* groupBy query: optional limit push down to segment scan
* make segment level limit push down configurable
* fix teamcity errors
* fix segment limit pushdown flag handling on query level config override
* use equals for comparator check
* fix sql and null handling
* fix unused imports
* handle null offset in NullableValueGroupByColumnSelectorStrategy for buffer comparator similar to RowBasedGrouperHelper.NullableRowBasedKeySerdeHelper
* add timeout support for JsonParserIterator init future
* add queryId
* should be less than 1
* fix
* fix npe
* fix lgtm
* adjust exception, nullable
* fix test
* refactor
* revert queryId change
* add log.warn to tie exception to json parser iterator
* update DimensionDictionarySelector.getValueCardinality() javadoc
* unknown cardinality in StringDictionaryEncodedColumn dim selector
* revert StringDictionaryEncodedColumn change as that fails GroupBy-v1 execution for many working queries
* fix/add more comments
* string column handling for long min/max/sum aggregators
* add apache license to new files
* use 'L' as suffix for long literal instead of 'l'
* return null in ParallelCombiner.SettableColumnSelectorFactory.getColumnCapabilities(String) as is required by contract of ColumnSelectorFactory interface
* fix more tests
* LoggingEmitter: print event as json
* use DefaultRequestLogEventBuilderFactory in emitting request logger by default
* print context in query metric as json
* removed unused jsonMapper from DefaultQueryMetrics
* add comment
* remove change to DefaultRequestLogEventBuilderFactory.java
* Fallback to parsing classpath for hadoop task in Java 9+
In Java 9 and above we cannot assume that the system classloader is an
instance of URLClassLoader. This change adds a fallback method to parse
the system classpath in that case, and adds a unit test to validate it matches
what JDK8 would do.
Note: This has not been tested in an actual hadoop setup, so this is mostly
to help us pass unit tests.
* Remove granularity test of dubious value
One of our granularity tests relies on system classloader being a URLClassLoaders to
catch a bug related to class initialization and static initializers using a subclass (see
#2979)
This test was added to catch a potential regression, but it assumes we would add back
the same type of static initializers to this specific class, so it seems to be of dubious value
as a unit test and mostly serves to illustrate the bug.
relates to #5589
When building column/dimension selectors, calling computeIfAbsent can
cause the applied function to modify the same cache through virtual
column references. The JDK11 map implementation detects this change and
will throw an exception.
This fix – while not as elegant – breaks the single call into two
steps to avoid this problem.
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* check ctyle for constant field name
* merging with upstream
* review-1
* unknow changes
* unknow changes
* review-2
* merging with master
* review-2 1 changes
* review changes-2 2
* bug fix
* use Number instead of long for response context to be forgiving of json serde to int or long
* test that encounters issue without fix
* now with more test
* is ints
* make double sum/min/max agg work on string columns
* style and compilation fixes
* fix tests
* address review comments
* add comment on SimpleDoubleAggregatorFactory
* make checkstyle happy
* Refactored ResponseContext and aggregated its keys into Enum
* Added unit tests for ResponseContext and refactored the serialization
* Removed unused methods
* Fixed code style
* Fixed code style
* Fixed code style
* Made SerializationResult static
* Updated according to the PR discussion:
Renamed an argument
Updated comparator
Replaced Pair usage with Map.Entry
Added a comment about quadratic complexity
Removed boolean field with an expression
Renamed SerializationResult field
Renamed the method merge to add and renamed several context keys
Renamed field and method related to scanRowsLimit
Updated a comment
Simplified a block of code
Renamed a variable
* Added JsonProperty annotation to renamed ScanQuery field
* Extension-friendly context key implementation
* Refactored ResponseContext: updated delegate type, comments and exceptions
Reducing serialized context length by removing some of its'
collection elements
* Fixed tests
* Simplified response context truncation during serialization
* Extracted a method of removing elements from a response context and
added some comments
* Fixed typos and updated comments
* 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
* GroupBy array-based result rows.
Fixes#8118; see that proposal for details.
Other than the GroupBy changes, the main other "interesting" classes are:
- ResultRow: The array-based result type.
- BaseQuery: T is no longer required to be Comparable.
- QueryToolChest: Adds "decorateObjectMapper" to enable query-aware serialization
and deserialization of result rows (necessary due to their positional nature).
- QueryResource: Uses the new decoration functionality.
- DirectDruidClient: Also uses the new decoration functionality.
- QueryMaker (in Druid SQL): Modifications to read ResultRows.
These classes weren't changed, but got some new javadocs:
- BySegmentQueryRunner
- FinalizeResultsQueryRunner
- Query
* Adjustments for TC stuff.
* 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
* add CachingClusteredClient benchmark, refactor some stuff
* revert WeightedServerSelectorStrategy to ConnectionCountServerSelectorStrategy and remove getWeight since felt artificial, default mergeResults in toolchest implementation for topn, search, select
* adjust javadoc
* adjustments
* oops
* use it
* use BinaryOperator, remove CombiningFunction, use Comparator instead of Ordering, other review adjustments
* rename createComparator to createResultComparator, fix typo, firstNonNull nullable parameters
* doc updates and changes to use the CollectionUtils.mapValues utility method
* Add Structural Search patterns to intelliJ
* refactoring from PR comments
* put -> putIfAbsent
* do single key lookup
* 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.
Make static imports forbidden in tests and remove all occurrences to be
consistent with the non-test code.
Also, various changes to files affected by above:
- Reformat to adhere to druid style guide
- Fix various IntelliJ warnings
- Fix various SonarLint warnings (e.g., the expected/actual args to
Assert.assertEquals() were flipped)
* GroupBy: Fix improper uses of StorageAdapter#getColumnCapabilities.
1) A usage in "isArrayAggregateApplicable" that would potentially incorrectly use
array-based aggregation on a virtual column that shadows a real column.
2) A usage in "process" that would potentially use the more expensive multi-value
aggregation path on a singly-valued virtual column. (No correctness issue, but
a performance issue.)
* Add addl javadoc.
* ExpressionVirtualColumn: Set multi-value flag.
Himanshu
Clint Wylie
Gian Merlino
Chi Cao Minh
Benedict Jin
Jonathan Wei
Jihoon Son
Xavier Léauté
SandishKumarHN
Fokko Driesprong
Samarth Jain
Eugene Sevastianov
Sashidhar Thallam
Surekha