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• • Re: [PR] feat: serialize ASOF join plans [datafusion] via GitHub
• [PR] feat: add ASOF joins to DataFrame API [datafusion] via GitHub
  • Re: [PR] feat: add ASOF joins to DataFrame API [datafusion] via GitHub
  • Re: [PR] feat: add ASOF joins to DataFrame API [datafusion] via GitHub
• [PR] feat: support ASOF JOIN SQL [datafusion] via GitHub
  • Re: [PR] feat: support ASOF JOIN SQL [datafusion] via GitHub
  • Re: [PR] feat: support ASOF JOIN SQL [datafusion] via GitHub
• [PR] feat: add ASOF join logical semantics [datafusion] via GitHub
  • Re: [PR] feat: add ASOF join logical semantics [datafusion] via GitHub
  • Re: [PR] feat: add ASOF join logical semantics [datafusion] via GitHub
• [PR] feat: add ASOF join physical operator [datafusion] via GitHub
  • Re: [PR] feat: add ASOF join physical operator [datafusion] via GitHub
• [PR] chore(deps): bump tokio-stream from 0.1.18 to 0.1.19 in /python [datafusion-ballista] via GitHub
  • Re: [PR] chore(deps): bump tokio-stream from 0.1.18 to 0.1.19 in /python [datafusion-ballista] via GitHub
• [PR] chore(deps): bump tokio-stream from 0.1.18 to 0.1.19 [datafusion-ballista] via GitHub
  • Re: [PR] chore(deps): bump tokio-stream from 0.1.18 to 0.1.19 [datafusion-ballista] via GitHub
• [PR] chore(deps): bump arrow from 58.3.0 to 58.4.0 in /python [datafusion-ballista] via GitHub
• [PR] chore(deps): bump arrow-flight from 58.3.0 to 58.4.0 in /python [datafusion-ballista] via GitHub
• [PR] chore(deps): bump arrow from 58.3.0 to 58.4.0 [datafusion-ballista] via GitHub
  • [PR] chore(deps): bump arrow from 58.3.0 to 58.4.0 [datafusion-ballista] via GitHub
• [PR] chore(deps): bump arrow-flight from 58.3.0 to 58.4.0 [datafusion-ballista] via GitHub
• [PR] chore(ci): bump taiki-e/install-action from 2.84.0 to 2.84.1 [datafusion-ballista] via GitHub
  • Re: [PR] chore(ci): bump taiki-e/install-action from 2.84.0 to 2.84.1 [datafusion-ballista] via GitHub
  • Re: [PR] chore(ci): bump taiki-e/install-action from 2.84.0 to 2.84.1 [datafusion-ballista] via GitHub
• [PR] test: cover ArrayExists three-valued logic config [datafusion-comet] via GitHub
  • Re: [PR] test: cover ArrayExists three-valued logic config [datafusion-comet] via GitHub
  • Re: [PR] test: cover ArrayExists three-valued logic config [datafusion-comet] via GitHub
• Re: [PR] 2PC and staging output [datafusion-comet] via GitHub
• Re: [PR] fix(spark) CTAS with UNION in Spark 4.x native writer [datafusion-comet] via GitHub
• Re: [PR] feat: support InSubquery and Exists in Projection expressions [datafusion] via GitHub
• Re: [PR] fix: translate SIMILAR TO pattern to PostgreSQL-compatible regex [datafusion] via GitHub
• [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
  • Re: [PR] perf(functions-aggregate): optimize sliding window MIN/MAX using monotonic deques (#23826) [datafusion] via GitHub
• [I] Optimize sliding window MIN/MAX aggregations using monotonic deques [datafusion] via GitHub
  • Re: [I] Optimize sliding window MIN/MAX aggregations using monotonic deques [datafusion] via GitHub
  • Re: [I] Optimize sliding window MIN/MAX aggregations using monotonic deques [datafusion] via GitHub
• Re: [PR] feat: add BuildHasher variants for hash_utils [datafusion] via GitHub
  • Re: [PR] feat: add BuildHasher variants for hash_utils [datafusion] via GitHub
• [PR] refactor(proto): migrate AsyncFuncExec to self-serializing proto [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate AsyncFuncExec to self-serializing proto [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate AsyncFuncExec to self-serializing proto [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate AsyncFuncExec to self-serializing proto [datafusion] via GitHub
• [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) (DRAFT) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) [datafusion] via GitHub
  • Re: [PR] feat(optimizer): logical rewrite Filter(row_number() = 1) over PARTITION BY → Aggregate(FIRST_VALUE(... ORDER BY)) [datafusion] via GitHub
• Re: [I] FIRST/LAST returns wrong result with `PartialMerge` [datafusion-comet] via GitHub
• [I] datafusion-proto: logical-plan serialization overflows the stack in debug builds [datafusion] via GitHub
  • Re: [I] datafusion-proto: logical-plan serialization overflows the stack in debug builds [datafusion] via GitHub
  • Re: [I] datafusion-proto: logical-plan serialization overflows the stack in debug builds [datafusion] via GitHub
• Re: [PR] feat: Add support for `explode_outer` function for arrays [datafusion] via GitHub
  • Re: [PR] feat: Add support for `explode_outer` function for arrays [datafusion] via GitHub
• [PR] Preimage date trunc [datafusion] via GitHub
  • Re: [PR] Preimage date trunc [datafusion] via GitHub
  • Re: [PR] Preimage date trunc [datafusion] via GitHub
  • Re: [PR] Preimage date trunc [datafusion] via GitHub
  • Re: [PR] Support Preimage for `date_trunc` [datafusion] via GitHub
  • Re: [PR] Support Preimage for `date_trunc` [datafusion] via GitHub
  • Re: [PR] Support Preimage for `date_trunc` [datafusion] via GitHub
• [I] Incorrect result in `DataFusion 54.0.0 version: SELECT DISTINCT host FROM t ORDER BY host LIMIT k [datafusion] via GitHub
  • Re: [I] Incorrect result in DataFusion 53.0.0 version: `SELECT DISTINCT host FROM t ORDER BY host LIMIT k` [datafusion] via GitHub
  • Re: [I] Incorrect result in DataFusion 53.0.0 version: `SELECT DISTINCT host FROM t ORDER BY host LIMIT k` [datafusion] via GitHub
• Re: [I] Perf: Streaming Aggregation should not be chosen unconditionally when the input is sorted [datafusion] via GitHub
• [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
  • Re: [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
  • Re: [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
  • Re: [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
  • Re: [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
  • Re: [PR] test: add functional_dependencies.slt covering functional dependency driven optimizations [datafusion] via GitHub
• [I] Incorrect results: GROUP BY returns two rows for the NULL group with a nullable UNIQUE constraint [datafusion] via GitHub
  • Re: [I] Incorrect results: GROUP BY returns two rows for the NULL group with a nullable UNIQUE constraint [datafusion] via GitHub
  • Re: [I] Incorrect results: GROUP BY returns two rows for the NULL group with a nullable UNIQUE constraint [datafusion] via GitHub
  • Re: [I] Incorrect results: GROUP BY returns two rows for the NULL group with a nullable UNIQUE constraint [datafusion] via GitHub
• [I] Incorrect results: GROUP BY column dropped based on a nullable UNIQUE constraint [datafusion] via GitHub
  • Re: [I] Incorrect results: GROUP BY column dropped based on a nullable UNIQUE constraint [datafusion] via GitHub
• [I] Incorrect results: ORDER BY drops a sort key based on a nullable UNIQUE constraint [datafusion] via GitHub
  • Re: [I] Incorrect results: ORDER BY drops a sort key based on a nullable UNIQUE constraint [datafusion] via GitHub
• [I] store partitioning in dynamic filters [datafusion] via GitHub
  • Re: [I] store partitioning in dynamic filters [datafusion] via GitHub
  • Re: [I] store partitioning in dynamic filters [datafusion] via GitHub
• Re: [PR] Add ObjectStore-backed TempFileFactor / spill example [datafusion] via GitHub
• Re: [I] Flaky CI: TPC-H SF10 job intermittently fails with "No space left on device" [datafusion-ballista] via GitHub
• [I] AQE: a replan that reassigns stage ids orphans the sibling leaf stage, and its task completion errors out [datafusion-ballista] via GitHub
• [PR] fix(scheduler): reclaim intermediate shuffle data under AQE [datafusion-ballista] via GitHub
• [PR] Add an example of an in-process model of distributed execution [datafusion] via GitHub
  • Re: [PR] Add an example of an in-process model of distributed execution [datafusion] via GitHub
  • Re: [PR] Add an example of an in-process model of distributed execution [datafusion] via GitHub
• [PR] feat(functions-aggregate): make approx_distinct HLL precision configurable [datafusion] via GitHub
  • Re: [PR] feat(functions-aggregate): make approx_distinct HLL precision configurable [datafusion] via GitHub
• [I] approx_distinct: make HLL register precision configurable [datafusion] via GitHub
• [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
  • Re: [I] make dynamic filters in `ExecutionPlan` nodes discoverable [datafusion] via GitHub
• [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
  • Re: [PR] fix: reject nested aggregate functions (e.g. `sum(sum(x))`) during logical planning [datafusion] via GitHub
• [PR] test(tpcds): bump TPC-DS test data to scale factor 10 [datafusion-ballista] via GitHub
  • Re: [PR] test(tpcds): bump TPC-DS test data to scale factor 10 [datafusion-ballista] via GitHub
  • Re: [PR] test(tpcds): bump TPC-DS test data to scale factor 10 [datafusion-ballista] via GitHub
• Re: [PR] Test performance of `BatchCoalescer::push_batch_with_filter` [datafusion] via GitHub
• [I] CI: TPC-H SF10 failure artifact is missing executor.log [datafusion-ballista] via GitHub
• Re: [I] AQE: immediate intermediate-shuffle reclaim on job success is a no-op under the adaptive planner [datafusion-ballista] via GitHub
• [I] Nested aggregate functions (e.g. `sum(sum(x))`) are accepted at logical planning and fail at physical planning with an unhelpful error [datafusion] via GitHub
  • Re: [I] Nested aggregate functions (e.g. `sum(sum(x))`) are accepted at logical planning and fail at physical planning with an unhelpful error [datafusion] via GitHub
• Re: [I] [native_datafusion] Add support for reading row index metadata columns [datafusion-comet] via GitHub
• Re: [PR] chore: use DF `array_repeat` and `array_compact` [datafusion-comet] via GitHub
• [I] Consider moving to_hex's Arrow integer type dispatch into datafusion-common [datafusion] via GitHub
• [I] Avoid per-row String allocation when hex-encoding digest output (md5, sha1, sha2) [datafusion] via GitHub
  • Re: [I] Avoid per-row String allocation when hex-encoding digest output (md5, sha1, sha2) [datafusion] via GitHub
  • Re: [I] Avoid per-row String allocation when hex-encoding digest output (md5, sha1, sha2) [datafusion] via GitHub
  • Re: [I] Avoid per-row String allocation when hex-encoding digest output (md5, sha1, sha2) [datafusion] via GitHub
• [PR] fix: exclude precision-losing integer-to-float conversions from CastExpr::check_bigger_cast (#23808) [datafusion] via GitHub
  • Re: [PR] fix: exclude precision-losing integer-to-float conversions from CastExpr::check_bigger_cast (#23808) [datafusion] via GitHub
  • Re: [PR] fix: exclude precision-losing integer-to-float conversions from CastExpr::check_bigger_cast (#23808) [datafusion] via GitHub
• [I] Fix precision loss in CastExpr::check_bigger_cast for integer-to-float conversions [datafusion] via GitHub
• Re: [PR] chore: fallback to Spark if legacy sql configurations are set [datafusion-comet] via GitHub
  • Re: [PR] chore: fallback to Spark if legacy sql configurations are set [datafusion-comet] via GitHub
• [I] Missing Redshift constructs [datafusion-sqlparser-rs] via GitHub
• Re: [I] bug: array/map kernels crash on non-null child field via CometLocalTableScanExec [datafusion-comet] via GitHub
• Re: [PR] fix: widen local table scan child nullability to match native kernels [datafusion-comet] via GitHub
• [PR] Generate the config reference documentation from the config registry [datafusion-ballista] via GitHub
  • Re: [PR] Generate the config reference documentation from the config registry [datafusion-ballista] via GitHub
  • Re: [PR] Generate the config reference documentation from the config registry [datafusion-ballista] via GitHub
• [I] Generate the config reference documentation from the config registry [datafusion-ballista] via GitHub
  • Re: [I] Generate the config reference documentation from the config registry [datafusion-ballista] via GitHub
• [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
  • Re: [I] TPC-H q18 hangs with 16 executors x 8 cores in EKS [datafusion-ballista] via GitHub
• Re: [I] High HashJoin probe latency under high fanout and key skew (Partitioned mode) [datafusion] via GitHub
  • Re: [I] High HashJoin probe latency under high fanout and key skew (Partitioned mode) [datafusion] via GitHub
• Re: [PR] Prune unread nested parquet leaves when a projected column is cast to a narrower type (nested schema pruning) [datafusion] via GitHub
• Re: [PR] feat: prune nested Parquet leaves when the projected schema narrows a nested column [datafusion] via GitHub
  • Re: [PR] feat: prune nested Parquet leaves when the projected schema narrows a nested column [datafusion] via GitHub
• [PR] Debug why sort ordering get messed up [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))` opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))` opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
  • Re: [PR] Allow expression to report whether they keep the same ordering of the input (`a.cmp(b) == f(a).cmp(f(b))`) opening up for more optimization [datafusion] via GitHub
• [PR] feat(core): report the actual sort shuffle spill trigger in logs [datafusion-ballista] via GitHub
  • Re: [PR] feat(core): report the actual sort shuffle spill trigger in logs [datafusion-ballista] via GitHub
  • Re: [PR] feat(core): report the actual sort shuffle spill trigger in logs [datafusion-ballista] via GitHub
• Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [datafusion] via GitHub

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