* 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
* Update rollup.md
Added SE tip around roll-up.
* Update docs/ingestion/rollup.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* 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
* Corrected admonition issue
* Update data-formats.md
Removed all admonition bits, and took out sf linebreaks.
* Update data-formats.md
Changed the shocker line into something a little more practical.
### 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.
* Add handoff wait time to ingestion stats report. Refactor some code for batch handoff
* fix checkstyle
* Add assertion to AbstractITBatchIndexTask to make sure report reflects wait for segments happened
* add docs to the task reports section of doc
* Update index.md
Moved H4s underneath the H3 for the task log location and added hyperlinks.
* Update tasks.md
Added process information around log file generation, and subsumed text from the configuration guide into this explanatory text instead.
* Update tasks.md
.html > .md
* Update docs/ingestion/tasks.md
Co-authored-by: Frank Chen <frankchen@apache.org>
Co-authored-by: Frank Chen <frankchen@apache.org>
LGTM
* Update native-batch.md
Knowledge from https://the-asf.slack.com/archives/CJ8D1JTB8/p1595434977062400
* Update native-batch.md
* Fixed broken link + some grammar
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* Update native-batch.md
Some grammatical wizardry.
* Update native-batch.md
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Update docs/ingestion/native-batch.md
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Apply suggestions from code review
remove orphaned links
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Allow kill task to mark segments as unused
* Add IndexerSQLMetadataStorageCoordinator test
* Update docs/ingestion/data-management.md
Co-authored-by: Jihoon Son <jihoonson@apache.org>
* Add warning to kill task doc
Co-authored-by: Jihoon Son <jihoonson@apache.org>
Fixed a syntax error in "prefix" lines in docs/ingestion/native-batch.md
S3 requires a trailing slash for directory like structures, so this updates the examples to include the trailing slashes.
* 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
* Allow only HTTP and HTTPS protocols for the HTTP inputSource
* rename
* Update core/src/main/java/org/apache/druid/data/input/impl/HttpInputSource.java
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
* fix http firehose and update doc
* HDFS inputSource
* add configs for allowed protocols
* fix checkstyle and doc
* more checkstyle
* remove stale doc
* remove more doc
* Apply doc suggestions from code review
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.com>
* update hdfs address in docs
* fix test
Co-authored-by: Abhishek Agarwal <1477457+abhishekagarwal87@users.noreply.github.com>
Co-authored-by: Charles Smith <38529548+techdocsmith@users.noreply.github.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>
* clarify security requirements around HTTPInputSource
* explicitly mention write/datasource in best practices. clarify that the ingestion task is the risk
* Update docs/operations/security-overview.md
Co-authored-by: Suneet Saldanha <suneet@apache.org>
Co-authored-by: Suneet Saldanha <suneet@apache.org>
* 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
* 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
* 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
* Add segment pruning for hash based partitioning
* Update doc
* Add additional test
* Address comments
* Fix unit test failure
Co-authored-by: Jian Wang <jwang@pinterest.com>
* Fill in the core partition set size properly for batch ingestion with
dynamic partitioning
* incomplete javadoc
* Address comments
* fix tests
* fix json serde, add tests
* checkstyle
* Set core partition set size for hash-partitioned segments properly in
batch ingestion
* test for both parallel and single-threaded task
* unused variables
* fix test
* unused imports
* add hash/range buckets
* some test adjustment and missing json serde
* centralized partition id allocation in parallel and simple tasks
* remove string partition chunk
* revive string partition chunk
* fill numCorePartitions for hadoop
* clean up hash stuffs
* resolved todos
* javadocs
* Fix tests
* add more tests
* doc
* unused imports
* Allow append to existing datasources when dynamic partitioing is used
* fix test
* checkstyle
* checkstyle
* fix test
* fix test
* fix other tests..
* checkstyle
* hansle unknown core partitions size in overlord segment allocation
* fail to append when numCorePartitions is unknown
* log
* fix comment; rename to be more intuitive
* double append test
* cleanup complete(); add tests
* fix build
* add tests
* address comments
* checkstyle
* fix docs error: google to azure and hdfs to http
* fix docs error: indexSpecForIntermediatePersists of tuningConfig in hadoop-based batch part
* fix docs error: logParseExceptions of tuningConfig in hadoop-based batch part
* fix docs error: maxParseExceptions of tuningConfig in hadoop-based batch part
* Fill in the core partition set size properly for batch ingestion with
dynamic partitioning
* incomplete javadoc
* Address comments
* fix tests
* fix json serde, add tests
* checkstyle
* Set core partition set size for hash-partitioned segments properly in
batch ingestion
* test for both parallel and single-threaded task
* unused variables
* fix test
* unused imports
* add hash/range buckets
* some test adjustment and missing json serde
* centralized partition id allocation in parallel and simple tasks
* remove string partition chunk
* revive string partition chunk
* fill numCorePartitions for hadoop
* clean up hash stuffs
* resolved todos
* javadocs
* Fix tests
* add more tests
* doc
* unused imports
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* fix checksyle
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* API to verify a datasource has the latest ingested data
* fix spelling
* address comments
* fix checkstyle
* update docs
* fix tests
* fix doc
* address comments
* fix typo
* fix spelling
* address comments
* address comments
* fix typo in docs
* Add AvroOCFInputFormat
* Support supplying a reader schema in AvroOCFInputFormat
* Add docs for Avro OCF input format
* Address review comments
* Address second round of review
* Update data-formats.md
Per Suneet, "Since you're editing this file can you also fix the json on line 177 please - it's missing a comma after the }"
* Light text cleanup
* Removing discussion of sample data, since it's repeated in the data loading tutorial, and not immediately relevant here.
* Update index.md
* original quickstart full first pass
* original quickstart full first pass
* first pass all the way through
* straggler
* image touchups and finished old tutorial
* a bit of finishing up
* Review comments
* fixing links
* spell checking gymnastics
* Skip empty files for local, hdfs, and cloud input sources
* split hint spec doc
* doc for skipping empty files
* fix typo; adjust tests
* unnecessary fluent iterable
* address comments
* fix test
* use the right lists
* fix test
* fix test
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* Add support for optional cloud (aws, gcs, etc.) credentials for s3 for ingestion
* fix build failure
* fix failing build
* fix failing build
* Code cleanup
* fix failing test
* Removed CloudConfigProperties and make specific class for each cloudInputSource
* Removed CloudConfigProperties and make specific class for each cloudInputSource
* pass s3ConfigProperties for split
* lazy init s3client
* update docs
* fix docs check
* address comments
* add ServerSideEncryptingAmazonS3.Builder
* fix failing checkstyle
* fix typo
* wrap the ServerSideEncryptingAmazonS3.Builder in a provider
* added java docs for S3InputSource constructor
* added java docs for S3InputSource constructor
* remove wrap the ServerSideEncryptingAmazonS3.Builder in a provider
* Move Azure extension into Core
Moving the azure extension into Core.
* * Fix build failure
* * Add The MIT License (MIT) to list of compatible licenses
* * Address review comments
* * change reference to contrib azure to core azure
* * Fix spelling mistakes.
* Create splits of multiple files for parallel indexing
* fix wrong import and npe in test
* use the single file split in tests
* rename
* import order
* Remove specific local input source
* Update docs/ingestion/native-batch.md
Co-Authored-By: sthetland <steve.hetland@imply.io>
* Update docs/ingestion/native-batch.md
Co-Authored-By: sthetland <steve.hetland@imply.io>
* doc and error msg
* fix build
* fix a test and address comments
Co-authored-by: sthetland <steve.hetland@imply.io>
* Add Azure config options for segment prefix and max listing length
Added configuration options to allow the user to specify the prefix
within the segment container to store the segment files. Also
added a configuration option to allow the user to specify the
maximum number of input files to stream for each iteration.
* * Fix test failures
* * Address review comments
* * add dependency explicitly to pom
* * update docs
* * Address review comments
* * Address review comments
* Update data-formats.md
Field error and light rewording of new Avro material (and working through the doc authoring process).
* Update data-formats.md
Make default statements consistent. Future change: s/=/is.
* Doc update for new input source and input format.
- The input source and input format are promoted in all docs under docs/ingestion
- All input sources including core extension ones are located in docs/ingestion/native-batch.md
- All input formats and parsers including core extension ones are localted in docs/ingestion/data-formats.md
- New behavior of the parallel task with different partitionsSpecs are documented in docs/ingestion/native-batch.md
* parquet
* add warning for range partitioning with sequential mode
* hdfs + s3, gs
* add fs impl for gs
* address comments
* address comments
* gcs
* Fail superbatch range partition multi dim values
Change the behavior of parallel indexing range partitioning to fail
ingestion if any row had multiple values for the partition dimension.
After this change, the behavior matches that of hadoop indexing.
(Previously, rows with multiple dimension values would be skipped.)
* Improve err msg, rename method, rename test class
* Parallel indexing single dim partitions
Implements single dimension range partitioning for native parallel batch
indexing as described in #8769. This initial version requires the
druid-datasketches extension to be loaded.
The algorithm has 5 phases that are orchestrated by the supervisor in
`ParallelIndexSupervisorTask#runRangePartitionMultiPhaseParallel()`.
These phases and the main classes involved are described below:
1) In parallel, determine the distribution of dimension values for each
input source split.
`PartialDimensionDistributionTask` uses `StringSketch` to generate
the approximate distribution of dimension values for each input
source split. If the rows are ungrouped,
`PartialDimensionDistributionTask.UngroupedRowDimensionValueFilter`
uses a Bloom filter to skip rows that would be grouped. The final
distribution is sent back to the supervisor via
`DimensionDistributionReport`.
2) The range partitions are determined.
In `ParallelIndexSupervisorTask#determineAllRangePartitions()`, the
supervisor uses `StringSketchMerger` to merge the individual
`StringSketch`es created in the preceding phase. The merged sketch is
then used to create the range partitions.
3) In parallel, generate partial range-partitioned segments.
`PartialRangeSegmentGenerateTask` uses the range partitions
determined in the preceding phase and
`RangePartitionCachingLocalSegmentAllocator` to generate
`SingleDimensionShardSpec`s. The partition information is sent back
to the supervisor via `GeneratedGenericPartitionsReport`.
4) The partial range segments are grouped.
In `ParallelIndexSupervisorTask#groupGenericPartitionLocationsPerPartition()`,
the supervisor creates the `PartialGenericSegmentMergeIOConfig`s
necessary for the next phase.
5) In parallel, merge partial range-partitioned segments.
`PartialGenericSegmentMergeTask` uses `GenericPartitionLocation` to
retrieve the partial range-partitioned segments generated earlier and
then merges and publishes them.
* Fix dependencies & forbidden apis
* Fixes for integration test
* Address review comments
* Fix docs, strict compile, sketch check, rollup check
* Fix first shard spec, partition serde, single subtask
* Fix first partition check in test
* Misc rewording/refactoring to address code review
* Fix doc link
* Split batch index integration test
* Do not run parallel-batch-index twice
* Adjust last partition
* Split ITParallelIndexTest to reduce runtime
* Rename test class
* Allow null values in range partitions
* Indicate which phase failed
* Improve asserts in tests
* Fix the potential race SplittableInputSource.getNumSplits() and SplittableInputSource.createSplits() in TaskMonitor
* Fix docs and javadoc
* Add unit tests for large or small estimated num splits
* add override
Since it hasn't received updates or community interest in a while, it makes sense
to de-emphasize it in the distribution and most documentation (outside of simple
mentions of its existence).
Jonathan Wei
Frank Chen
shallada
Peter Marshall
Charles Smith
Maytas Monsereenusorn
jacobtolar
Jihoon Son
Katya Macedo
lokesh-lingarajan
Lucas Capistrant
Daegi Kim
Arvin.Z
Yi Yuan
jerryleooo
sthetland
Egor Riashin
Charles Smith
Lasse Krogh Mammen
imply-jbalik
Gian Merlino
spinatelli
Atul Mohan
Pierre Carrier
Joseph Glanville
LightGHLi
Fernando
Jian Wang
mans2singh
Fullstop000
Jianhuan Liu
Maytas Monsereenusorn
Clint Wylie
Maytas Monsereenusorn
zachjsh
Chi Cao Minh