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feat(functions): map functions and spark.sql.mapKeyDedupPolicy - #245
Signatures and result rules are in krishiv-functions, implicit casts in the analyzer (keys and values meet separately; map_concat needs the same map type under ANSI; map_contains_key meets the key without string promotion).
Kernels in krishiv-kernels build maps over Arrow ListArray/MapArray/StructArray directly, compare keys with Spark equality and hash with the observable Murmur3. A null key raises NULL_MAP_KEY; a duplicate key raises DUPLICATED_MAP_KEY, or keeps the last value under spark.sql.mapKeyDedupPolicy=LAST_WIN.
spark.sql.mapKeyDedupPolicy is a new session config, honoured when folding and executing and carried to workers behind the new map_key_dedup_policy plan-codec feature (golden and reader-refusal test included).
New analysis-level tests pin CREATE_MAP_KEY_DIFF_TYPES, CREATE_MAP_VALUE_DIFF_TYPES and MAP_CONCAT_DIFF_TYPES.
Golden counts (listed failing statements)
Session golden ratchet: 12080 before, 12058 after (22 removed, 0 added); the fn-map category is gone (10 statements to 0).
Registry matrix: 448 map cases now analyzed; entries that remain need arrays, structs or intervals.
Not included
Lambda forms (map_filter, map_zip_with, transform_keys, transform_values), and element_at/try_element_at over maps. The empty map()/map_concat() forms and the INVALID_MAP_KEY_TYPE paths follow Spark's rules and are pinned by unit tests but have no recorded Spark run.
Verification
cargo xtask precheck passes except the dist-binary size budget, which compares against a baseline older than current main.
Add the nine scalar functions of Spark 4.2's map family: map,
map_concat, map_contains_key, map_keys, map_values, map_entries,
map_from_arrays, map_from_entries and str_to_map. The lambda forms
(map_filter, map_zip_with, transform_keys/values) stay out as
higher-order functions, as do element_at and try_element_at.
Typing follows the Spark 4.2 sources and the recorded 4.2 runs, with
signatures and result rules in krishiv-functions and implicit casts in
the analyzer (keys and values of map meet separately, map_concat needs
every map and the same type under ANSI, map_contains_key meets the key
without string promotion). The kernels in krishiv-kernels build maps
row by row over Arrow ListArray, MapArray and StructArray directly,
comparing keys with Spark's equality and hashing with the observable
Murmur3. A null key raises NULL_MAP_KEY and a duplicate key raises
DUPLICATED_MAP_KEY, or keeps the last value under
spark.sql.mapKeyDedupPolicy=LAST_WIN (new session config, honoured
when folding and executing, carried to workers behind a new
map_key_dedup_policy plan-codec feature).
The golden fn-map category goes from 10 failing statements to none,
and the registry matrix covers the 448 map cases. Unverified against
a Spark run: the empty map() and map_concat() forms and the
INVALID_MAP_KEY_TYPE paths, which follow the sources and are pinned
by unit tests.
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
…ype errors
Hash and list-range lookups in the map kernels no longer substitute
zero or an empty range; a missing entry is an internal error. Adds
analysis-level tests for CREATE_MAP_KEY_DIFF_TYPES,
CREATE_MAP_VALUE_DIFF_TYPES and MAP_CONCAT_DIFF_TYPES, and drops the
implemented str_to_map from the unsupported list in the crate notes.
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
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Walkthrough
This PR adds map kernels and scalar functions, registers map typing and coercion, and exposes map functions through the Python SQL API. It adds the spark.sql.mapKeyDedupPolicy setting and carries LAST_WIN through evaluation and plan encoding.
Changes: Map Functions and Deduplication Policy
Layer / File(s)
Summary
Deduplication policy and plan propagation crates/krishiv-common/src/config/*, crates/krishiv-exec/src/physical/mod.rs, crates/krishiv-exec/src/planner/eval/*, crates/krishiv-plan-codec/src/*, proto/krishiv/plan/v1/plan.proto, crates/krishiv-plan/src/analyzer/mod.rs, crates/krishiv-plan/src/analyzer/fold.rs, related tests
Adds the session-scoped MAP_KEY_DEDUP_POLICY setting, defaulting to EXCEPTION, and supports LAST_WIN. Evaluation environments and plan data carry the setting; the codec records it as the map_key_dedup_policy feature.
Map signatures and analyzer coercion crates/krishiv-functions/src/registry/*, crates/krishiv-functions/src/signature.rs, crates/krishiv-plan/src/analyzer/coerce.rs, crates/krishiv-plan/src/analyzer/exprs.rs, crates/krishiv-session/tests/map_type_errors.rs
Adds map function signatures and result rules. Analyzer coercion handles map keys and values, map_concat, map_contains_key, nested types, and untyped NULL; map type mismatches receive dedicated errors.
Adds Arrow implementations for map creation, concatenation, lookup, projections, and conversions. Key equality handles supported primitive and nested types. Duplicate keys raise an error by default or retain the last value with LAST_WIN.
Scalar binding and execution crates/krishiv-functions/src/scalar/*, crates/krishiv-functions/Cargo.toml
Adds bindings and execution for map constructors, concatenation, lookup, projections, and str_to_map. Column bindings now carry nullability, and map bindings receive the selected deduplication policy.
Public APIs and integration coverage crates/krishiv-functions/src/python_wrappers/table.rs, python/krishiv/sql/_generated_functions.*, python/tests/test_generated_functions.py, crates/krishiv-cli/src/sql.rs, crates/krishiv-session/tests/*, tests/spark-golden/known-failures*
Adds Python wrappers and stubs, CLI map rendering, and tests for map behavior and typing. Updates Spark known-failure lists to remove several map cases.
KrishivAI/krishiv-engine#244: Adds struct construction and field access used by map_from_entries and nested struct map keys and values.
KrishivAI/krishiv-engine#209: Adds array and map data types and nested coercion used by the map signatures, kernels, and analyzer.
KrishivAI/krishiv-engine#193: Adds the plan-codec feature mechanism used to register and encode map_key_dedup_policy.
Merge Risk: Moderate · previous review 274c5
Map support is mostly in place, but two kernel bugs can produce errors or wrong null rows for nested-struct values and map_from_entries inputs. The Python str_to_map wrapper also mishandles a lone key/value delimiter. Fix these before merging; the remaining findings are minor.
Security architecture risk: Moderate · up to 274c5
The policy propagation has explicit compatibility safeguards. However, crafted map keys can force quadratic duplicate-checking work, creating an availability risk when queries process untrusted inputs. The impact beyond the executing query depends on resource isolation and execution limits that were not established.
Retained concerns
Medium · security · inferred: The new deduplication index uses Spark's deterministic hash as its collision-group key and scans every previously retained candidate in that group. Supported array keys can have the same non-null elements in the same order but different null positions: hashing ignores those nulls, while positional equality distinguishes the keys. An input containing many such distinct keys therefore forces n(n−1)/2 candidate comparisons. The outer randomized HashMap and the EXCEPTION default do not prevent this because all entries have the same hash but are not duplicates. This introduces input-driven CPU amplification in map construction. Exhaustion of shared execution capacity is conditional on query admission and isolation controls that were not established.
Security review details
Security Blast Radius
inferred — The directly supported exposure is CPU amplification within an executing map-construction invocation, requiring control of processed keys and a query that invokes the function. Shared-worker or cross-tenant availability impact depends on deployment isolation and effective execution budgets; no credential, storage-authority, or tenant-identity escalation is established by this path.
Security Findings and Attack Paths
inferred — An input producer can place many distinct fixed-length array keys containing the same sequence of non-null values at different positions into one map_from_arrays row. Nulls leave the hash state unchanged, so every key enters the same candidate vector. Positional equality rejects each prior candidate, forcing quadratic comparisons before construction completes. This is a source-derived availability concern, not a measured service-wide denial-of-service result.
Trust Boundaries and Controls
observed — Duplicate-key handling remains a session-level semantic choice, not a grant of additional authority. At plan transport, explicit feature checks reject readers that cannot honor the selected LAST_WIN behavior.
Resilience and Maintainability Implications
observed — Deduplication state and assembly builders are invocation-owned. Assembly returns a MapArray only after appending entries and validating the completed Arrow structures; propagated assembly errors do not publish a partially built result. These controls contain construction state but do not bound collision-comparison work.
Hardening Proposals
proposed — Separate observable Spark hash compatibility from internal deduplication indexing. An internal collision-resistant index should encode nested structure and positional nulls, with a bounded-work fallback or query-budget checks for excessive collision groups. Randomizing only the existing Spark hash seed would not resolve null-placement collisions.
Pre-merge checks: 3 · 2
Failed checks: 2 warnings
Check name
Status
Explanation
Resolution
Description check
The description gives a strong summary, scope boundaries, test coverage, and verification result. It does not include the required Task/spec/ADRs section or the required Checklist, including dependenc…
Add the task, specification, and ADR references. Add the required checklist with each applicable item marked. Include explicit test commands and result lines, including dependency-budget and performance review details. Explain the dist-bina…
Docstring Coverage
Docstring coverage is 50.89% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 224 functions across 39 files. (7 skipped…
Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed checks: 3 passed
Check name
Status
Explanation
Title check
The title clearly identifies the two main changes: map functions and the Spark map-key deduplication configuration.
Linked Issues check
Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check
Check skipped because no linked issues were found for this pull request.
Full details: Description check
Explanation
The description gives a strong summary, scope boundaries, test coverage, and verification result. It does not include the required Task/spec/ADRs section or the required Checklist, including dependency and performance reviews. The Tests run section also lacks explicit command and result lines in the template format.
Resolution
Add the task, specification, and ADR references. Add the required checklist with each applicable item marked. Include explicit test commands and result lines, including dependency-budget and performance review details. Explain the dist-binary budget exception and its baseline justification in the relevant checklist section.
Full details: Docstring Coverage
Explanation
Docstring coverage is 50.89% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 224 functions across 39 files. (7 skipped: 7 unsupported.)
Resolution
Write docstrings for the functions missing them to satisfy the coverage threshold.
Finishing Touches: 💡 1
⚔️ Resolve merge conflicts: 💡
Resolve merge conflict in branch feat/functions-map-fn
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Actionable comments posted: 7
🪄 Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @crates/krishiv-functions/src/scalar/map.rs:
- Around line 345-353: Update the splitter closure in the map conversion flow to
return a reference to the cached Splitter instead of cloning it on cache hits;
construct and insert a Splitter only on a cache miss, then borrow it from the
cache. Preserve the separate caches so both delimiter references remain usable,
and remove Clone derives from Splitter and Compiled if they are no longer
needed.
Review comments at @crates/krishiv-kernels/src/map.rs:
- Around line 283-287: Update struct_equal to pair the struct columns by
position rather than retrieving them by field name, so duplicate names compare
the corresponding columns. Keep the existing keys_equal comparison and
missing-field behavior consistent with the positional column iteration.
- Around line 992-995: Update the null-element handling in the `MapFromEntries`
row loop to null only the current row: record `ordered.len()` before scanning
its entries, truncate `ordered` to that point if a null entry is found, append a
null marker and an empty `per_row` entry, then continue. Update
`from_entries_maps_struct_slices` to assert row 0 is null and row 1 is valid,
and remove `whole_null` if it has no remaining callers.
- Line 824: Update both offset construction sites that call m.value_offsets() so
they reuse and clone m’s existing OffsetBuffer instead of copying the offsets
into a new buffer; preserve the current offset values and behavior.
- Around line 385-391: Update the null-struct branch to append a typed null to
each field builder using its corresponding source column and the existing
append_value path, instead of downcasting field builders to NullBuilder. Add a
kernel test covering a null struct value inside a map and a list.
Review comments at @crates/krishiv-plan/src/analyzer/mod.rs:
- Line 133: Update ContextFingerprint::digest to include map_key_dedup_last_win
in its encoded fingerprint fields, so contexts with different map policies
produce different digests.
Review comments at @python/krishiv/sql/_generated_functions.py:
- Around line 1180-1181: Update the `str_to_map` wrapper generator so supplying
`keyValueDelim` without `pairDelim` inserts the default comma for `pairDelim`,
preserving the argument position passed to the registry; then regenerate the
wrapper rather than editing the generated file by hand.
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Return cached splitters by reference; compare struct keys by position; append null struct values through the typed path; share map offsets; null only the affected map_from_entries row; include map_key_dedup_last_win in the context digest; insert the default pair delimiter when only keyValueDelim is given.
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
Merging this PR will degrade performance by 27.16%
1 warning, 1 note
⚠️9 benchmarks are dominated by system calls
System calls cannot be simulated consistently and are left out of the measure. The reported value understates the real cost. Switch to the Walltime instrument to measure them.
ExprEnv field 5 went to main's legacy_statistical_aggregate, so
map_key_dedup_last_win moves to field 6 (the pb.rs is regenerated and the
map_key_dedup_policy golden re-blessed; it was never on main). The scalar
family list gains url next to map. The Python wrappers are regenerated, and
the map functions' PySpark 4.2.0 signatures go into
python/tests/_pyspark_signatures.py (the wheel import tests failed without
them).
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
… with main
map() now resolves, so the parse_url and try_parse_url cases over a map
argument pass and leave the manifest; schema_of_csv over a map now reports
NON_FOLDABLE_INPUT (Spark: UNEXPECTED_INPUT_TYPE) and stays listed.
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
BindArg::Column takes main's field name (ty); the map and struct
families both bind; the map_key_dedup_policy and struct_field codec
cases sit side by side. The registry-matrix manifest, the Python
wrappers, the golden ratchet and the datetime calendar tally are
regenerated for map and named_struct both running.
Signed-off-by: gopal tathe <44522021+techgopal@users.noreply.github.com>
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Summary
The map function family.
Functions added:
map,map_concat,map_contains_key,map_keys,map_values,map_entries,map_from_arrays,map_from_entries,str_to_map.krishiv-functions, implicit casts in the analyzer (keys and values meet separately;map_concatneeds the same map type under ANSI;map_contains_keymeets the key without string promotion).krishiv-kernelsbuild maps over ArrowListArray/MapArray/StructArraydirectly, compare keys with Spark equality and hash with the observable Murmur3. A null key raisesNULL_MAP_KEY; a duplicate key raisesDUPLICATED_MAP_KEY, or keeps the last value underspark.sql.mapKeyDedupPolicy=LAST_WIN.spark.sql.mapKeyDedupPolicyis a new session config, honoured when folding and executing and carried to workers behind the newmap_key_dedup_policyplan-codec feature (golden and reader-refusal test included).CREATE_MAP_KEY_DIFF_TYPES,CREATE_MAP_VALUE_DIFF_TYPESandMAP_CONCAT_DIFF_TYPES.Golden counts (listed failing statements)
fn-mapcategory is gone (10 statements to 0).Not included
Lambda forms (
map_filter,map_zip_with,transform_keys,transform_values), andelement_at/try_element_atover maps. The emptymap()/map_concat()forms and theINVALID_MAP_KEY_TYPEpaths follow Spark's rules and are pinned by unit tests but have no recorded Spark run.Verification
cargo xtask precheckpasses except the dist-binary size budget, which compares against a baseline older than current main.