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• • Re: [I] Fix remaining reported issues for arrays of map [datafusion-comet] via GitHub
• Re: [I] Add native support for CollectMetricsExec (df.observe) to preserve stage fusion [datafusion-comet] via GitHub
• Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
  • Re: [I] Release sqlparser-rs version `0.63.0` around 2026-08-31 [datafusion-sqlparser-rs] via GitHub
• Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
  • Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
  • Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
  • Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
  • Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
  • Re: [I] [Incompatibility] Document array_join null handling differences [datafusion-comet] via GitHub
• Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
  • Re: [I] [EPIC] Use blocked / chunked memory management in hash aggregation [datafusion] via GitHub
• [PR] Preserve single quote literal display [datafusion-sqlparser-rs] via GitHub
  • Re: [PR] Preserve single quote literal display [datafusion-sqlparser-rs] via GitHub
  • Re: [PR] Preserve single quote literal display [datafusion-sqlparser-rs] via GitHub
• [PR] perf: project cached batches by buffer selection, prune on collated strings [datafusion-comet] via GitHub
  • Re: [PR] perf: project cached batches by buffer selection, prune on collated strings [datafusion-comet] via GitHub
• [PR] Preserve numeric compound field access display [datafusion-sqlparser-rs] via GitHub
  • Re: [PR] Preserve numeric compound field access display [datafusion-sqlparser-rs] via GitHub
  • Re: [PR] Preserve numeric compound field access display [datafusion-sqlparser-rs] via GitHub
• Re: [I] PostgreSQL compatibility: `ln(-1.0::float8)` should error, not return NaN [datafusion] via GitHub
  • Re: [I] PostgreSQL compatibility: `ln(-1.0::float8)` should error, not return NaN [datafusion] via GitHub
  • Re: [I] PostgreSQL compatibility: `ln(-1.0::float8)` should error, not return NaN [datafusion] via GitHub
• Re: [PR] fix(spark): derive pmod's decimal result type from the declared arguments [datafusion] via GitHub
  • Re: [PR] fix(spark): derive pmod's decimal result type from the declared arguments [datafusion] via GitHub
  • Re: [PR] fix(spark): derive pmod's decimal result type from the declared arguments [datafusion] via GitHub
• Re: [I] PostgreSQL compatibility: `log(0.0::float8)` should error, not return `-inf` [datafusion] via GitHub
• Re: [I] Add spilling support for HashJoin [datafusion] via GitHub
  • Re: [I] Add spilling support for HashJoin [datafusion] via GitHub
• [I] Memory Limited Joins (Externalized / Spill) [datafusion] via GitHub
  • Re: [I] Memory Limited Joins (Externalized / Spill) [datafusion] via GitHub
  • Re: [I] Memory Limited Joins (Externalized / Spill) [datafusion] via GitHub
  • Re: [I] Memory Limited Joins (Externalized / Spill) [datafusion] via GitHub
  • Re: [I] Memory Limited Joins (Externalized / Spill) [datafusion] via GitHub
• Re: [PR] fix: log(0.0::float8) should error, not return -inf [datafusion] via GitHub
• Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
  • Re: [I] Supporting analytics over large amounts of pre‑partitioned data [datafusion] via GitHub
• Re: [PR] fix sqrt(-1.0::float8) should error, not return NaN [datafusion] via GitHub
• Re: [PR] fixing negative power to zero [datafusion] via GitHub
• Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
  • Re: [PR] feat: skip hash shuffle for date_bin/date_trunc on Range([timestamp]) [datafusion] via GitHub
• [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
  • Re: [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
  • Re: [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
  • Re: [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
  • Re: [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
  • Re: [PR] fix: prune row groups when file statistics collapse the predicate to a constant [datafusion] via GitHub
• Re: [PR] IN LIST: use runtime dispatch for `FixedSizeBinary` filter (reduce binary size) [datafusion] via GitHub
  • Re: [PR] IN LIST: use runtime dispatch for `FixedSizeBinary` filter (reduce binary size) [datafusion] via GitHub
  • Re: [PR] IN LIST: use runtime dispatch for `FixedSizeBinary` filter (reduce binary size) [datafusion] via GitHub
• [I] Native Azure store lets ambient AZURE_* environment variables override or corrupt explicit Hadoop auth config [datafusion-comet] via GitHub
  • Re: [I] Native Azure store lets ambient AZURE_* environment variables override or corrupt explicit Hadoop auth config [datafusion-comet] via GitHub
• [I] Iceberg native scan fails queries on tables whose column names are case-distinct to Java but not to Rust [datafusion-comet] via GitHub
  • Re: [I] Iceberg native scan fails queries on tables whose column names are case-distinct to Java but not to Rust [datafusion-comet] via GitHub
• [I] Iceberg native scan claims schemes it cannot execute; three scheme lists disagree [datafusion-comet] via GitHub
  • Re: [I] Iceberg native scan claims schemes it cannot execute; three scheme lists disagree [datafusion-comet] via GitHub
• [I] Regression: DataFusion 55 no longer prunes row groups for `col = <literal>` when statistics show the column is entirely NULL [datafusion] via GitHub
  • Re: [I] Regression: DataFusion 55 no longer prunes row groups for `col = <literal>` when statistics show the column is entirely NULL [datafusion] via GitHub
• Re: [I] `avg(decimal)` might lose precision and cause an overflow over return type [datafusion] via GitHub
• Re: [I] Avoid unnecessary repartitioning when joining against pre-partitioned relations [datafusion] via GitHub
• Re: [I] Destructure proto hooks for CASE and IN-list physical expressions [datafusion] via GitHub
• Re: [I] PROPOSAL Hash Join Spilling Proposal [datafusion] via GitHub
  • Re: [I] PROPOSAL Hash Join Spilling Proposal [datafusion] via GitHub
  • Re: [I] PROPOSAL Hash Join Spilling Proposal [datafusion] via GitHub
• [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
  • Re: [I] [EPIC] Spilling Hash Join — run any join in a bounded memory budget [datafusion] via GitHub
• Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
  • Re: [PR] Share per-chunk JoinLeftData across right partitions in NLJ memory-limited fallback [datafusion] via GitHub
• [PR] feat: use object store for history server persistence [datafusion-ballista] via GitHub
  • Re: [PR] feat: use object store for history server persistence [datafusion-ballista] via GitHub
  • Re: [PR] feat: use object store for history server persistence [datafusion-ballista] via GitHub
• Re: [I] Destructure proto hooks for the Arrow and Avro sources [datafusion] via GitHub
• Re: [I] percentile_cont is wrong for `Decimal32` with lower interpolation precision [datafusion] via GitHub
• Re: [I] `ScalarValue::iter_to_array` accepts mismatched type parameters [datafusion] via GitHub
• Re: [I] Ungrouped aggregation never charges accumulators' construction-time state to the memory pool [datafusion] via GitHub
• Re: [I] warning: linker stderr: ld: __eh_frame section too large [datafusion-ballista] via GitHub
• Re: [I] [EPIC] Enable Adaptive Query Execution (AQE) by default [datafusion-ballista] via GitHub
  • Re: [I] [EPIC] Enable Adaptive Query Execution (AQE) by default [datafusion-ballista] via GitHub
• Re: [I] Ballista 53.0.0 — Coordinator OOM Crash on TPCH SF100 [datafusion-ballista] via GitHub
  • Re: [I] Ballista 53.0.0 — Coordinator OOM Crash on TPCH SF100 [datafusion-ballista] via GitHub
• Re: [I] Update benchmark results in README [datafusion-ballista] via GitHub
  • Re: [I] Update benchmark results in README [datafusion-ballista] via GitHub
• Re: [I] Unable to use Ballista at scale (e.g. TPC-H @ 1TB) [datafusion-ballista] via GitHub
  • Re: [I] Unable to use Ballista at scale (e.g. TPC-H @ 1TB) [datafusion-ballista] via GitHub
• Re: [I] [EPIC] Adaptive Query Execution (AQE) [datafusion-ballista] via GitHub
  • Re: [I] [EPIC] Adaptive Query Execution (AQE) [datafusion-ballista] via GitHub
  • Re: [I] [EPIC] Adaptive Query Execution (AQE) [datafusion-ballista] via GitHub
• Re: [I] [EPIC] Shuffle file execs improvement [datafusion-ballista] via GitHub
  • Re: [I] [EPIC] Shuffle file execs improvement [datafusion-ballista] via GitHub
• Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
  • Re: [PR] Fix CASE evaluation for custom column expressions [datafusion] via GitHub
• Re: [I] Avoid casting unreachable child values in nested List casts [datafusion] via GitHub
• Re: [PR] fix: Address avg return type overflow for decimals [datafusion] via GitHub
  • Re: [PR] fix: Address avg return type overflow for decimals [datafusion] via GitHub
  • Re: [PR] fix: Address avg return type overflow for decimals [datafusion] via GitHub
  • Re: [PR] fix: Address avg return type overflow for decimals [datafusion] via GitHub
• Re: [I] Validate BALLISTA_PROTOCOL_VERSION for clients, not just executors [datafusion-ballista] via GitHub
• Re: [PR] feat: scheduler REST & GRPC returns ballista version headers [datafusion-ballista] via GitHub
  • Re: [PR] feat: scheduler REST & GRPC returns ballista version headers [datafusion-ballista] via GitHub
• [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
  • Re: [PR] fix: prevent memory leak after failed Arrow vector import [datafusion-comet] via GitHub
• Re: [I] Vendored datafusion.proto sync check silently passes without checking datafusion.proto [datafusion-ballista] via GitHub
• Re: [I] Python client silently forces the static planner (pinned to ballista 54.0.0 defaults) [datafusion-ballista] via GitHub
  • Re: [I] Python client silently forces the static planner (pinned to ballista 54.0.0 defaults) [datafusion-ballista] via GitHub
  • Re: [I] Python client silently forces the static planner (pinned to ballista 54.0.0 defaults) [datafusion-ballista] via GitHub
• [PR] fix(core): stop forwarding BallistaConfig defaults to the scheduler [datafusion-ballista] via GitHub
  • Re: [PR] fix(core): stop forwarding BallistaConfig defaults to the scheduler [datafusion-ballista] via GitHub
• Re: [PR] feat: Implement map-to-string casting [datafusion-comet] via GitHub
  • Re: [PR] feat: Implement map-to-string casting [datafusion-comet] via GitHub
  • Re: [PR] feat: Implement map-to-string casting [datafusion-comet] via GitHub
  • Re: [PR] feat: Implement map-to-string casting [datafusion-comet] via GitHub
• Re: [I] perf: bypass Arrow FFI for broadcast exchange reads [datafusion-comet] via GitHub
• [PR] perf: add direct native reads for broadcast exchange [datafusion-comet] via GitHub
  • Re: [PR] perf: add direct native reads for broadcast exchange [datafusion-comet] via GitHub
• [PR] fix: align Spark collect aggregate element nullability [datafusion] via GitHub
  • Re: [PR] fix: align Spark collect aggregate element nullability [datafusion] via GitHub
  • Re: [PR] fix: align Spark collect aggregate element nullability [datafusion] via GitHub
  • Re: [PR] fix: align Spark collect aggregate element nullability [datafusion] via GitHub

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