[sjvanrossum]

Optimizes Row construction, field verification, RowWithGetters field caching, and Row utility methods by eliminating intermediate object allocations (RowPosition, FieldAccessDescriptor, RowFieldMatcher, CapturingRowCases, TreeMap, and Stream pipelines) on hot paths.

Previously, Row.Builder.build() wrapped its positional List<Object> into a FieldOverrides tree (allocating a FieldAccessNode, a FieldAccessDescriptor per field, and a RowPosition per field/nested element) and traversed the schema through RowFieldMatcher + CapturingRowCases. Similarly, SchemaVerification.verifyFieldValue constructed a single-field Schema, FieldOverrides, CapturingRowCases, RowFieldMatcher, and RowPosition on every single field verification call. Replaced RowFieldMatcher and CapturingRowCases with direct static RowUtils.captureRow(Schema, List<Object>) and RowUtils.captureValue(FieldType, Object, String) methods, and simplified FieldOverrides (Row.FieldValueBuilder) to apply overrides directly via captureValue.

Replaced the TreeMap<Integer, Object> (and per-lookup boxed Integer key + anonymous Function allocation in computeIfAbsent) in RowWithGetters with a flat Object[] indexed by fieldIdx (using a NULL_VALUE sentinel to cache null results without re-invoking getters). Extended RowWithGetters.cacheFieldType to also cache ROW and LOGICAL_TYPE fields in addition to MAP, ARRAY, and ITERABLE, avoiding repeated nested RowWithGetters / logical type conversions when a field is accessed multiple times.

Pre-sized Row.Builder's internal ArrayList to schema.getFieldCount() and used Collections.addAll in addValues(Object...). Replaced IntStream/Stream pipelines and name-based lookups with indexed loops in Row.getBaseValues(), Row.sorted(), Row.toSnakeCase(), Row.toCamelCase(), Row.nullRow(), and SchemaUtils.toPrettyRowString().

Added JMH benchmarks covering flat and complex Row construction, Row equals/hashCode, repeated RowWithGetters field reads, and RowCoder / SchemaCoder encoding and decoding.

Note

This PR stacks on top of #40789 and is part of a series of patches driving the following improvements:

Benchmark	Base (ops/us)	Patch series (ops/us)	vs base
buildFlatRow	1.070 ± 0.011	26.722 ± 0.174	24.97x (+2,397.4%)
buildComplexRow	0.860 ± 0.012	9.550 ± 0.195	11.10x (+1,010.5%)
complexRowEqualsAndHashCode	1.481 ± 0.036	12.391 ± 0.400	8.37x (+736.7%)
readFlatRowBoxedGetters	148.151 ± 2.005	501.611 ± 2.892	3.39x (+238.6%)
readFlatRowPrimitiveGetters	148.151 ± 2.005	503.336 ± 3.551	3.40x (+239.7%)
encodeFlatRow	7.987 ± 0.068	19.758 ± 0.280	2.47x (+147.4%)
decodeFlatRow	11.425 ± 0.351	12.524 ± 0.068	1.10x (+9.6%)
encodeComplexRow	8.217 ± 0.130	12.388 ± 0.538	1.51x (+50.8%)
decodeComplexRow	3.954 ± 0.095	4.178 ± 0.047	1.06x (+5.7%)
encodePojoViaSchemaCoder	4.932 ± 0.053	7.412 ± 0.159	1.50x (+50.3%)
decodePojoViaSchemaCoder	2.616 ± 0.030	3.755 ± 0.019	1.44x (+43.5%)
readRowWithGettersRepeatedly	27.326 ± 0.642	121.171 ± 1.810	4.43x (+343.4%)

[github-actions]

📋 Review Summary

This PR significantly optimizes Row construction, SchemaVerification.verifyFieldValue, RowWithGetters field caching, and Row/SchemaUtils helper methods by removing intermediate RowPosition, FieldAccessDescriptor, RowFieldMatcher, CapturingRowCases, TreeMap, and Stream allocations on hot paths. It also fixes several correctness issues uncovered during optimization, including Row.Equals.deepHashCode for logical types, RowWithGetters equals/hashCode contract consistency with RowWithStorage, nested Row schema validation, ByteBuffer slice/offset handling, and DATETIME-based logical type handling in SchemaCoderHelpers.

🔍 General Feedback

• Replacing RowFieldMatcher and CapturingRowCases with direct static RowUtils.captureRow and RowUtils.captureValue methods is much cleaner and eliminates substantial per-row and per-field allocation overhead.
• Replacing the TreeMap<Integer, Object> in RowWithGetters with a transient Object[] using a NULL_VALUE sentinel and extending caching to ROW and LOGICAL_TYPE fields is well-designed and avoids repeated wrapper/conversion work.
• The added unit tests and JMH benchmarks thoroughly cover the bug fixes and performance improvements.

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