Commit Graph

430 Commits

Author SHA1 Message Date
Gian Merlino 72432c2e78
Speed up SQL IN using SCALAR_IN_ARRAY. (#16388)
* Speed up SQL IN using SCALAR_IN_ARRAY.

Main changes:

1) DruidSqlValidator now includes a rewrite of IN to SCALAR_IN_ARRAY, when the size of
   the IN is above inFunctionThreshold. The default value of inFunctionThreshold
   is 100. Users can restore the prior behavior by setting it to Integer.MAX_VALUE.

2) SearchOperatorConversion now generates SCALAR_IN_ARRAY when converting to a regular
   expression, when the size of the SEARCH is above inFunctionExprThreshold. The default
   value of inFunctionExprThreshold is 2. Users can restore the prior behavior by setting
   it to Integer.MAX_VALUE.

3) ReverseLookupRule generates SCALAR_IN_ARRAY if the set of reverse-looked-up values is
   greater than inFunctionThreshold.

* Revert test.

* Additional coverage.

* Update docs/querying/sql-query-context.md

Co-authored-by: Benedict Jin <asdf2014@apache.org>

* New test.

---------

Co-authored-by: Benedict Jin <asdf2014@apache.org>
2024-05-14 08:09:27 -07:00
Gian Merlino cdf78ecccd
Fix IndexSpec in SqlBenchmark to use stringEncodingStrategy (#16336) 2024-05-14 14:59:15 +05:30
Laksh Singla 4bfc186153
Support sorting on complex columns in MSQ (#16322)
MSQ sorts the columns in a highly specialized manner by byte comparisons. As such the values are serialized differently. This works well for the primitive types and primitive arrays, however complex types cannot be serialized specially.

This PR adds the support for sorting the complex columns by deserializing the value from the field and comparing it via the type strategy. This is a lot slower than the byte comparisons, however, it's the only way to support sorting on complex columns that can have arbitrary serialization not optimized for MSQ.

The primitives and the arrays are still compared via the byte comparison, therefore this doesn't affect the performance of the queries supported before the patch. If there's a sorting key with mixed complex and primitive/primitive array types, for example: longCol1 ASC, longCol2 ASC, complexCol1 DESC, complexCol2 DESC, stringCol1 DESC, longCol3 DESC, longCol4 ASC, the comparison will happen like:

    longCol1, longCol2 (ASC) - Compared together via byte-comparison, since both are byte comparable and need to be sorted in ascending order
    complexCol1 (DESC) - Compared via deserialization, cannot be clubbed with any other field
    complexCol2 (DESC) - Compared via deserialization, cannot be clubbed with any other field, even though the prior field was a complex column with the same order
    stringCol1, longCol3 (DESC) - Compared together via byte-comparison, since both are byte comparable and need to be sorted in descending order
    longCol4 (ASC) - Compared via byte-comparison, couldn't be coalesced with the previous fields as the direction was different

This way, we only deserialize the field wherever required
2024-05-13 15:07:05 +05:30
Zoltan Haindrich 2d0e86cbdc
Use quidem to run tests (#16249)
* test scoped jdbc driver for druidtest:/// backed DruidAvaticaTestDriver
** DecoupledTestConfig is used inside the URI - this will make it possible to attach to existing things more easily
* DruidQuidemTestBase can be used to create module level set of quidem tests
* added quidem commands: !convertedPlan, !logicalPlan, !druidPlan, !nativePlan
** for these I've used some values of the Hook which was there in calcite
* there are some shortcuts with proxies(they are only used during testing) - we can probably remove those later
2024-05-02 02:12:42 -04:00
Adarsh Sanjeev 9a2d7c28bc
Prepare master branch for 31.0.0 release (#16333) 2024-04-26 09:22:43 +05:30
Laksh Singla 6bca406d31
Grouping on complex columns aka unifying GroupBy strategies (#16068)
Users can pass complex types as dimensions to the group by queries. For example:

SELECT nested_col1, count(*) FROM foo GROUP BY nested_col1
2024-04-24 23:00:14 +05:30
Rishabh Singh e30790e013
Introduce Segment Schema Publishing and Polling for Efficient Datasource Schema Building (#15817)
Issue: #14989

The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Thereafter, we addressed the problem of publishing schema for realtime segments (#15475). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information.

This is the final change which involves publishing segment schema for finalized segments from task and periodically polling them in the Coordinator.
2024-04-24 22:22:53 +05:30
Tim Williamson 4bdc1890f7
Improve worst-case performance of LIKE filters by 20x (#16153)
* Expected-linear-time LIKE

`LikeDimFilter` was compiling the `LIKE` clause down to a `java.util.regex.Pattern`. Unfortunately, even seemingly simply regexes can lead to [catastrophic backtracking](https://www.regular-expressions.info/catastrophic.html). In particular, something as simple as a few `%` wildcards can end up in [exploding the time complexity](https://www.rexegg.com/regex-explosive-quantifiers.html#remote). This MR implements a simple greedy algorithm that avoids backtracking.

Technically, the algorithm runs in `O(nm)`, where `n` is the length of the string to match and `m` is the length of the pattern. In practice, it should run in linear time: essentially as fast as `String.indexOf()` can search for the next match. Running an updated version of the `LikeFilterBenchmark` with Java 11 on a `t2.xlarge` instance showed at least a 1.7x speed up for a simple "contains" query (`%50%`), and more than a 20x speed up for a "killer" query with four wildcards but no matches (`%%%%x`). The benchmark uses short strings: cases with longer strings should benefit more.

Note that the `REGEX` operator still suffers from the same potentially-catastrophic runtimes. Using a better library than the built-in `java.util.regex.Pattern` (e.g., [joni](https://github.com/jruby/joni)) would be a good idea to avoid accidental — or intentional — DoSing.

```
Benchmark                                (cardinality)  Mode  Cnt  Before Score       Error  After Score       Error  Units  Before / After
LikeFilterBenchmark.matchBoundPrefix              1000  avgt   10         6.686 ±     0.026        6.765 ±     0.087  us/op           0.99x
LikeFilterBenchmark.matchBoundPrefix            100000  avgt   10       163.936 ±     1.589      140.014 ±     0.563  us/op           1.17x
LikeFilterBenchmark.matchBoundPrefix           1000000  avgt   10      1235.259 ±     7.318     1165.330 ±     9.300  us/op           1.06x
LikeFilterBenchmark.matchLikeContains             1000  avgt   10       255.074 ±     1.530      130.212 ±     3.314  us/op           1.96x
LikeFilterBenchmark.matchLikeContains           100000  avgt   10     34789.639 ±   210.219    18563.644 ±   100.030  us/op           1.87x
LikeFilterBenchmark.matchLikeContains          1000000  avgt   10    287265.302 ±  1790.957   164684.778 ±   317.698  us/op           1.74x
LikeFilterBenchmark.matchLikeEquals               1000  avgt   10         0.410 ±     0.003        0.399 ±     0.001  us/op           1.03x
LikeFilterBenchmark.matchLikeEquals             100000  avgt   10         0.793 ±     0.005        0.719 ±     0.003  us/op           1.10x
LikeFilterBenchmark.matchLikeEquals            1000000  avgt   10         0.864 ±     0.004        0.839 ±     0.005  us/op           1.03x
LikeFilterBenchmark.matchLikeKiller               1000  avgt   10      3077.629 ±     7.928      103.714 ±     2.417  us/op          29.67x
LikeFilterBenchmark.matchLikeKiller             100000  avgt   10    311048.049 ± 13466.911    14777.567 ±    70.242  us/op          21.05x
LikeFilterBenchmark.matchLikeKiller            1000000  avgt   10   3055855.099 ± 18387.839    92476.621 ±  1198.255  us/op          33.04x
LikeFilterBenchmark.matchLikePrefix               1000  avgt   10         6.711 ±     0.035        6.653 ±     0.046  us/op           1.01x
LikeFilterBenchmark.matchLikePrefix             100000  avgt   10       161.535 ±     0.574      163.740 ±     0.833  us/op           0.99x
LikeFilterBenchmark.matchLikePrefix            1000000  avgt   10      1255.696 ±     5.207     1201.378 ±     3.466  us/op           1.05x
LikeFilterBenchmark.matchRegexContains            1000  avgt   10       467.736 ±     2.546      481.431 ±     5.647  us/op           0.97x
LikeFilterBenchmark.matchRegexContains          100000  avgt   10     64871.766 ±   223.341    65483.992 ±   391.249  us/op           0.99x
LikeFilterBenchmark.matchRegexContains         1000000  avgt   10    482906.004 ±  2003.583   477195.835 ±  3094.605  us/op           1.01x
LikeFilterBenchmark.matchRegexKiller              1000  avgt   10      8071.881 ±    18.026     8052.322 ±    17.336  us/op           1.00x
LikeFilterBenchmark.matchRegexKiller            100000  avgt   10   1120094.520 ±  2428.172   808321.542 ±  2411.032  us/op           1.39x
LikeFilterBenchmark.matchRegexKiller           1000000  avgt   10   8096745.012 ± 40782.747  8114114.896 ± 43250.204  us/op           1.00x
LikeFilterBenchmark.matchRegexPrefix              1000  avgt   10       170.843 ±     1.095      175.924 ±     1.144  us/op           0.97x
LikeFilterBenchmark.matchRegexPrefix            100000  avgt   10     17785.280 ±   116.813    18708.888 ±    61.857  us/op           0.95x
LikeFilterBenchmark.matchRegexPrefix           1000000  avgt   10    174415.586 ±  1827.478   173190.799 ±   949.224  us/op           1.01x
LikeFilterBenchmark.matchSelectorEquals           1000  avgt   10         0.411 ±     0.003        0.416 ±     0.002  us/op           0.99x
LikeFilterBenchmark.matchSelectorEquals         100000  avgt   10         0.728 ±     0.003        0.739 ±     0.003  us/op           0.99x
LikeFilterBenchmark.matchSelectorEquals        1000000  avgt   10         0.842 ±     0.002        0.879 ±     0.007  us/op           0.96x
```

* Take into account whether druid.generic.useDefaultValueForNull is set in LikeDimFilterTest assertions.

* Attempt to placate CodeQL.

* Fix handling of multi-pattern suffixes.

* Expected-linear-time LIKE

`LikeDimFilter` was compiling the `LIKE` clause down to a `java.util.regex.Pattern`. Unfortunately, even seemingly simply regexes can lead to [catastrophic backtracking](https://www.regular-expressions.info/catastrophic.html). In particular, something as simple as a few `%` wildcards can end up in [exploding the time complexity](https://www.rexegg.com/regex-explosive-quantifiers.html#remote). This MR implements a simple greedy algorithm that avoids the catastrophic backtracking, converting the `LIKE` pattern into a list of `java.util.regex.Pattern` by splitting on the `%` wildcard. The resulting sub-patterns do no backtracking, and a simple greedy loop using `Matcher.find()` to progress through the string is used.

Running an updated version of the `LikeFilterBenchmark` with Java 11 on a `t2.xlarge` instance showed at least a 1.15x speed up for a simple "contains" query (`%50%`), and more than a 20x speed up for a "killer" query with four wildcards but no matches (`%%%%x`). The benchmark uses short strings: cases with longer strings should benefit more.

Note that the `REGEX` operator still suffers from the same potentially-catastrophic runtimes. Using a better library than the built-in `java.util.regex.Pattern` (e.g., [joni](https://github.com/jruby/joni)) would be a good idea to avoid accidental — or intentional — DoSing.

```
Benchmark                                      (cardinality)  Mode  Cnt  Before Score       Error      After Score     Error  Units  Before/After
LikeFilterBenchmark.matchBoundPrefix                    1000  avgt   10         5.410 ±     0.010          5.582 ±     0.004  us/op         0.97x
LikeFilterBenchmark.matchBoundPrefix                  100000  avgt   10       140.920 ±     0.306        141.082 ±     0.391  us/op         1.00x
LikeFilterBenchmark.matchBoundPrefix                 1000000  avgt   10      1082.762 ±     1.070       1171.407 ±     1.628  us/op         0.92x
LikeFilterBenchmark.matchLikeComplexContains            1000  avgt   10       221.572 ±     0.228        183.742 ±     0.210  us/op         1.21x
LikeFilterBenchmark.matchLikeComplexContains          100000  avgt   10     25461.362 ±    21.481      17373.828 ±    42.577  us/op         1.47x
LikeFilterBenchmark.matchLikeComplexContains         1000000  avgt   10    221075.917 ±   919.238     177454.683 ±   506.420  us/op         1.25x
LikeFilterBenchmark.matchLikeContains                   1000  avgt   10       283.015 ±     0.219        218.835 ±     3.126  us/op         1.29x
LikeFilterBenchmark.matchLikeContains                 100000  avgt   10     30202.910 ±    32.697      26713.488 ±    49.525  us/op         1.13x
LikeFilterBenchmark.matchLikeContains                1000000  avgt   10    284661.411 ±   130.324     243381.857 ±   540.143  us/op         1.17x
LikeFilterBenchmark.matchLikeEquals                     1000  avgt   10         0.386 ±     0.001          0.380 ±     0.001  us/op         1.02x
LikeFilterBenchmark.matchLikeEquals                   100000  avgt   10         0.670 ±     0.001          0.705 ±     0.002  us/op         0.95x
LikeFilterBenchmark.matchLikeEquals                  1000000  avgt   10         0.839 ±     0.001          0.796 ±     0.001  us/op         1.05x
LikeFilterBenchmark.matchLikeKiller                     1000  avgt   10      4882.099 ±     7.953        170.142 ±     0.494  us/op        28.69x
LikeFilterBenchmark.matchLikeKiller                   100000  avgt   10    524122.010 ±   390.170      19461.637 ±   117.090  us/op        26.93x
LikeFilterBenchmark.matchLikeKiller                  1000000  avgt   10   5121795.377 ±  4176.052     181162.978 ±   368.443  us/op        28.27x
LikeFilterBenchmark.matchLikePrefix                     1000  avgt   10         5.708 ±     0.005          5.677 ±     0.011  us/op         1.01x
LikeFilterBenchmark.matchLikePrefix                   100000  avgt   10       141.853 ±     0.554        108.313 ±     0.330  us/op         1.31x
LikeFilterBenchmark.matchLikePrefix                  1000000  avgt   10      1199.148 ±     1.298       1153.297 ±     1.575  us/op         1.04x
LikeFilterBenchmark.matchLikeSuffix                     1000  avgt   10       256.020 ±     0.283        196.339 ±     0.564  us/op         1.30x
LikeFilterBenchmark.matchLikeSuffix                   100000  avgt   10     29917.931 ±    28.218      21450.997 ±    20.341  us/op         1.39x
LikeFilterBenchmark.matchLikeSuffix                  1000000  avgt   10    241225.193 ±   465.824     194034.292 ±   362.312  us/op         1.24x
LikeFilterBenchmark.matchRegexComplexContains           1000  avgt   10       119.597 ±     0.635        135.550 ±     0.697  us/op         0.88x
LikeFilterBenchmark.matchRegexComplexContains         100000  avgt   10     13089.670 ±    13.738      13766.712 ±    12.802  us/op         0.95x
LikeFilterBenchmark.matchRegexComplexContains        1000000  avgt   10    130822.830 ±  1624.048     131076.029 ±  1636.811  us/op         1.00x
LikeFilterBenchmark.matchRegexContains                  1000  avgt   10       573.273 ±     0.421        615.399 ±     0.633  us/op         0.93x
LikeFilterBenchmark.matchRegexContains                100000  avgt   10     57259.313 ±   162.747      62900.380 ±    44.746  us/op         0.91x
LikeFilterBenchmark.matchRegexContains               1000000  avgt   10    571335.768 ±  2822.776     542536.982 ±   780.290  us/op         1.05x
LikeFilterBenchmark.matchRegexKiller                    1000  avgt   10     11525.499 ±     8.741      11061.791 ±    21.746  us/op         1.04x
LikeFilterBenchmark.matchRegexKiller                  100000  avgt   10   1170414.723 ±   766.160    1144437.291 ±   886.263  us/op         1.02x
LikeFilterBenchmark.matchRegexKiller                 1000000  avgt   10  11507668.302 ± 11318.176  110381620.014 ± 10707.974  us/op         1.11x
LikeFilterBenchmark.matchRegexPrefix                    1000  avgt   10       156.460 ±     0.097        155.217 ±     0.431  us/op         1.01x
LikeFilterBenchmark.matchRegexPrefix                  100000  avgt   10     15056.491 ±    23.906      15508.965 ±   763.976  us/op         0.97x
LikeFilterBenchmark.matchRegexPrefix                 1000000  avgt   10    154416.563 ±   473.108     153737.912 ±   273.347  us/op         1.00x
LikeFilterBenchmark.matchRegexSuffix                    1000  avgt   10       610.684 ±     0.462        590.352 ±     0.334  us/op         1.03x
LikeFilterBenchmark.matchRegexSuffix                  100000  avgt   10     53196.517 ±    78.155      59460.261 ±    56.934  us/op         0.89x
LikeFilterBenchmark.matchRegexSuffix                 1000000  avgt   10    536100.944 ±   440.353     550098.917 ±   740.464  us/op         0.97x
LikeFilterBenchmark.matchSelectorEquals                 1000  avgt   10         0.390 ±     0.001          0.366 ±     0.001  us/op         1.07x
LikeFilterBenchmark.matchSelectorEquals               100000  avgt   10         0.724 ±     0.001          0.714 ±     0.001  us/op         1.01x
LikeFilterBenchmark.matchSelectorEquals              1000000  avgt   10         0.826 ±     0.001          0.847 ±     0.001  us/op         0.98x
```
2024-04-23 22:45:23 -07:00
Laksh Singla b9bbde5c0a
Fix deadlock that can occur while merging group by results (#15420)
This PR prevents such a deadlock from happening by acquiring the merge buffers in a single place and passing it down to the runner that might need it.
2024-04-22 14:10:44 +05:30
Clint Wylie aa230642dd
use PeekableIntIterator for OR filter "partial index" value matchers (#16300) 2024-04-17 08:27:21 -07:00
Gian Merlino 58a8a23243
Avoid conversion to String in JsonReader, JsonNodeReader. (#15693)
* Avoid conversion to String in JsonReader, JsonNodeReader.

These readers were running UTF-8 decode on the provided entity to
convert it to a String, then parsing the String as JSON. The patch
changes them to parse the provided entity's input stream directly.

In order to preserve the nice error messages that include parse errors,
the readers now need to open the entity again on the error path, to
re-read the data. To make this possible, the InputEntity#open contract
is tightened to require the ability to re-open entities, and existing
InputEntity implementations are updated to allow re-opening.

This patch also renames JsonLineReaderBenchmark to JsonInputFormatBenchmark,
updates it to benchmark all three JSON readers, and adds a case that reads
fields out of the parsed row (not just creates it).

* Fixes for static analysis.

* Implement intermediateRowAsString in JsonReader.

* Enhanced JsonInputFormatBenchmark.

Renames JsonLineReaderBenchmark to JsonInputFormatBenchmark, and enhances it to
test various readers (JsonReader, JsonLineReader, JsonNodeReader) as well as
to test with/without field discovery.
2024-03-26 08:16:05 -07:00
Clint Wylie b0a9c318d6
add new typed in filter (#16039)
changes:
* adds TypedInFilter which preserves matching sets in the native match value type
* SQL planner uses new TypedInFilter when druid.generic.useDefaultValueForNull=false (the default)
2024-03-22 12:45:08 -07:00
AmatyaAvadhanula 488d376209
Optimize isOvershadowed when there is a unique minor version for an interval (#15952)
* Optimize isOvershadowed for intervals with timechunk locking
2024-03-20 19:30:00 +05:30
Clint Wylie dd9bc3749a
fix issues with array_contains and array_overlap with null left side arguments (#15974)
changes:
* fix issues with array_contains and array_overlap with null left side arguments
* modify singleThreaded stuff to allow optimizing Function similar to how we do for ExprMacro - removed SingleThreadSpecializable in favor of default impl of asSingleThreaded on Expr with clear javadocs that most callers shouldn't be calling it directly and should be using Expr.singleThreaded static method which uses a shuttle and delegates to asSingleThreaded instead
* add optimized 'singleThreaded' versions of array_contains and array_overlap
* add mv_harmonize_nulls native expression to use with MV_CONTAINS and MV_OVERLAP to allow them to behave consistently with filter rewrites, coercing null and [] into [null]
* fix bug with casting rhs argument for native array_contains and array_overlap expressions
2024-03-13 18:16:10 -07:00
Clint Wylie 313da98879
decouple column serializer compression closers from SegmentWriteoutMedium to optionally allow serializers to release direct memory allocated for compression earlier than when segment is completed (#16076) 2024-03-11 12:28:04 -07:00
Zoltan Haindrich 27d7c30c38
Only use ExprEval in ConstantExpr if its known that it will be safe (#15694)
* `Expr#singleThreaded` which creates a singleThreaded version of the actual expression (caching ExprEval is allowed)
* `Expr#makeSingleThreaded` to make a whole subtree of expressions 'singleThreaded' - uses `Shuttle` to create the new expression tree
* `ConstantExpr#singleThreaded` creates a specialized `ConstantExpr` which does cache the `ExprEval`
* some `@Immutable` annotations were added to make it more likely to notice that there might be something off if a similar change will be made around here for some reason
2024-03-05 12:53:09 -08:00
Clint Wylie 101176590c
adaptive filter partitioning (#15838)
* cooler cursor filter processing allowing much smart utilization of indexes by feeding selectivity forward, with implementations for range and predicate based filters
* added new method Filter.makeFilterBundle which cursors use to get indexes and matchers for building offsets
* AND filter partitioning is now pushed all the way down, even to nested AND filters
* vector engine now uses same indexed base value matcher strategy for OR filters which partially support indexes
2024-02-29 15:38:12 -08:00
Gian Merlino 54b30646f3
Add sqlReverseLookupThreshold for ReverseLookupRule. (#15832)
If lots of keys map to the same value, reversing a LOOKUP call can slow
things down unacceptably. To protect against this, this patch introduces
a parameter sqlReverseLookupThreshold representing the maximum size of an
IN filter that will be created as part of lookup reversal.

If inSubQueryThreshold is set to a smaller value than
sqlReverseLookupThreshold, then inSubQueryThreshold will be used instead.
This allows users to use that single parameter to control IN sizes if they
wish.
2024-02-06 16:32:05 +05:30
Vishesh Garg 37d1650ccf
Benchmark for query planning time for IN queries (#15688)
Adds a set of benchmark queries for measuring the planning time with the IN operator. Current results indicate that with the recent optimizations, the IN planning time with 100K expressions in the IN clause is just 3s and with 1M is 46s. For IN clause paired with OR <col>=<val> expr, the numbers are 10s and 155s for 100K and 1M, resp.
2024-01-31 15:40:31 +05:30
Karan Kumar c4990f56d6
Prepare main branch for next 30.0.0 release. (#15707) 2024-01-23 15:55:54 +05:30
Zoltan Haindrich d6a12c4389
Add ability to enable ResultCache in tests (#15465) 2024-01-22 09:02:59 -05:00
Gian Merlino 792e5c58e4
IncrementalIndex#add is no longer thread-safe. (#15697)
* IncrementalIndex#add is no longer thread-safe.

Following #14866, there is no longer a reason for IncrementalIndex#add
to be thread-safe.

It turns out it already was not using its selectors in a thread-safe way,
as exposed by #15615 making `testMultithreadAddFactsUsingExpressionAndJavaScript`
in `IncrementalIndexIngestionTest` flaky. Note that this problem isn't
new: Strings have been stored in the dimension selectors for some time,
but we didn't have a test that checked for that case; we only have
this test that checks for concurrent adds involving numeric selectors.

At any rate, this patch changes OnheapIncrementalIndex to no longer try
to offer a thread-safe "add" method. It also improves performance a bit
by adding a row ID supplier to the selectors it uses to read InputRows,
meaning that it can get the benefit of caching values inside the selectors.

This patch also:

1) Adds synchronization to HyperUniquesAggregator and CardinalityAggregator,
   which the similar datasketches versions already have. This is done to
   help them adhere to the contract of Aggregator: concurrent calls to
   "aggregate" and "get" must be thread-safe.

2) Updates OnHeapIncrementalIndexBenchmark to use JMH and moves it to the
   druid-benchmarks module.

* Spelling.

* Changes from static analysis.

* Fix javadoc.
2024-01-18 03:45:22 -08:00
Gian Merlino d3d0c1c91e
Faster parsing: reduce String usage, list-based input rows. (#15681)
* Faster parsing: reduce String usage, list-based input rows.

Three changes:

1) Reworked FastLineIterator to optionally avoid generating Strings
   entirely, and reduce copying somewhat. Benefits the line-oriented
   JSON, CSV, delimited (TSV), and regex formats.

2) In the delimited (TSV) format, when the delimiter is a single byte,
   split on UTF-8 bytes directly.

3) In CSV and delimited (TSV) formats, use list-based input rows when
   the column list is provided upfront by the user.

* Fix style.

* Fix inspections.

* Restore validation.

* Remove fastutil-extra.

* Exception type.

* Fixes for error messages.

* Fixes for null handling.
2024-01-18 19:18:46 +08:00
Gian Merlino 500681d0cb
Add ImmutableLookupMap for static lookups. (#15675)
* Add ImmutableLookupMap for static lookups.

This patch adds a new ImmutableLookupMap, which comes with an
ImmutableLookupExtractor. It uses a fastutil open hashmap plus two
lists to store its data in such a way that forward and reverse
lookups can both be done quickly. I also observed footprint to be
somewhat smaller than Java HashMap + MapLookupExtractor for a 1 million
row lookup.

The main advantage, though, is that reverse lookups can be done much
more quickly than MapLookupExtractor (which iterates the entire map
for each call to unapplyAll). This speeds up the recently added
ReverseLookupRule (#15626) during SQL planning with very large lookups.

* Use in one more test.

* Fix benchmark.

* Object2ObjectOpenHashMap

* Fixes, and LookupExtractor interface update to have asMap.

* Remove commented-out code.

* Fix style.

* Fix import order.

* Add fastutil.

* Avoid storing Map entries.
2024-01-13 13:14:01 -08:00
Gian Merlino cccf13ea82
Reverse, pull up lookups in the SQL planner. (#15626)
* Reverse, pull up lookups in the SQL planner.

Adds two new rules:

1) ReverseLookupRule, which eliminates calls to LOOKUP by doing
   reverse lookups.

2) AggregatePullUpLookupRule, which pulls up calls to LOOKUP above
   GROUP BY, when the lookup is injective.

Adds configs `sqlReverseLookup` and `sqlPullUpLookup` to control whether
these rules fire. Both are enabled by default.

To minimize the chance of performance problems due to many keys mapping to
the same value, ReverseLookupRule refrains from reversing a lookup if there
are more keys than `inSubQueryThreshold`. The rationale for using this setting
is that reversal works by generating an IN, and the `inSubQueryThreshold`
describes the largest IN the user wants the planner to create.

* Add additional line.

* Style.

* Remove commented-out lines.

* Fix tests.

* Add test.

* Fix doc link.

* Fix docs.

* Add one more test.

* Fix tests.

* Logic, test updates.

* - Make FilterDecomposeConcatRule more flexible.

- Make CalciteRulesManager apply reduction rules til fixpoint.

* Additional tests, simplify code.
2024-01-12 00:06:31 -08:00
Gian Merlino 2231cb30a4
Faster k-way merging using tournament trees, 8-byte key strides. (#15661)
* Faster k-way merging using tournament trees, 8-byte key strides.

Two speedups for FrameChannelMerger (which does k-way merging in MSQ):

1) Replace the priority queue with a tournament tree, which does fewer
   comparisons.

2) Compare keys using 8-byte strides, rather than 1 byte at a time.

* Adjust comments.

* Fix style.

* Adjust benchmark and test.

* Add eight-list test (power of two).
2024-01-11 08:36:22 -08:00
Clint Wylie df5bcd1367
fix bugs with expression virtual column indexes for expression virtual columns which refer to other virtual columns (#15633)
changes:
* ColumnIndexSelector now extends ColumnSelector. The only real implementation of ColumnIndexSelector, ColumnSelectorColumnIndexSelector, already has a ColumnSelector, so this isn't very disruptive
* removed getColumnNames from ColumnSelector since it was not used
* VirtualColumns and VirtualColumn getIndexSupplier method now needs argument of ColumnIndexSelector instead of ColumnSelector, which allows expression virtual columns to correctly recognize other virtual columns, fixing an issue which would incorrectly handle other virtual columns as non-existent columns instead
* fixed a bug with sql planner incorrectly not using expression filter for equality filters on columns with extractionFn and no virtual column registry
2024-01-08 13:10:11 -08:00
Clint Wylie c221a2634b
overhaul DruidPredicateFactory to better handle 3VL (#15629)
* overhaul DruidPredicateFactory to better handle 3VL

fixes some bugs caused by some limitations of the original design of how DruidPredicateFactory interacts with 3-value logic. The primary impacted area was with how filters on values transformed with expressions or extractionFn which turn non-null values into nulls, which were not possible to be modelled with the 'isNullInputUnknown' method

changes:
* adds DruidObjectPredicate to specialize string, array, and object based predicates instead of using guava Predicate
* DruidPredicateFactory now uses DruidObjectPredicate
* introduces DruidPredicateMatch enum, which all predicates returned from DruidPredicateFactory now use instead of booleans to indicate match. This means DruidLongPredicate, DruidFloatPredicate, DruidDoublePredicate, and the newly added DruidObjectPredicate apply methods all now return DruidPredicateMatch. This allows matchers and indexes
* isNullInputUnknown has been removed from DruidPredicateFactory

* rename, fix test

* adjust

* style

* npe

* more test

* fix default value mode to not match new test
2024-01-05 19:08:02 -08:00
Clint Wylie f19ece146f
expression virtual column indexes (#15585)
* ExpressionVirtualColumn + indexes = bff. Expression virtual columns can now use indexes of the underlying columns similar to how expression filters
2024-01-03 21:00:39 -08:00
Zoltan Haindrich 7552dc49fb
Reduce amount of expression objects created during evaluations (#15552)
I was looking into a query which was performing a bit poorly because the case_searched was touching more than 1 columns (if there is only 1 column there is a cache based evaluator).
While I was doing that I've noticed that there are a few simple things which could help a bit:

use a static TRUE/FALSE instead of creating a new object every time
create the ExprEval early for ConstantExpr -s (except the one for BigInteger which seem to have some odd contract)
return early from type autodetection
these changes mostly reduce the amount of garbage the query creates during case_searched evaluation; although ExpressionSelectorBenchmark shows some improvements ~15% - but my manual trials on the taxi dataset with 60M rows showed more improvements - probably due to the fact that these changes mostly only reduce gc pressure.
2023-12-15 16:11:59 +05:30
Clint Wylie e55f6b6202
remove search auto strategy, estimateSelectivity of BitmapColumnIndex (#15550)
* remove search auto strategy, estimateSelectivity of BitmapColumnIndex

* more cleanup
2023-12-13 16:30:01 -08:00
Clint Wylie 5ce4aab3b8
update ARRAY_OVERLAP to plan with ArrayContainsElement for ARRAY columns (#15451)
Updates ARRAY_OVERLAP to use the same ArrayContainsElement filter added in #15366 when filtering ARRAY typed columns so that it can also use indexes like ARRAY_CONTAINS.
2023-11-30 10:05:20 +05:30
Clint Wylie 0516d0dae4
simplify IncrementalIndex since group-by v1 has been removed (#15448) 2023-11-29 14:46:16 -08:00
Clint Wylie 64fcb32bcf
add native 'array contains element' filter (#15366)
* add native arrayContainsElement filter to use array column element indexes
2023-11-29 03:33:00 -08:00
Clint Wylie 97623b408c
add optional 'castToType' parameter to 'auto' column schema (#15417)
* auto but.. with an expected type
2023-11-28 17:19:23 -08:00
Rishabh Singh 8c802e4c9b
Relocating Table Schema Building: Shifting from Brokers to Coordinator for Improved Efficiency (#14985)
In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal.

To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
2023-11-04 19:33:25 +05:30
Laksh Singla 5f86072456
Prepare master for Druid 29 (#15121)
Prepare master for Druid 29
2023-10-11 10:33:45 +05:30
Xavier Léauté adef2069b1
Make unit tests pass with Java 21 (#15014)
This change updates dependencies as needed and fixes tests to remove code incompatible with Java 21
As a result all unit tests now pass with Java 21.

* update maven-shade-plugin to 3.5.0 and follow-up to #15042
  * explain why we need to override configuration when specifying outputFile
  * remove configuration from dependency management in favor of explicit overrides in each module.
* update to mockito to 5.5.0 for Java 21 support when running with Java 11+
  * continue using latest mockito 4.x (4.11.0) when running with Java 8  
  * remove need to mock private fields
* exclude incorrectly declared mockito dependency from pac4j-oidc
* remove mocking of ByteBuffer, since sealed classes can no longer be mocked in Java 21
* add JVM options workaround for system-rules junit plugin not supporting Java 18+
* exclude older versions of byte-buddy from assertj-core
* fix for Java 19 changes in floating point string representation
* fix missing InitializedNullHandlingTest
* update easymock to 5.2.0 for Java 21 compatibility
* update animal-sniffer-plugin to 1.23
* update nl.jqno.equalsverifier to 3.15.1
* update exec-maven-plugin to 3.1.0
2023-10-03 22:41:21 -07:00
Soumyava 8088a763a6
Vectorize earliest aggregator for both numeric and string types (#14408)
* Vectorizing earliest for numeric

* Vectorizing earliest string aggregator

* checkstyle fix

* Removing unnecessary exceptions

* Ignoring tests in MSQ as earliest is not supported for numeric there

* Fixing benchmarks

* Updating tests as MSQ does not support earliest for some cases

* Addressing review comments by adding the following:
1. Checking capabilities first before creating selectors
2. Removing mockito in tests for numeric first aggs
3. Removing unnecessary tests

* Addressing issues for dictionary encoded single string columns where we can use the dictionary ids instead of the entire string

* Adding a flag for multi value dimension selector

* Addressing comments

* 1 more change

* Handling review comments part 1

* Handling review comments and correctness fix for latest_by when the time expression need not be in sorted order

* Updating numeric first vector agg

* Revert "Updating numeric first vector agg"

This reverts commit 4291709901.

* Updating code for correctness issues

* fixing an issue with latest agg

* Adding more comments and removing an unnecessary check

* Addressing null checks for tie selector and only vectorize false for quantile sketches
2023-09-05 08:41:42 -07:00
Clint Wylie 36e659a501
remove group-by v1 (#14866)
* remove group-by v1

* docs

* remove unused configs, fix test

* fix test

* adjustments

* why not

* adjust

* review stuff
2023-08-23 12:44:06 -07:00
Clint Wylie fb053c399c
consolidate json and auto indexers, remove v4 nested column serializer (#14456) 2023-08-22 18:50:11 -07:00
Clint Wylie 194a9c9abc
set druid.expressions.useStrictBooleans to true by default (#14734) 2023-08-22 00:19:56 -07:00
Kashif Faraz c211dcc4b3
Clean up compaction logs on coordinator (#14875)
Changes:
- Move logic of `NewestSegmentFirstIterator.needsCompaction` to `CompactionStatus`
to improve testability and readability
- Capture the list of checks performed to determine if compaction is needed in a readable
manner in `CompactionStatus.CHECKS`
- Make `CompactionSegmentIterator` iterate over instances of `SegmentsToCompact`
instead of `List<DataSegment>`. This allows use of the `umbrellaInterval` later.
- Replace usages of `QueueEntry` with `SegmentsToCompact`
- Move `SegmentsToCompact` out of `NewestSegmentFirstIterator`
- Simplify `CompactionStatistics`
- Reduce level of less important logs to debug
- No change made to tests to ensure correctness
2023-08-21 17:30:41 +05:30
Clint Wylie 6b14dde50e
deprecate config-magic in favor of json configuration stuff (#14695)
* json config based processing and broker merge configs to deprecate config-magic
2023-08-16 18:23:57 -07:00
dependabot[bot] f0a79fa0e4
Bump org.apache.maven.plugins:maven-source-plugin from 2.2.1 to 3.3.0 (#14812)
Bumps [org.apache.maven.plugins:maven-source-plugin](https://github.com/apache/maven-source-plugin) from 2.2.1 to 3.3.0.
- [Commits](https://github.com/apache/maven-source-plugin/compare/maven-source-plugin-2.2.1...maven-source-plugin-3.3.0)

---
updated-dependencies:
- dependency-name: org.apache.maven.plugins:maven-source-plugin
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2023-08-15 07:39:19 -07:00
Clint Wylie e5661a394c
refactor front-coded into static classes instead of using functional interfaces (#14572)
* refactor front-coded into static classes instead of using functional interfaces

* shared v0 static method instead of copy
2023-08-04 10:52:36 -07:00
imply-cheddar 748874405c
Minimize PostAggregator computations (#14708)
* Minimize PostAggregator computations

Since a change back in 2014, the topN query has been computing
all PostAggregators on all intermediate responses from leaf nodes
to brokers.  This generates significant slow downs for queries
with relatively expensive PostAggregators.  This change rewrites
the query that is pushed down to only have the minimal set of
PostAggregators such that it is impossible for downstream
processing to do too much work.  The final PostAggregators are
applied at the very end.
2023-08-04 00:04:31 +05:30
Kashif Faraz 22290fd632
Test: Simplify test impl of LoadQueuePeon (#14684)
Changes
- Rename `LoadQueuePeonTester` to `TestLoadQueuePeon`
- Simplify `TestLoadQueuePeon` by removing dependency on `CuratorLoadQueuePeon`
- Remove usages of mock peons in `LoadRuleTest` and use `TestLoadQueuePeon` instead
2023-07-28 16:14:23 +05:30
Clint Wylie 913416c669
add equality, null, and range filter (#14542)
changes:
* new filters that preserve match value typing to better handle filtering different column types
* sql planner uses new filters by default in sql compatible null handling mode
* remove isFilterable from column capabilities
* proper handling of array filtering, add array processor to column processors
* javadoc for sql test filter functions
* range filter support for arrays, tons more tests, fixes
* add dimension selector tests for mixed type roots
* support json equality
* rename semantic index maker thingys to mostly have plural names since they typically make many indexes, e.g. StringValueSetIndex -> StringValueSetIndexes
* add cooler equality index maker, ValueIndexes 
* fix missing string utf8 index supplier
* expression array comparator stuff
2023-07-18 12:15:22 -07:00
AmatyaAvadhanula 0412f40d36
Prepare master branch for next release, 28.0.0 (#14595)
* Prepare master branch for next release, 28.0.0
2023-07-18 09:22:30 +05:30