Also change defaults:
- bufferGrouperMaxLoadFactor from 0.75 to 0.7.
- maxMergingDictionarySize to 100MB from 25MB, should be more appropriate
for most heaps.
Follow-up to #1773, which meant to add more useful query errors but
did not actually do so. Since that patch, any error other than
interrupt/cancel/timeout was reported as `{"error":"Unknown exception"}`.
With this patch, the error fields are:
- error, one of the specific strings "Query interrupted", "Query timeout",
"Query cancelled", or "Unknown exception" (same behavior as before).
- errorMessage, the message of the topmost non-QueryInterruptedException
in the causality chain.
- errorClass, the class of the topmost non-QueryInterruptedException
in the causality chain.
- host, the host that failed the query.
* Add time interval dim filter and retention analysis example
* Use closed-open matching for intervals, update cache key generation
* Fix time filtering tests for interval boundary change
* ability to not rollup at index time, make pre aggregation an option
* rename getRowIndexForRollup to getPriorIndex
* fix doc misspelling
* test query using no-rollup indexes
* fix benchmark fail due to jmh bug
* Add numeric StringComparator
* Only use direct long comparison for numeric ordering in BoundFilter, add time filtering benchmark query
* Address PR comments, add multithreaded BoundDimFilter test
* Add comment on strlen tie handling
* Add timeseries interval filter benchmark
* Adjust docs
* Use jackson for StringComparator, address PR comments
* Add new TopNMetricSpec and SearchSortSpec with tests (WIP)
* More TopNMetricSpec and SearchSortSpec tests
* Fix NewSearchSortSpec serde
* Update docs for new DimensionTopNMetricSpec
* Delete NumericDimensionTopNMetricSpec
* Delete old SearchSortSpec
* Rename NewSearchSortSpec to SearchSortSpec
* Add TopN numeric comparator benchmark, address PR comments
* Refactor OrderByColumnSpec
* Add null checks to NumericComparator and String->BigDecimal conversion function
* Add more OrderByColumnSpec serde tests
This fixes a potential issue where groupBy resources could be allocated to
create a Sequence, but then the Sequence is never used, and thus the resources
are never freed.
Also simplifies how groupBy handles config overrides (this made the new
unit test easier to write).
* InputRowParser to decode OrcStruct from OrcNewInputFormat
* add unit test for orc hadoop indexing
* update docs and fix test code bug
* doc updated
* resove maven dependency conflict
* remove unused imports
* fix returning array type from Object[] to correct primitive array type
* fix to support getDimension() of MapBasedRow : changing return type of orc list from array to list
* rebase and updated based on comments
* updated based on comments
* on reflecting review comments
* fix bug in typeStringFromParseSpec() and add unit test
* add license header
* Support filtering on __time column
* Rename DruidPredicate
* Add docs for ValueMatcherFactory, add comment on getColumnCapabilities
* Combine ValueMatcherFactory predicate methods to accept DruidCompositePredicate
* Address PR comments (support filter on all long columns)
* Use predicate factory instead of composite predicate
* Address PR comments
* Lazily initialize long handling in selector/in filter
* Move long value parsing from InFilter to InDimFilter, make long value parsing thread-safe
* Add multithreaded selector/in filter test
* Fix non-final lock object in SelectorDimFilter
- Attempt to make things clearer in general
- Point out that HDFS deep storage and MR jobs don't use the same loading mechanism
- Recommend using mapreduce.job.classloader = true when possible
* Initial commit of caffeine cache
* Address code comments
* Move and fixup README.md a bit
* Improve caffeine readme information
* Cleanup caffeine pom
* Address review comments
* Bump caffeine to 2.3.1
* Bump druid version to 0.9.2-SNAPSHOT
* Make test not fail randomly.
See https://github.com/ben-manes/caffeine/pull/93#issuecomment-227617998 for an explanation
* Fix distribution and documentation
* Add caffeine to extensions.md
* Fix links in extensions.md
* Lexicographic
This is actually reasonable for a groupBy or lexicographic topNs that is
being used to do a "COUNT DISTINCT" kind of query. No aggregators are
needed for that query, and including a dummy aggregator wastes 8 bytes
per row.
It's kind of silly for timeseries, but why not.
Gian Merlino
Himanshu
Slim
David Lim
Stéphane Derosiaux
Dave Li
Jonathan Wei
Ashish
Chanh Le
Fangjin Yang
rajk-tetration
Nishant
Navis Ryu
kaijianding
Charles Allen
Keuntae Park