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• • 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
  • Re: [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
  • 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
  • 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
• [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [rebased from #22518] [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [rebased from #22518] [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [rebased from #22518] [datafusion] via GitHub
  • Re: [PR] feat(aggregate): cost-aware partial-aggregation skip (opt-in) [rebased from #22518] [datafusion] via GitHub
• [I] Release DataFusion `54.2.0` (minor/patch) Release [datafusion] via GitHub
  • Re: [I] Release DataFusion `54.2.0` (minor/patch) Release [datafusion] via GitHub
  • Re: [I] Release DataFusion `54.2.0` (minor/patch) Release [datafusion] via GitHub
• [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
  • Re: [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
  • Re: [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
  • Re: [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
  • Re: [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
  • Re: [PR] fix: do not treat concat as preserving lexicographical ordering [datafusion] via GitHub
• [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
  • Re: [PR] benchmarks: count simulated object store GET requests per query [datafusion] via GitHub
• Re: [I] [EPIC] Split Aggregation Logic into Dedicated Streams [datafusion] via GitHub
  • Re: [I] [EPIC] Split Aggregation Logic into Dedicated Streams [datafusion] via GitHub
  • Re: [I] [EPIC] Split Aggregation Logic into Dedicated Streams [datafusion] via GitHub
• Re: [PR] refactor: Use cast preimages for cast predicate rewrites [datafusion] via GitHub
• Re: [PR] fix: preserve aggregate filter pushdown order [datafusion] via GitHub
• [PR] feat: remove extra Rows from ReusableRows [datafusion] via GitHub
• Re: [PR] feat: Add Native Support for In-Memory Cache [datafusion-comet] via GitHub
  • Re: [PR] feat: Add Native Support for In-Memory Cache [datafusion-comet] via GitHub
• [I] Remove the buffering of an extra Rows in ReusableRows [datafusion] via GitHub
  • Re: [I] Remove the buffering of an extra Rows in ReusableRows [datafusion] via GitHub
• Re: [I] Expose Range Partitioning Across FFI Boundaries [datafusion] via GitHub
• [PR] fix: preserve global limit for multi-partition fetch [datafusion] via GitHub
• [I] LimitPushdown can mistake per-partition fetch for a global limit [datafusion] via GitHub
• Re: [I] Shrink residual Vec in split_vec_min_alloc to fix capacity-based memory accounting on long split_off chains [datafusion] via GitHub
  • Re: [I] Shrink residual Vec in split_vec_min_alloc to fix capacity-based memory accounting on long split_off chains [datafusion] via GitHub
  • Re: [I] Shrink residual Vec in split_vec_min_alloc to fix capacity-based memory accounting on long split_off chains [datafusion] via GitHub
• [I] ProjectExec does not keep sorting information for passthrough expression [datafusion] via GitHub
  • Re: [I] ProjectExec does not keep sorting information for passthrough expression [datafusion] via GitHub
• [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
  • Re: [PR] feat: allow configuring datafusion-cli history file location [datafusion] via GitHub
• [I] datafusion-cli: allow configuring the location of the interactive shell's history file [datafusion] via GitHub
• [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
  • Re: [PR] Experimental: parquet bounded streaming of large column chunks (companion to arrow-rs#10410) [datafusion] via GitHub
• [PR] refactor(proto): migrate SortExec and SortPreservingMergeExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate SortExec and SortPreservingMergeExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate SortExec and SortPreservingMergeExec serde [datafusion] via GitHub
• [I] `concat` should NOT be reported as preserve lex ordering - wrong output [datafusion] via GitHub
  • Re: [I] `concat` should NOT be reported as preserve lex ordering - wrong output [datafusion] via GitHub
  • Re: [I] `concat` should NOT be reported as preserve lex ordering - wrong output [datafusion] via GitHub
• [PR] refactor(proto): migrate RepartitionExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate RepartitionExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate RepartitionExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate RepartitionExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate RepartitionExec serde [datafusion] via GitHub
• Re: [I] Proto: migrate ParquetSource [datafusion] via GitHub
• Re: [I] Proto: migrate the simple file scans (CsvSource, JsonSource, ArrowSource, AvroSource) [datafusion] via GitHub
• [PR] refactor(proto): migrate GlobalLimitExec and LocalLimitExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate GlobalLimitExec and LocalLimitExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate GlobalLimitExec and LocalLimitExec serde [datafusion] via GitHub
  • Re: [PR] refactor(proto): migrate GlobalLimitExec and LocalLimitExec serde [datafusion] via GitHub
• [PR] docs: add Supermetal to known users [datafusion] via GitHub
  • Re: [PR] docs: add Supermetal to known users [datafusion] via GitHub
  • Re: [PR] docs: add Supermetal to known users [datafusion] via GitHub
  • Re: [PR] docs: add Supermetal to known users [datafusion] via GitHub
  • Re: [PR] docs: add Supermetal to known users [datafusion] via GitHub
• [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
  • Re: [PR] refactor(unparser): centralize aggregate-scope rendering in the SQL unparser [datafusion] via GitHub
• [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
  • Re: [PR] fix: avoid overflow in join cardinality estimation [datafusion] via GitHub
• [I] Join cardinality estimation can overflow row count multiplication [datafusion] via GitHub
  • Re: [I] Join cardinality estimation can overflow row count multiplication [datafusion] via GitHub

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