter brokerService in the query context. If this is a valid broker service, use it.
Check if the field defaultManualBrokerService has been set in the strategy. If this is a valid broker service, use it.
Move on to the next strategy
* Avro union support
* Document new union support
* Add support for AvroStreamInputFormat and fix checkstyle
* Extend multi-member union test schema and format
* Some additional docs and add Enums to spelling
* Rename explodeUnions -> extractUnions
* explode -> extract
* ByType
* Correct spelling error
With this change, Druid will only support ZooKeeper 3.5.x and later.
In order to support Java 15 we need to switch to ZK 3.5.x client libraries and drop support for ZK 3.4.x
(see #10780 for the detailed reasons)
* remove ZooKeeper 3.4.x compatibility
* exclude additional ZK 3.5.x netty dependencies to ensure we use our version
* keep ZooKeeper version used for integration tests in sync with client library version
* remove the need to specify ZK version at runtime for docker
* add support to run integration tests with JDK 15
* build and run unit tests with Java 15 in travis
* allow user to set group.id for Kafka ingestion task
* fix test coverage by removing deprecated code and add doc
* fix typo
* Update docs/development/extensions-core/kafka-ingestion.md
Co-authored-by: frank chen <frankchen@apache.org>
Co-authored-by: frank chen <frankchen@apache.org>
* lay the groundwork for throttling replicant loads per RunRules execution
* Add dynamic coordinator config to control new replicant threshold.
* remove redundant line
* add some unit tests
* fix checkstyle error
* add documentation for new dynamic config
* improve docs and logs
* Alter how null is handled for new config. If null, manually set as default
* ARRAY_AGG sql aggregator function
* add javadoc
* spelling
* review stuff, return null instead of empty when nil input
* review stuff
* Update sql.md
* use type inference for finalize, refactor some things
* add experimental expression aggregator
* add test
* fix lgtm
* fix test
* adjust test
* use not null constant
* array_set_concat docs
* add equals and hashcode and tostring
* fix it
* spelling
* do multi-value magic for expression agg, more javadocs, tests
* formatting
* fix inspection
* more better
* nullable
* add protobuf inputformat
* repair pom
* alter intermediateRow to type of Dynamicmessage
* add document
* refine test
* fix document
* add protoBytesDecoder
* refine document and add ser test
* add hash
* add schema registry ser test
Co-authored-by: yuanyi <yuanyi@freewheel.tv>
* Add ability to wait for segment availability for batch jobs
* IT updates
* fix queries in legacy hadoop IT
* Fix broken indexing integration tests
* address an lgtm flag
* spell checker still flagging for hadoop doc. adding under that file header too
* fix compaction IT
* Updates to wait for availability method
* improve unit testing for patch
* fix bad indentation
* refactor waitForSegmentAvailability
* Fixes based off of review comments
* cleanup to get compile after merging with master
* fix failing test after previous logic update
* add back code that must have gotten deleted during conflict resolution
* update some logging code
* fixes to get compilation working after merge with master
* reset interrupt flag in catch block after code review pointed it out
* small changes following self-review
* fixup some issues brought on by merge with master
* small changes after review
* cleanup a little bit after merge with master
* Fix potential resource leak in AbstractBatchIndexTask
* syntax fix
* Add a Compcation TuningConfig type
* add docs stipulating the lack of support by Compaction tasks for the new config
* Fixup compilation errors after merge with master
* Remove erreneous newline
* DruidInputSource: Fix issues in column projection, timestamp handling.
DruidInputSource, DruidSegmentReader changes:
1) Remove "dimensions" and "metrics". They are not necessary, because we
can compute which columns we need to read based on what is going to
be used by the timestamp, transform, dimensions, and metrics.
2) Start using ColumnsFilter (see below) to decide which columns we need
to read.
3) Actually respect the "timestampSpec". Previously, it was ignored, and
the timestamp of the returned InputRows was set to the `__time` column
of the input datasource.
(1) and (2) together fix a bug in which the DruidInputSource would not
properly read columns that are used as inputs to a transformSpec.
(3) fixes a bug where the timestampSpec would be ignored if you attempted
to set the column to something other than `__time`.
(1) and (3) are breaking changes.
Web console changes:
1) Remove "Dimensions" and "Metrics" from the Druid input source.
2) Set timestampSpec to `{"column": "__time", "format": "millis"}` for
compatibility with the new behavior.
Other changes:
1) Add ColumnsFilter, a new class that allows input readers to determine
which columns they need to read. Currently, it's only used by the
DruidInputSource, but it could be used by other columnar input sources
in the future.
2) Add a ColumnsFilter to InputRowSchema.
3) Remove the metric names from InputRowSchema (they were unused).
4) Add InputRowSchemas.fromDataSchema method that computes the proper
ColumnsFilter for given timestamp, dimensions, transform, and metrics.
5) Add "getRequiredColumns" method to TransformSpec to support the above.
* Various fixups.
* Uncomment incorrectly commented lines.
* Move TransformSpecTest to the proper module.
* Add druid.indexer.task.ignoreTimestampSpecForDruidInputSource setting.
* Fix.
* Fix build.
* Checkstyle.
* Misc fixes.
* Fix test.
* Move config.
* Fix imports.
* Fixup.
* Fix ShuffleResourceTest.
* Add import.
* Smarter exclusions.
* Fixes based on tests.
Also, add TIME_COLUMN constant in the web console.
* Adjustments for tests.
* Reorder test data.
* Update docs.
* Update docs to say Druid 0.22.0 instead of 0.21.0.
* Fix test.
* Fix ITAutoCompactionTest.
* Changes from review & from merging.
* first pass compaction refactor. includes updated behavior for queryGranularity. removes duplicated doc
* fix links, typos, some reorganization
* fix spelling. TBD still there for work in progress
* updates tutorial examples, adds more clarification around compaction use cases
* add granularity spec to automatic compaction config
* final edits
* spelling fixes
* apply suggestions from review
* upadtes from review
* last edits
* move note
* clarify null
* fix links & spelling
* latest review
* edits to auto-compaction config
* add back rollup
* fix links & spelling
* Update compaction.md
add granularityspec to example
* prometheus-emitter
* use existing jetty server to expose prometheus collection endpoint
* unused variables
* better variable names
* removed unused dependencies
* more metric definitions
* reorganize
* use prometheus HTTPServer instead of hooking into Jetty server
* temporary empty help string
* temporary non-empty help. fix incorrect dimension value in JSON (also updated statsd json)
* added full help text. added metric conversion factor for timers that are not using seconds. Correct metric dimension name in documentation
* added documentation for prometheus emitter
* safety for invalid labelNames
* fix travis checks
* Unit test and better sanitization of metrics names and label values
* add precondition to check namespace against regex
* use precompiled regex
* remove static imports. fix metric types
* better docs. fix possible NPE in PrometheusEmitterConfig. Guard against multiple calls to PrometheusEmitter.start()
* Update regex for label-value replacements to allow internal numeric values. Additional tests
* Adds missing license header
updates website/.spelling to add words used in prometheus-emitter docs.
updates docs/operations/metrics.md to correct the spelling of
bufferPoolName
* fixes version in extensions-contrib/prometheus-emitter
* fix style guide errors
* update import ordering
* add another word to website/.spelling
* remove unthrown declared exception
* remove unused import
* Pushgateway strategy for metrics
* typo
* Format fix and nullable strategy
* Update pom file for prometheus-emitter
* code review comments. Counter to gauge for cache metrics, periodical task to pushGateway
* Syntax fix
* Dimension label regex include numeric character back, fix previous commit
* bump prometheus-emitter pom dev version
* Remove scheduled task inside poen that push metrics
* Fix checkstyle
* Unit test coverage
* Unit test coverage
* Spelling
* Doc fix
* spelling
Co-authored-by: Michael Schiff <michael.schiff@tubemogul.com>
Co-authored-by: Michael Schiff <schiff.michael@gmail.com>
Co-authored-by: Tianxin Zhao <tianxin.zhao@tubemogul.com>
Co-authored-by: Tianxin Zhao <tizhao@adobe.com>
* Add config and header support for confluent schema registry. (porting code from https://github.com/apache/druid/pull/9096)
* Add Eclipse Public License 2.0 to license check
* Update licenses.yaml, revert changes to check-licenses.py and dependencies for integration-tests
* Add spelling exception and remove unused dependency
* Use non-deprecated getSchemaById() and remove duplicated license entry
* Update docs/ingestion/data-formats.md
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* Added check for schema being null, as per Confluent code
* Missing imports and whitespace
* Updated unit tests with AvroSchema
Co-authored-by: Sergio Spinatelli <sergio.spinatelli.extern@7-tv.de>
Co-authored-by: Sergio Spinatelli <sergio.spinatelli.extern@joyn.de>
Co-authored-by: Clint Wylie <cjwylie@gmail.com>
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix checkstyle
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* fix test
* fix test
* add log
* Fix byte calculation for maxBytesInMemory to take into account of Sink/Hydrant Object overhead
* address comments
* fix checkstyle
* fix checkstyle
* add config to skip overhead memory calculation
* add test for the skipBytesInMemoryOverheadCheck config
* add docs
* fix checkstyle
* fix checkstyle
* fix spelling
* address comments
* fix travis
* address comments
* Multiphase merge for IndexMergerV9
* JSON fix
* Cleanup temp files
* Docs
* Address logging and add IT
* Fix spelling and test unloader datasource name
* integration test for coordinator and overlord leadership, added sys.servers is_leader column
* docs
* remove not needed
* fix comments
* fix compile heh
* oof
* revert unintended
* fix tests, split out docker-compose file selection from starting cluster, use docker-compose down to stop cluster
* fixes
* style
* dang
* heh
* scripts are hard
* fix spelling
* fix thing that must not matter since was already wrong ip, log when test fails
* needs more heap
* fix merge
* less aggro
* fix JSON format
* Change all columns in sys segments to be JSON
* Change all columns in sys segments to be JSON
* add tests
* fix failing tests
* fix failing tests
* Add shuffle metrics for parallel indexing
* javadoc and concurrency test
* concurrency
* fix javadoc
* Feature flag
* doc
* fix doc and add a test
* checkstyle
* add tests
* fix build and address comments
* Fix Avro OCF detection prefix and run formation detection on raw input
* Support Avro Fixed and Enum types correctly
* Check Avro version byte in format detection
* Add test for AvroOCFReader.sample
Ensures that the Sampler doesn't receive raw input that it can't
serialize into JSON.
* Document Avro type handling
* Add TS unit tests for guessInputFormat
* Adding more worker metrics to Druid Overlord
* Changing the nomenclature from worker to peon as that represents the metrics that we want to monitor better
* Few more instance of worker usage replaced with peon
* Modifying the peon idle count logic to only use eligible workers available capacity
* Changing the naming to task slot count instead of peon
* Adding some unit test coverage for the new test runner apis
* Addressing Review Comments
* Modifying the TaskSlotCountStatsProvider apis so that overlords which are not leader do not emit these metrics
* Fixing the spelling issue in the docs
* Setting the annotation Nullable on the TaskSlotCountStatsProvider methods
* Store hash partition function in dataSegment and allow segment pruning only when hash partition function is provided
* query context
* fix tests; add more test
* javadoc
* docs and more tests
* remove default and hadoop tests
* consistent name and fix javadoc
* spelling and field name
* default function for partitionsSpec
* other comments
* address comments
* fix tests and spelling
* test
* doc
* Working
* add test
* doc
* fix test
* split other integration test
* exclude other-index from other tests
* doc anchor fix
* adjust task slots and number of merge tasks
* spell check
* reduce maxNumConcurrentSubTasks to 1
* maxNumConcurrentSubtasks for range partitinoing
* reduce memory for historical
* change group name
* support redis cluster
* add 'password', 'database' properties
* test cases passed
* update doc
* some improvements
* fix CI
* add more test cases to improve branch coverage
* fix dependency check for test
* resolve review comments
* support unit suffix on byte-related properties
* add doc
* change default value of byte-related properites in example files
* fix coding style
* fix doc
* fix CI
* suppress spelling errors
* improve code according to comments
* rename Bytes to HumanReadableBytes
* add getBytesInInt to get value safely
* improve doc
* fix problem reported by CI
* fix problem reported by CI
* resolve code review comments
* improve error message
* improve code & doc according to comments
* fix CI problem
* improve doc
* suppress spelling check errors
Agustin Gonzalez
Gian Merlino
Frank Chen
Lucas Capistrant
Rohan Garg
Victoria Lim
zachjsh
somu-imply
Adarsh Sanjeev
Gian Merlino
Karan Kumar
Frank Chen
Charles Smith
Clint Wylie
Maytas Monsereenusorn
Kashif Faraz
sthetland
Jian Wang
Arun Ramani
lokesh-lingarajan
Jihoon Son
Paul Rogers
Parag Jain
Harini Rajendran
Joseph Glanville
Egor Riashin
Xavier Léauté
Yuanli Han
Lasse Krogh Mammen
Charles Smith
Yi Yuan
Abhishek Agarwal
Tianxin Zhao
spinatelli
Himanshu
Jonathan Wei
Nishant Bangarwa
Mainak Ghosh
Suneet Saldanha
Fernando