perf: multi-field object inline array storage (2-8 fields)#688
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He-Pin wants to merge 2 commits intodatabricks:masterfrom
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perf: multi-field object inline array storage (2-8 fields)#688He-Pin wants to merge 2 commits intodatabricks:masterfrom
He-Pin wants to merge 2 commits intodatabricks:masterfrom
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For objects with exactly one field (common in patterns like `{ n: X }`),
store the field key and member inline in Val.Obj instead of allocating a
LinkedHashMap. The LinkedHashMap is lazily constructed only when needed
(e.g., key iteration via getAllKeys).
Key changes:
- Val.Obj: added singleFieldKey/singleFieldMember constructor params
- getValue0: lazily constructs LinkedHashMap from inline storage
- valueRaw: single-field fast path with String.equals instead of HashMap.get
- hasKeys/containsKey: fast paths to avoid forcing LinkedHashMap materialization
- visitMemberList: lazy builder allocation, only for 2+ field objects
Upstream: jit branch d284ecf (single-field object avoid LinkedHashMap)
Three-tier object storage: 1 field uses singleKey/singleMember, 2-8 fields use flat parallel arrays (inlineFieldKeys/inlineFieldMembers), 9+ fields use LinkedHashMap. This eliminates LinkedHashMap allocation for the vast majority of Jsonnet objects which have fewer than 9 fields. All fast paths updated: getValue0, hasKeys, containsKey, containsVisibleKey, allKeyNames, visibleKeyNames, valueRaw. Field tracking logic extracted into trackField() helper to avoid code duplication between the two Member.Field case branches. JMH: bench.02 -17.9%, realistic2 -2.7%, bench.04 -5.5% Native: realistic2 -13.5% (1.89x faster than jrsonnet) Upstream: jit branch commit 13e6ff3
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Motivation
Val.Obj currently always allocates a LinkedHashMap for fields, even for small objects with 2-8 fields. In Jsonnet programs, most objects are small (config entries, function returns). The LinkedHashMap overhead dominates allocation in object-heavy workloads.
Key Design Decision
Store object fields in flat inline arrays when the field count is ≤8: parallel arrays for keys, values, and visibility flags. This avoids LinkedHashMap allocation, hashing, and entry boxing while preserving O(1) field lookup via linear scan (fast for ≤8 elements due to cache locality).
Modification
Benchmark Results
JMH (JVM, 3 iterations warmup + 3 measurement)
Analysis
The bench.02 improvement (-25.0%) is the strongest single-PR gain on this benchmark, because bench.02 creates many small objects repeatedly. The tight error bars confirm this is a real structural improvement rather than JIT noise. This builds on the single-field optimization in #687 to cover the full small-object spectrum.
References
13e6ff39Result
All 46 tests pass. All benchmarks strongly positive, no regressions.