### Description
This change allows for consideration of the input format and compression when computing how to split the input files among available tasks, in MSQ ingestion, when considering the value of the `maxInputBytesPerWorker` query context parameter. This query parameter allows users to control the maximum number of bytes, with granularity of input file / object, that ingestion tasks will be assigned to ingest. With this change, this context parameter now denotes the estimated weighted size in bytes of the input to split on, with consideration for input format and compression format, rather than the actual file size, reported by the file system. We assume uncompressed newline delimited json as a baseline, with scaling factor of `1`. This means that when computing the byte weight that a file has towards the input splitting, we take the file size as is, if uncompressed json, 1:1. It was found during testing that gzip compressed json, and parquet, has scale factors of `4` and `8` respectively, meaning that each byte of data is weighted 4x and 8x respectively, when computing input splits. This weighted byte scaling is only considered for MSQ ingestion that uses either LocalInputSource or CloudObjectInputSource at the moment. The default value of the `maxInputBytesPerWorker` query context parameter has been updated from 10 GiB, to 512 MiB
In StreamChunkParser#parseWithInputFormat, we call byteEntityReader.read() without handling a potential ParseException, which is thrown during this function call by the delegate AvroStreamReader#intermediateRowIterator.
A ParseException can be thrown if an Avro stream has corrupt data or data that doesn't conform to the schema specified or for other decoding reasons. This exception if uncaught, can cause ingestion to fail.
Hadoop 2 often causes red security scans on Druid distribution because of the dependencies it brings. We want to move away from Hadoop 2 and provide Hadoop 3 distribution available. Switch druid to building with Hadoop 3 by default. Druid will still be compatible with Hadoop 2 and users can build hadoop-2 compatible distribution using hadoop2 profile.
array columns!
changes:
* add support for storing nested arrays of string, long, and double values as specialized nested columns instead of breaking them into separate element columns
* nested column type mimic behavior means that columns ingested with only root arrays of primitive values will be ARRAY typed columns
* neat test refactor stuff
* add v4 segment test
* add array element indexes
* add tests for unnest and array columns
* fix unnest column value selector cursor handling of null and empty arrays
* merge druid-core, extendedset, and druid-hll into druid-processing to simplify everything
* fix poms and license stuff
* mockito is evil
* allow reset of JvmUtils RuntimeInfo if tests used static injection to override
* discover nested columns when using nested column indexer for schemaless
* move useNestedColumnIndexerForSchemaDiscovery from AppendableIndexSpec to DimensionsSpec
* Attach IO error to parse error when we can't contact Avro schema registry.
The change in #12080 lost the original exception context. This patch
adds it back.
* Add hamcrest-core.
* Fix format string.
* introduce a "tree" type to the flattenSpec
* feedback - rename exprs to nodes, use CollectionsUtils.isNullOrEmpty for guard
* feedback - expand docs to more clearly capture limitations of "tree" flattenSpec
* feedback - fix for typo on docs
* introduce a comment to explain defensive copy, tweak null handling
* fix: part of rebase
* mark ObjectFlatteners.FlattenerMaker as an ExtensionPoint and provide default for new tree type
* fix: objectflattener restore previous behavior to call getRootField for root type
* docs: ingestion/data-formats add note that ORC only supports path expressions
* chore: linter remove unused import
* fix: use correct newer form for empty DimensionsSpec in FlattenJSONBenchmark
* Cleaner JSON for various input sources and formats.
Add JsonInclude to various properties, to avoid population of default
values in serialized JSON.
Also fixes a bug in OrcInputFormat: it was not writing binaryAsString,
so the property would be lost on serde.
* Additonal test cases.
The Avro parsing code leaks some "object" representations.
We need to convert them into Maps/Lists so that other code
can understand and expect good things. Previously, these
objects were handled with .toString(), but that's not a
good contract in terms of how to work with objects.
This PR aims to make the ParseExceptions in Druid more informative, by adding additional information (metadata) to the ParseException, which can contain additional information about the exception. For example - the path of the file generating the issue, the line number (where it can be easily fetched - like CsvReader)
Following changes are addressed in this PR:
A new class CloseableIteratorWithMetadata has been created which is like CloseableIterator but also has a metadata method that returns a context Map<String, Object> about the current element returned by next().
IntermediateRowParsingReader#read() now attaches the InputEntity and the "record number" which created the exception (while parsing them), and IntermediateRowParsingReader#sample attaches the InputEntity (but not the "record number").
TextReader (and its subclasses), which is a specific implementation of the IntermediateRowParsingReader also include the line number which caused the generation of the error.
This will also help in triaging the issues when InputSourceReader generates ParseException because it can point to the specific InputEntity which caused the exception (while trying to read it).
* 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
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 back missing unit test coverage in AvroFlattenerMakerTest
Adds back test coverage for Avro flattener that was mistakenly removed in https://github.com/apache/druid/pull/10505. Recfactored the tests a bit too.
* resolve checkstyle warnings
* 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
* 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.
* 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>
* support multi-line text
* add test cases
* split json text into lines case by case
* improve exception handle
* fix CI
* use IntermediateRowParsingReader as base of JsonReader
* update doc
* ignore the non-immutable field in test case
* add more test cases
* mark `lineSplittable` as final
* fix testcases
* fix doc
* add a test case for SqlReader
* return all raw columns when exception occurs
* fix CI
* fix test cases
* resolve review comments
* handle ParseException returned by index.add
* apply Iterables.getOnlyElement
* fix CI
* fix test cases
* improve code in more graceful way
* fix test cases
* fix test cases
* add a test case to check multiple json string in one text block
* fix inspection check
* 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
* Filter http requests by http method
Add a config that allows a user which http methods to allow against their
Druid server.
Druid will only accept http requests with the method: GET, PUT, POST, DELETE
and OPTIONS.
If a Druid admin wants to allow other methods, they can do so by using the
ServerConfig#allowedHttpMethods config.
If a Druid user would like to disallow OPTIONS, this can be done by changing
the AuthConfig#allowUnauthenticatedHttpOptions config
* Exclude OPTIONS from always supported HTTP methods
Add HEAD as an allowed method for web console e2e tests
* fix docs
* fix security IT
* Actually fix the web console e2e tests
* Ignore icode coverage for nitialization classes
* code review
* Add AvroOCFInputFormat
* Support supplying a reader schema in AvroOCFInputFormat
* Add docs for Avro OCF input format
* Address review comments
* Address second round of review
Tejaswini Bandlamudi
zachjsh
Abhishek Radhakrishnan
robo220
Clint Wylie
somu-imply
Kashif Faraz
Gian Merlino
Jason Koch
Abhishek Agarwal
imply-cheddar
Laksh Singla
Jihoon Son
Karan Kumar
Jonathan Wei
Frank Chen
Yi Yuan
Xavier Léauté
Joseph Glanville
spinatelli
Lasse Krogh Mammen
belugabehr
Suneet Saldanha
Adam Peck