[GLUTEN-7600][VL] Add monotonically_increasing_id function mapping#11674
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n0r0shi wants to merge 1 commit intoapache:mainfrom
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[GLUTEN-7600][VL] Add monotonically_increasing_id function mapping#11674n0r0shi wants to merge 1 commit intoapache:mainfrom
n0r0shi wants to merge 1 commit intoapache:mainfrom
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Adds `Sig[MonotonicallyIncreasingID]` to `ExpressionMappings.SCALAR_SIGS` so the function is offloaded to Velox instead of falling back to vanilla Spark. Also sets Velox's `expression.dedup_non_deterministic` to `false`. By default Velox deduplicates structurally identical non-deterministic expression trees, merging them into a single instance with shared state. This is incorrect for Spark semantics where each non-deterministic call has independent state — e.g. `SELECT monotonically_increasing_id(), monotonically_increasing_id()` must return [0,0],[1,1] (two independent counters), not [0,2],[1,3] (one shared counter). For seeded functions like `rand(42)`, disabling dedup is safe: each independent instance produces the same sequence from the same seed, matching Spark's behavior either way. Un-ignores and fixes the corresponding test in `ScalarFunctionsValidateSuite`. Closes apache#7628
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Summary
Sig[MonotonicallyIncreasingID]toExpressionMappings.SCALAR_SIGSso the function is offloaded to Velox instead of falling back to vanilla Spark.expression.dedup_non_deterministictofalseto match Spark semantics — Spark never deduplicates non-deterministic expressions, each call has independent state.ScalarFunctionsValidateSuite.Context
PR #10097 previously attempted this but was closed because of a result mismatch (#7628):
SELECT monotonically_increasing_id(), monotonically_increasing_id()returnedinstead of Spark's expected
The root cause was Velox's expression compiler deduplicating the two structurally identical calls into one shared counter instance.
Velox has since added the
expression.dedup_non_deterministicconfig (facebookincubator/velox#15008) to control this behavior. This PR sets it tofalsefor Gluten. This only affects non-deterministic expressions — deterministic expression deduplication is unchanged.Question for reviewers: Is setting
expression.dedup_non_deterministic = falseglobally the right approach? An alternative would be conditionally disabling it only when stateful expressions likemonotonically_increasing_idare detected in the plan, but we believe the global approach is correct since Spark semantics never deduplicate non-deterministic expressions.Closes #7628
Related issue: #7600