* Enable ability to toggle SegmentMetadata request logging on/off
* Move SegmentMetadata query log filter to FilteredRequestLogger
* Update documentation to reflect the segment metadata flag moving to the filtered request logger
* Modify patch to allow blacklist of query types to not log to request logger
* Address styling and naming requests following latest code review
* Fix indentation on multiple locations per Druid style rules
* Add a cluster-wide configuration to force timeChunk lock and add a doc for segment locking
* add more test
* javadoc for missingIntervalsInOverwriteMode
* Fix test
* Address comments
* avoid spotbugs
* Add IPv4 SQL functions
New SQL functions for filtering IPv4 addresses:
- IPV4_MATCH: Check if IP address belongs to a subnet
- IPV4_PARSE: Convert string IP address to integer
- IPV4_STRINGIFY: Convert integer IP address to string
These are the SQL analogs of the druid expressions with the same name.
Filtering is more efficient when operating on IP addresses as integers
instead of strings.
* Refactor operator conversions into named constants
* Add IPv4 druid expressions
New druid expressions for filtering IPv4 addresses:
- ipv4address_match: Check if IP address belongs to a subnet
- ipv4address_parse: Convert string IP address to long
- ipv4address_stringify: Convert long IP address to string
These expressions operate on IP addresses represented as either strings
or longs, so that they can be applied to dimensions with mixed
representation of IP addresses. The filtering is more efficient when
operating on IP addresses as longs. In other words, the intended use
case is:
1) Use ipv4address_parse to convert to long at ingestion time
2) Use ipv4address_match to filter (on longs) at query time
3) Use ipv4adress_stringify to convert to (readable) string at query
time
* Fix licenses and null handling
* Simplify IPv4 expressions
* Fix tests
* Fix check for valid ipv4 address string
* Use partitionsSpec for all task types
* fix doc
* fix typos and revert to use isPushRequired
* address comments
* move partitionsSpec to core
* remove hadoopPartitionsSpec
* firehose doc adjustments
* fix typo
* additional information on parser types in ingestion docs
* clarify ingest segment firehose docs, add sql firehose examples to sql extension pages
* fixit
* make sql firehose more forgiving my always constructing a MapInputRowParser from the parseSpec of whatever actual InputRowParser impl is provided, remove doc references to map based parsers
* transforms
* fix tests
* remove unecessary lock in ForegroundCachePopulator leading to a lot of contention
* mutableboolean, javadocs,document some cache configs that were missing
* more doc stuff
* adjustments
* remove background documentation
* 1. Added TimestampExtractExprMacro.Unit for MILLISECOND 2. expr eval for MILLISECOND 3. Added a test case to test extracting millisecond from expression. #7935
* 1. Adding DATASOURCE4 in tests. 2. Adding test TimeExtractWithMilliseconds
* Fixing testInformationSchemaTables test
* Fixing failing tests in DruidAvaticaHandlerTest
* Adding cannotVectorize() call before the test
* Extract time function - Adding support for MICROSECOND, ISODOW, ISOYEAR and CENTURY time units, documentation changes.
* Adding MILLISECOND in test case
* Adding support DECADE and MILLENNIUM, updating test case and documentation
* Fixing expression eval for DECADE and MILLENIUM
The Markdown dialect used when publishing the documentation to the web
site is much more sensitive than Github-flavoured Markdown. In
particular, it requires an empty line before code blocks (unless the
code block starts right after a heading), otherwise the code block
gets formatted in-line with the previous paragraph. Likewise for
bullet-point lists.
* Benchmarks: New SqlBenchmark, add caching & vectorization to some others.
- Introduce a new SqlBenchmark geared towards benchmarking a wide
variety of SQL queries. Rename the old SqlBenchmark to
SqlVsNativeBenchmark.
- Add (optional) caching to SegmentGenerator to enable easier
benchmarking of larger segments.
- Add vectorization to FilteredAggregatorBenchmark and GroupByBenchmark.
* Query vectorization.
This patch includes vectorized timeseries and groupBy engines, as well
as some analogs of your favorite Druid classes:
- VectorCursor is like Cursor. (It comes from StorageAdapter.makeVectorCursor.)
- VectorColumnSelectorFactory is like ColumnSelectorFactory, and it has
methods to create analogs of the column selectors you know and love.
- VectorOffset and ReadableVectorOffset are like Offset and ReadableOffset.
- VectorAggregator is like BufferAggregator.
- VectorValueMatcher is like ValueMatcher.
There are some noticeable differences between vectorized and regular
execution:
- Unlike regular cursors, vector cursors do not understand time
granularity. They expect query engines to handle this on their own,
which a new VectorCursorGranularizer class helps with. This is to
avoid too much batch-splitting and to respect the fact that vector
selectors are somewhat more heavyweight than regular selectors.
- Unlike FilteredOffset, FilteredVectorOffset does not leverage indexes
for filters that might partially support them (like an OR of one
filter that supports indexing and another that doesn't). I'm not sure
that this behavior is desirable anyway (it is potentially too eager)
but, at any rate, it'd be better to harmonize it between the two
classes. Potentially they should both do some different thing that
is smarter than what either of them is doing right now.
- When vector cursors are created by QueryableIndexCursorSequenceBuilder,
they use a morphing binary-then-linear search to find their start and
end rows, rather than linear search.
Limitations in this patch are:
- Only timeseries and groupBy have vectorized engines.
- GroupBy doesn't handle multi-value dimensions yet.
- Vector cursors cannot handle virtual columns or descending order.
- Only some filters have vectorized matchers: "selector", "bound", "in",
"like", "regex", "search", "and", "or", and "not".
- Only some aggregators have vectorized implementations: "count",
"doubleSum", "floatSum", "longSum", "hyperUnique", and "filtered".
- Dimension specs other than "default" don't work yet (no extraction
functions or filtered dimension specs).
Currently, the testing strategy includes adding vectorization-enabled
tests to TimeseriesQueryRunnerTest, GroupByQueryRunnerTest,
GroupByTimeseriesQueryRunnerTest, CalciteQueryTest, and all of the
filtering tests that extend BaseFilterTest. In all of those classes,
there are some test cases that don't support vectorization. They are
marked by special function calls like "cannotVectorize" or "skipVectorize"
that tell the test harness to either expect an exception or to skip the
test case.
Testing should be expanded in the future -- a project in and of itself.
Related to #3011.
* WIP
* Adjustments for unused things.
* Adjust javadocs.
* DimensionDictionarySelector adjustments.
* Add "clone" to BatchIteratorAdapter.
* ValueMatcher javadocs.
* Fix benchmark.
* Fixups post-merge.
* Expect exception on testGroupByWithStringVirtualColumn for IncrementalIndex.
* BloomDimFilterSqlTest: Tag two non-vectorizable tests.
* Minor adjustments.
* Update surefire, bump up Xmx in Travis.
* Some more adjustments.
* Javadoc adjustments
* AggregatorAdapters adjustments.
* Additional comments.
* Remove switching search.
* Only missiles.
* Add inline firehose
To allow users to quickly parsing and schema, add a firehose that reads
data that is inlined in its spec.
* Address review comments
* Remove suppression of sonar warnings
* disable all compression in intermediate segment persists while ingestion
* more changes and build fix
* by default retain existing indexingSpec for intermediate persisted segments
* document indexSpecForIntermediatePersists index tuning config
* fix build issues
* update serde tests
* Fix license check in travis and make it optional
* debug
* fix build
* too loud maven
* move MAVEN_OPTS to top and add comments
* adjust script
* remove mvn option from python script
In Single-Server Quickstart tutorial the overlord and coordinator
is started as one process on port 8081. But in delete data tutorial the kill
task is sent to 8090 port, which fails.
* Add round support for DS-HLL
Since the Cardinality aggregator has a "round" option to round off estimated
values generated from the HyperLogLog algorithm, add the same "round" option to
the DataSketches HLL Sketch module aggregators to be consistent.
* Fix checkstyle errors
* Change HllSketchSqlAggregator to do rounding
* Fix test for standard-compliant null handling mode
* more sql support for expression array functions
* prepend/slice
* doc fixes
* fix imports
* fix tests
* add null numeric expr for proper conversions between ExprEval and Expr and back to ExprEval
* re-arrange
* imports :(
* add append/prepend test
* array support for expression language for multi-value string columns
* fix tests?
* fixes
* more tests
* fixes
* cleanup
* more better, more test
* ignore inspection
* license
* license fix
* inspection
* remove dumb import
* more better
* some comments
* add expr rewrite for arrayfn args for more magic, tests
* test stuff
* more tests
* fix test
* fix test
* castfunc can deal with arrays
* needs more empty array
* more tests, make cast to long array more forgiving
* refactor
* simplify ExprMacro Expr implementations with base classes in core
* oops
* more test
* use Shuttle for Parser.flatten, javadoc, cleanup
* fixes and more tests
* unused import
* fixes
* javadocs, cleanup, refactors
* fix imports
* more javadoc
* more javadoc
* more
* more javadocs, nonnullbydefault, minor refactor
* markdown fix
* adjustments
* more doc
* move initial filter out
* docs
* map empty arg lambda, apply function argument validation
* check function args at parse time instead of eval time
* more immutable
* more more immutable
* clarify grammar
* fix docs
* empty array is string test, we need a way to make arrays better maybe in the future, or define empty arrays as other types..
Jonathan Wei
Lucas Capistrant
Samarth Jain
Jihoon Son
Chi Cao Minh
Clint Wylie
Surekha
Nathan
Magnus Henoch
Sashidhar Thallam
Roman Leventov
Gian Merlino
Atul Mohan
Himanshu
Eyal Yurman
Dinesh Sawant
Chi Cao Minh
Xue Yu
Alexander Saydakov
Vadim Ogievetsky
Benedict Jin
Clint Wylie