changes:
* modified druid schema column type compution to special case COMPLEX<json> handling to choose COMPLEX<json> if any column in any segment is COMPLEX<json>
* NestedFieldVirtualColumn can now work correctly on any type of column, returning either a column selector if a root path, or nil selector if not
* fixed a random bug with NilVectorSelector when using a vector size larger than the default and druid.generic.useDefaultValueForNull=false would have the nulls vector set to all false instead of true
* fixed an overly aggressive check in ExprEval.ofType when handling complex types which would try to treat any string as base64 without gracefully falling back if it was not in fact base64 encoded, along with special handling for complex<json>
* added ExpressionVectorSelectors.castValueSelectorToObject and ExpressionVectorSelectors.castObjectSelectorToNumeric as convience methods to cast vector selectors using cast expressions without the trouble of constructing an expression. the polymorphic nature of the non-vectorized engine (and significantly larger overhead of non-vectorized expression processing) made adding similar methods for non-vectorized selectors less attractive and so have not been added at this time
* fix inconsistency between nested column indexer and serializer in handling values (coerce non primitive and non arrays of primitives using asString)
* ExprEval best effort mode now handles byte[] as string
* added test for ExprEval.bestEffortOf, and add missing conversion cases that tests uncovered
* more tests more better
* Fallback virtual column
This virtual columns enables falling back to another column if
the original column doesn't exist. This is useful when doing
column migrations and you have some old data with column X,
new data with column Y and you want to use Y if it exists, X
otherwise so that you can run a consistent query against all of
the data.
With fault tolerance enabled in MSQ, not all the work orders might be populated if the worker is restarted. In case it gets the request for cleaning up the stage which is not present in the worker's map, it can throw an NPE. Added a check to ensure that the stage is present in the map before cleaning it up, or else logging it as a warning.
Merging regardless of nit since topic is in better shape.
* refresh the update data tutorial
* Apply suggestions from code review
Co-authored-by: Jill Osborne <jill.osborne@imply.io>
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Co-authored-by: Jill Osborne <jill.osborne@imply.io>
* Fix lookup docs
* Fix spelling
* Apply suggestions from code review
Co-authored-by: Charles Smith <techdocsmith@gmail.com>
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Co-authored-by: Charles Smith <techdocsmith@gmail.com>
* Adjust Operators to be Pausable
This enables "merge" style operations that
combine multiple streams.
This change includes a naive implementation
of one such merge operator just to provide
concrete evidence that the refactoring is
effective.
Add a new API to return the history of changes to automatic compaction config history to make it easy for users to see what changes have been made to their auto-compaction config.
The API is scoped per dataSource to allow users to triage issues with an individual dataSource. The API responds with a list of configs when there is a change to either the settings that impact all auto-compaction configs on a cluster or the dataSource in question.
* adds the SQL component of the native unnest functionality in Druid to unnest SQL queries on a table dimension, virtual column or a constant array and convert them into native Druid queries
* unnest in SQL is implemented as a combination of Correlate (the comma join part) and Uncollect (the unnest part)
* SQL test framework extensions
* Capture planner artifacts: logical plan, etc.
* Planner test builder validates the logical plan
* Validation for the SQL resut schema (we already have
validation for the Druid row signature)
* Better Guice integration: properties, reuse Guice modules
* Avoid need for hand-coded expr, macro tables
* Retire some of the test-specific query component creation
* Fix query log hook race condition
Co-authored-by: Paul Rogers <progers@apache.org>
* discover nested columns when using nested column indexer for schemaless
* move useNestedColumnIndexerForSchemaDiscovery from AppendableIndexSpec to DimensionsSpec
Much improved table functions
* Revises properties, definitions in the catalog
* Adds a "table function" abstraction to model such functions
* Specific functions for HTTP, inline, local and S3.
* Extended SQL types in the catalog
* Restructure external table definitions to use table functions
* EXTEND syntax for Druid's extern table function
* Support for array-valued table function parameters
* Support for array-valued SQL query parameters
* Much new documentation
Support both indexer and MM in ITs
Support for the DRUID_INTEGRATION_TEST_INDEXER variable
Conditional client cluster configuration
Cleanup of OVERRIDE_ENV file handling
Enforce setting of test-specific env vars
Cleanup of unused bits
* Semantic Implementations for ArrayListRAC
This adds implementations of semantic interfaces
to optimize (eliminate object creation) the
window processing on top of an ArrayListSegment.
Tests are also added to cover the interplay
between the semantic interfaces that are expected
for this use case
* migrate UTs form Travis to GHA
* update permissions
* rename file
* set fetch depth to 1
* debugs remote branches
* test with github.ref variable
* fetch github.base_ref for diff
* nit
* test git diff
* run tests
* test code coverage failure scenario
* nit
* nit
* revert code changes
* revert code changes
* Setup diff-test-coverage before tests
* build distribution module at end in packaging check
* nit
* remove redundant steps in static-checks workflow
* drop jdk8 unit tests from Travis
* Kinesis: More robust default fetch settings.
1) Default recordsPerFetch and recordBufferSize based on available memory
rather than using hardcoded numbers. For this, we need an estimate
of record size. Use 10 KB for regular records and 1 MB for aggregated
records. With 1 GB heaps, 2 processors per task, and nonaggregated
records, recordBufferSize comes out to the same as the old
default (10000), and recordsPerFetch comes out slightly lower (1250
instead of 4000).
2) Default maxRecordsPerPoll based on whether records are aggregated
or not (100 if not aggregated, 1 if aggregated). Prior default was 100.
3) Default fetchThreads based on processors divided by task count on
Indexers, rather than overall processor count.
4) Additionally clean up the serialized JSON a bit by adding various
JsonInclude annotations.
* Updates for tests.
* Additional important verify.
* single typed "root" only nested columns now mimic "regular" columns of those types
* incremental index can now use nested column indexer instead of string indexer for discovered columns