Refactor TSDataType switches to use TypeService by jt2594838 · Pull Request #18606 · apache/iotdb

jt2594838 · 2026-09-09T02:06:48Z

What is changed

Refactor TSDataType switch handling into TypeService implementations and add an ArchUnit check that rejects TSDataType switches outside TypeService.
Update Tablet decoding and AlignedTVList WAL handling for TsFile 2.4.1-260915-SNAPSHOT.
Merge the latest master branch changes.
Move numeric input scans for OrderedIrateAccumulator, GroupedOrderedRateAccumulator, GroupedOrderedIncreaseAccumulator, and GroupedOrderedDeltaAccumulator into the existing RATE_INPUT_SERVICE type-specific loops. Type dispatch occurs once per batch, while null handling, logical mask positions, value/time/window validation, and ordered state updates retain their original semantics.
Batch AlignedTVList WAL writes by column and physical array segment through ALIGNED_WAL_BATCH_WRITER_SERVICE. Each segment is cast once, preserving value/null-flag interleaving and placeholders for unmaterialized segments.
Fix GroupedApproxCountDistinctAccumulator sparse-mask traversal to use the selected-position count, preventing out-of-bounds access and processing of unselected rows.
Fix deleted-time bitmap size accounting and decoding in AlignedTVList: include the existing payload in the total size and read the bitmap length as the fixed-width integer already emitted by the WAL writer. The serialized format is unchanged.

Performance measurements

Standalone JVM microbenchmarks compare an independently compiled baseline at c4ec742b2ebc29ba53bd0ce1c96d9a990663fb9d with the retained optimization patch. The independent HLL mask and WAL bitmap correctness fixes were applied to both sides so they execute equivalent workloads. These measurements isolate the optimization experiment and are not a measurement of the intervening master merge.

Intel Core i9-12900, 16 cores / 24 threads; JBR 21.0.8. Maven sources target Java 17; the standalone harness and patched baseline classes were compiled with javac 21.
1,024 input rows per batch; three separate JVM forks per configuration, alternating baseline/candidate order. Speedup is baseline median time divided by candidate median time; values above 1 mean faster.
Rate accumulators: eight warmup and nine measured iterations, 2,048 batches per iteration, 16 groups for grouped cases. Mixed-type runs alternate INT32, INT64, FLOAT, and DOUBLE batches. Sparse masks select half the positions and include null values.
WAL: five warmup and seven measured iterations, 512 batches per iteration. The null/deletion fixture includes unmaterialized segments, null values, and deleted timestamps; it still serializes all rows.

Ordered rate accumulators

Accumulator	Mixed types, all rows	Mixed types, sparse mask	Fixed type, all rows	Fixed type, sparse mask
`OrderedIrateAccumulator`	11.65x	8.39x	0.92–0.97x	1.49–1.61x
`GroupedOrderedRateAccumulator`	2.08x	2.18x	1.02–1.05x	1.15–1.21x
`GroupedOrderedIncreaseAccumulator`	2.06x	2.23x	1.02–1.10x	1.16–1.22x
`GroupedOrderedDeltaAccumulator`	2.18x	2.32x	1.08–1.10x	1.14–1.29x

Fixed-type ranges cover separate INT32, INT64, FLOAT, and DOUBLE runs. All 240 rate measurements produced matching baseline/candidate checksums.

Tradeoff: OrderedIrateAccumulator is approximately 3%–9% slower for fixed-type, all-row input, adding 0.038–0.116 ns per row. It is retained for the substantially larger mixed-type and sparse-mask gains; this is not a universal speedup.

Aligned WAL writes

Input	Baseline ns/input row	Optimized ns/input row	Speedup
Mixed numeric types, populated	20.2211	6.7314	3.00x
Mixed numeric types, null/deletion fixture	23.8914	13.0100	1.84x
DOUBLE, populated	8.0683	3.1626	2.55x
DOUBLE, null/deletion fixture	9.8063	3.9482	2.48x

Other repositories were building concurrently on this machine, and storage samples showed substantial variability. These are local microbenchmark observations, not end-to-end IoTDB throughput estimates; small differences should be treated as noise. The TsFile JAR checksum remained unchanged throughout the final measurements.

The additional shared grouped/min-by, Percentile/HLL batch-input, IN/NOT IN, WAL batch-reader, and MemPageReader candidates were excluded after testing because their gains did not generalize or some configurations regressed. Their measurements are not included as improvements above.

Validation

For the additional optimization and correctness patch:

61 targeted tests passed: 21 in calc-commons, 38 in datanode, and 2 in the subscription dependency. Coverage includes rate validation across batches, sparse masks and logical group IDs, HLL mask bounds, all scalar WAL types with null segments, exact WAL buffer sizing, and deleted-time bitmap restoration.
128 rate baseline/candidate results matched across four numeric types, full/sparse masks, and plain, region, dictionary, and RLE columns.
WAL equivalence checks passed for all 11 supported scalar types, including original serialized bytes, restored logical values, and deleted-time flags.
English build/tests and Chinese-locale test compilation passed for datanode and all reactor dependencies (-pl iotdb-core/datanode -am).
Spotless, Checkstyle, and git diff --check passed.

Earlier PR validation also passed the ArchUnit TSDataType switch checks without a baseline and REST Chinese-locale test compilation.

jt2594838 · 2026-09-16T06:48:15Z

  public GroupedAvgAccumulator(TSDataType argumentDataType) {
    this.argumentDataType = argumentDataType;
+    Type type = Type.fromTsDataType(argumentDataType);
+    this.inputStrategy = TypeServices.GROUPED_AVG_INPUT_SERVICE.call(type);


Use a typed batch loop for grouped AVG so input type dispatch is outside the row loop. Group IDs still use logical input positions, and count/sum updates preserve input order. NumericBatchAggregationTest verifies masks, group placement and floating-point order; local mixed-type kernels improved 3.08–3.38x, with fixed-DOUBLE performance flat or better.

jt2594838 · 2026-09-16T06:48:16Z

-    this.minResult = TsPrimitiveType.getByType(seriesDataType);
+    this.type = Type.fromTsDataType(seriesDataType);
+    this.minResult = type.getTsPrimitiveType();
+    this.valueUpdater = TypeServices.MIN_COLUMN_BATCH_UPDATER_SERVICE.call(type);


MIN now selects a TypeService strategy containing the native scan, removing the shared per-value updater dispatch. NumericBatchAggregationTest verifies masked/null inputs and the existing NaN, signed-zero and integer-boundary behavior. The local mixed-type benchmark improved; fixed-DOUBLE results were smaller or approximately flat.

jt2594838 · 2026-09-16T06:48:17Z

-    this.maxResult = TsPrimitiveType.getByType(seriesDataType);
+    this.type = Type.fromTsDataType(seriesDataType);
+    this.maxResult = type.getTsPrimitiveType();
+    this.valueUpdater = TypeServices.MAX_COLUMN_BATCH_UPDATER_SERVICE.call(type);


MAX now selects a TypeService strategy containing the native scan, removing the shared per-value updater dispatch. NumericBatchAggregationTest verifies masked/null inputs and the existing NaN, signed-zero and integer-boundary behavior. The local mixed-type benchmark improved; fixed-DOUBLE results were smaller or approximately flat.

jt2594838 · 2026-09-16T06:48:19Z

-    this.extremeResult = TsPrimitiveType.getByType(seriesDataType);
+    this.type = Type.fromTsDataType(seriesDataType);
+    this.extremeResult = type.getTsPrimitiveType();
+    this.valueUpdater = TypeServices.EXTREME_COLUMN_BATCH_UPDATER_SERVICE.call(type);


EXTREME now selects a TypeService strategy containing the native scan, removing the shared per-value updater dispatch. NumericBatchAggregationTest verifies masked/null inputs and the existing NaN, signed-zero and integer-boundary behavior. The local mixed-type benchmark improved; fixed-DOUBLE results were smaller or approximately flat.

jt2594838 · 2026-09-16T06:48:30Z

      TSDataType seriesDataType, VarianceAccumulator.VarianceType varianceType) {
    this.seriesDataType = seriesDataType;
+    this.doubleValueConverter =
+        TypeServices.NUMERIC_BATCH_READER_SERVICE


Use the native numeric batch reader for grouped variance, retaining the existing recurrence callback and logical row order rather than changing the numerical algorithm. NumericMomentBatchTest covers moments/variance across tree, table and grouped implementations, including masked/null inputs. This candidate was retained after mixed-type and fixed-DOUBLE measurements; related candidates with measured regressions were restored.

jt2594838 · 2026-09-16T06:48:32Z

      TSDataType seriesDataType, CentralMomentAccumulator.MomentType momentType) {
    this.seriesDataType = seriesDataType;
+    this.doubleValueConverter =
+        TypeServices.NUMERIC_BATCH_READER_SERVICE


Use the native numeric batch reader for table central moment, retaining the existing recurrence callback and logical row order rather than changing the numerical algorithm. NumericMomentBatchTest covers moments/variance across tree, table and grouped implementations, including masked/null inputs. This candidate was retained after mixed-type and fixed-DOUBLE measurements; related candidates with measured regressions were restored.

jt2594838 · 2026-09-16T06:48:33Z

-      initializeOrValidateWindow(groupId, currentWindowStart, currentWindowEnd);
-      samples.add(groupId, time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


GroupedNaiveDeltaAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:35Z

-      initializeOrValidateWindow(groupId, currentWindowStart, currentWindowEnd);
-      samples.add(groupId, time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


GroupedNaiveIncreaseAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:36Z

-              arguments[1], position, RateFunctionType.IRATE, 2);
-      samples.add(groupId, time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


GroupedNaiveIrateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:38Z

-      initializeOrValidateWindow(groupId, currentWindowStart, currentWindowEnd);
-      samples.add(groupId, time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


GroupedNaiveRateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:39Z

-              arguments[1], position, RateFunctionType.IRATE, 2);
-      update(groupId, time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


GroupedOrderedIrateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:41Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      samples.add(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


NaiveDeltaAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:42Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      samples.add(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


NaiveIncreaseAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:44Z

-              arguments[1], position, RateFunctionType.IRATE, 2);
-      samples.add(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


NaiveIrateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:46Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      samples.add(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


NaiveRateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:47Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      update(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


OrderedDeltaAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:49Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      update(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


OrderedIncreaseAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:51Z

-      initializeOrValidateWindow(currentWindowStart, currentWindowEnd);
-      update(time, value);
-    }
+    TypeServices.RATE_INPUT_SERVICE


OrderedRateAccumulator now dispatches to a native batch reader through RATE_INPUT_SERVICE. It preserves value validation before time/window validation and keeps the existing state update callback, including logical group positions where applicable. RateBatchInputTest exercises all 16 implementations with native and wrapped columns, masks/nulls and validation cases. This is one of the 12 retained rate candidates; the other four were restored after fixed-DOUBLE benchmarks showed regressions.

jt2594838 · 2026-09-16T06:48:52Z

    return value;
  }

+  public static void validateValue(double value, RateFunctionType functionType) {


Expose the existing finite/nonnegative value checks to the typed batch readers without changing exception order or messages. Keep readValue’s scalar checks inline: replacing them with a helper changed the scalar benchmark behavior on paths whose batch refactor was rejected. RateBatchInputTest covers these validation semantics.

jt2594838 · 2026-09-16T06:48:53Z

      Type returnType, ColumnTransformer childColumnTransformer, ZoneId zoneId) {
    super(returnType, childColumnTransformer);
    this.zoneId = zoneId;
+    this.numericCastBatch =


Select the numeric source/target batch strategy once for CAST/TRY_CAST. The 16 INT32/INT64/FLOAT/DOUBLE pairs use native loops; other types keep the existing conversion path. NumericCastBatchTest covers overflow, NaN, null/selection, region and RLE inputs, including TRY_CAST null results. Local mixed-type kernels improved 2.11–2.83x; fixed DOUBLE-to-DOUBLE was mostly smaller gains or flat.

jt2594838 · 2026-09-16T07:23:54Z

  public VarianceAccumulator(TSDataType seriesDataType, VarianceType varianceType) {
    this.seriesDataType = seriesDataType;
+    this.doubleValueConverter =
+        TypeServices.NUMERIC_BATCH_READER_SERVICE


Use the native numeric batch reader for tree variance, retaining the existing recurrence callback and logical row order rather than changing the numerical algorithm. NumericMomentBatchTest covers moments/variance across tree, table and grouped implementations, including masked/null inputs. This candidate was retained after mixed-type and fixed-DOUBLE measurements; related candidates with measured regressions were restored.

Caideyipi · 2026-09-18T04:24:19Z

+                      value -> {
+                        throw new UnsupportedOperationException(
+                            String.format(
+                                "The type %s cannot be casted to int.", type.getTypeEnum()));


[P2] Preserve localized errors in the extracted type services

This branch replaces DataNodePipeMessages.PIPE_EXCEPTION_THE_TYPE_S_CANNOT_BE_CASTED_TO_INT_659069CC with a raw English string. In a -P with-zh-locale build, calling CustomizedReadableIntermediateResults.getInt() for a BOOLEAN intermediate result now emits The type BOOLEAN cannot be casted to int. instead of the existing Chinese message.

Please reuse the existing DataNodePipeMessages constants for these conversion errors. The long/float/double/string strategies below have the same regression. The extracted ROUND_TRANSFORMER_SERVICE, unsupportedSourceCastStrategy, and unsupportedTargetCastStrategy also replace DataNodeQueryMessages constants with English literals; please restore those localized messages as well.

jt2594838

Merged master at 9be80ea and resolved the OPC UA migration compatibility issues in 5fdbfc7. The following inline notes cover the registry cleanup, type-service relocation, and regression-test relocation. Validation: 66 targeted tests passed; English and Chinese test-compile passed for all 52 modules excluding distribution; Spotless, Checkstyle, and git diff --check passed. Distribution packaging was not validated: the initial full-reactor command stalled while downloading a remote distribution ZIP, so compilation was rerun excluding that packaging module.

jt2594838 · 2026-09-21T04:30:42Z

@@ -157,7 +157,6 @@ public String getClassName() {
                  IOT_CONSENSUS_V2_ASYNC_CONNECTOR.getPipePluginName().toLowerCase(),
                  PIPE_CONSENSUS_ASYNC_CONNECTOR.getPipePluginName().toLowerCase(),
                  WEBSOCKET_CONNECTOR.getPipePluginName().toLowerCase(),
-                  OPC_UA_CONNECTOR.getPipePluginName().toLowerCase(),


Remove the stale OPC_UA_CONNECTOR and OPC_UA_SINK entries from BUILTIN_SINKS. Master moved OPC UA to library-pipe and removed those enum constants, but these two references remained, causing node-commons compilation to fail. Removing both entries also correctly classifies the separately registered OPC UA plugin as external. The compatibility names in PipeSinkConstant remain available for configuration and the single-thread policy. Both locale builds passed after this cleanup.

jt2594838 · 2026-09-21T04:30:42Z

+import java.util.function.Supplier;
+
+// Keep Milo-dependent type services in the external plugin so core can load without Milo.
+final class OpcUaTypeServices {


Relocate the four OPC UA TypeServices from datanode's TypeServices.Pipe into the external plugin, and update all four OpcUaNameSpace call sites to use this class. Master removed Milo from datanode's dependencies; retaining DateTime/NodeId/Identifiers references there prevented compilation. Keeping the services with the plugin preserves the existing conversions, service checks, and Pub/Sub type selection outside the row loop without reintroducing Milo into core. The java.util.Date conversion fix is retained. Both locale reactor builds and the targeted OPC UA metadata/conversion tests passed.

jt2594838 · 2026-09-21T04:30:43Z

+
+public class OpcUaTypeServicesTest {
+
+  @Test


Move the existing DATE regression from datanode's TypeServicesTest alongside the relocated OPC UA services. The same assertion still checks Milo's DateTime against the LocalDate at the system zone's start of day, guarding against reintroducing java.sql.Date.toInstant(), which throws UnsupportedOperationException. This keeps regression coverage while allowing datanode tests to compile without Milo. The relocated test passed, together with five OPC UA metadata tests and the remaining 60 targeted tests.

jt2594838 added 30 commits July 13, 2026 16:02

Add type services

d8aef23

remove switches

6f47103

remove switches

7414025

remove switches

bd99532

refactor calculateValueLength

e3ab985

refactor calculateCapacity

5e179c0

refactor calculateCapacity

f2925d0

refactor TabletExample

9312f56

refactor IoTDBDescriptor.getDefaultEncodingByType

6138d92

refactor estimateSingleValueArrayMemoryUsageInBytes

4000fe9

refactor estimateTsPrimitiveTypeValueMemoryUsageInBytes

9d76c8a

refactor parse

1a5ece5

fix compilation

308061a

refactor convertTsDataType2VariantType

1fa4125

refactor initResultTsBlock

16460a4

refactor getRowSkipPrefixNulls

f453368

refactor TwoSum

6af8fc2

refactor UDAFAvg

2a3c35f

refactor UDAFSum

cc63846

refactor encodeRecord

236b866

refactor fillMeasurementValueColumns

a4b417a

refactor copyValueList

88a6514

refactor transferTabletForPubSubModel

2bd4b6c

refactor PRIMITIVE_TYPE_VALUE_EXTRACTOR_SERVICE

253a4e0

refactor reorderValueListAndBitMap

308571b

refactor writeIntermediateToStream

3e250e4

refactor constructInsertTabletStatement

dfe6aec

refactor processColumn

706092b

refactor getColumnsBytes

83d027b

refactor addTimeValuePairToResult

46dfe11

jt2594838 commented Sep 16, 2026

View reviewed changes

jt2594838 added 2 commits September 16, 2026 15:34

Merge branch 'master' into remove_swtich_type

19d97dd

multiple refactors

d5f06e6

JackieTien97 approved these changes Sep 17, 2026

View reviewed changes

Caideyipi reviewed Sep 18, 2026

View reviewed changes

jt2594838 added 2 commits September 21, 2026 11:25

Merge remote-tracking branch 'origin/master' into remove_swtich_type

310ddaa

Fix OPC UA TypeService integration after master merge

5fdbfc7

jt2594838 commented Sep 21, 2026

View reviewed changes

jt2594838 merged commit a670bce into master Sep 21, 2026
39 of 40 checks passed

jt2594838 deleted the remove_swtich_type branch September 21, 2026 06:00

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jt2594838 commented Sep 9, 2026 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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What is changed

Performance measurements

Ordered rate accumulators

Aligned WAL writes

Validation

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jt2594838 commented Sep 9, 2026 •

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