Copilot commented on code in PR #25580: URL: https://github.com/apache/datafusion/pull/25580#discussion_r4076672824
########## datafusion/expr/src/logical_plan/materialized_cte.rs: ########## @@ -0,0 +1,186 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Logical nodes for `WITH x AS MATERIALIZED (...)`. +//! +//! A materialized CTE is planned as one [`MaterializedCte`] node, which owns the +//! CTE body and the rest of the query (the "continuation"), and one +//! [`MaterializedCteScan`] leaf for each reference to the CTE inside the +//! continuation. The body is therefore optimized and executed once, and the +//! scans read its buffered output. +//! +//! The scans are leaves, so filters and projections of one reference are not +//! pushed into the shared body. This is the same optimization fence that +//! PostgreSQL applies to `MATERIALIZED` CTEs. + +use std::cmp::Ordering; +use std::fmt; +use std::hash::Hash; +use std::sync::atomic::{AtomicU64, Ordering as AtomicOrdering}; + +use datafusion_common::{DFSchemaRef, Result, assert_eq_or_internal_err}; + +use crate::{Expr, LogicalPlan, UserDefinedLogicalNodeCore}; + +/// Identifies one materialized CTE and binds its scans to it. +/// +/// CTE names are not unique (two sibling subqueries can each declare `WITH t`), +/// so the planner allocates a process-unique id. +#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)] +pub struct MaterializedCteId(u64); + +impl MaterializedCteId { + /// Allocate a new unique id. + pub fn next() -> Self { + static NEXT: AtomicU64 = AtomicU64::new(0); + Self(NEXT.fetch_add(1, AtomicOrdering::Relaxed)) + } + + /// The numeric value of this id. + pub fn as_u64(self) -> u64 { + self.0 + } +} + +impl fmt::Display for MaterializedCteId { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + write!(f, "{}", self.0) + } +} + +/// Computes `cte` once and evaluates `continuation`, in which every +/// [`MaterializedCteScan`] with the same `id` reads the buffered output of +/// `cte`. The output of this node is the output of `continuation`. +#[derive(Debug, Clone, PartialEq, Eq, Hash)] +pub struct MaterializedCte { + pub id: MaterializedCteId, + pub name: String, + pub cte: LogicalPlan, + pub continuation: LogicalPlan, +} + +impl PartialOrd for MaterializedCte { + fn partial_cmp(&self, other: &Self) -> Option<Ordering> { + match self.id.cmp(&other.id) { + Ordering::Equal => self.name.partial_cmp(&other.name), + ord => Some(ord), + } Review Comment: `UserDefinedLogicalNode::dyn_ord` requires `Some(Equal)` iff `dyn_eq` is true, but this comparison ignores `cte` and `continuation`. Two nodes retaining the same id/name after an optimizer rewrites a child therefore compare equal even though derived `PartialEq` says they differ, which can make logical-plan ordering/equality-based rewrites misidentify plans. Preserve the cheap id/name ordering but return `None` when those keys match and the full nodes differ. This issue also appears on line 145 of the same file. ########## datafusion/physical-plan/src/materialized_cte.rs: ########## @@ -0,0 +1,606 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Execution plans for `WITH x AS MATERIALIZED (...)`. +//! +//! [`MaterializedCteExec`] owns the CTE body and the continuation (the rest of +//! the query). Every [`MaterializedCteScanExec`] in the continuation shares one +//! [`MaterializedCteBuffer`] with it. The first consumer to execute runs every +//! partition of the body to completion and buffers the output; every scan then +//! replays that buffer. +//! +//! The body is fully materialized before any scan yields a row. This is a +//! pipeline break, but it cannot deadlock when two consumers of the same CTE +//! are read at different rates (for example the build and probe side of one +//! hash join), which a bounded fan-out channel can. +//! +//! Buffered batches are accounted in the memory pool. When a reservation +//! fails, the rest of that partition is written to a spill file, and the scans +//! read the in-memory prefix and then the spill file, so row order within a +//! partition is kept. + +use std::fmt; +use std::sync::Arc; + +use arrow::datatypes::SchemaRef; +use arrow::record_batch::RecordBatch; +use datafusion_common::config::ConfigOptions; +use datafusion_common::tree_node::TreeNodeRecursion; +use datafusion_common::{Result, Statistics, internal_err}; +use datafusion_common_runtime::JoinSet; +use datafusion_execution::memory_pool::{MemoryConsumer, MemoryReservation}; +use datafusion_execution::{SendableRecordBatchStream, SpillFile, TaskContext}; +use datafusion_physical_expr::{EquivalenceProperties, Partitioning, PhysicalExpr}; +use futures::{StreamExt, TryStreamExt}; +use parking_lot::Mutex; + +use crate::coop::cooperative; +use crate::execution_plan::{ + Boundedness, CardinalityEffect, EmissionType, ExecutionPlan, ExecutionPlanProperties, + PlanProperties, SchedulingType, +}; +use crate::filter_pushdown::{ + ChildFilterDescription, ChildPushdownResult, FilterDescription, FilterPushdownPhase, + FilterPushdownPropagation, +}; +use crate::joins::utils::{OnceAsync, OnceFut}; +use crate::metrics::{ + BaselineMetrics, ExecutionPlanMetricsSet, MetricBuilder, MetricsSet, SpillMetrics, +}; +use crate::spill::spill_manager::SpillManager; +use crate::statistics::{ChildStats, StatisticsArgs}; +use crate::stream::RecordBatchStreamAdapter; +use crate::{ + ChildrenPropertiesMode, DisplayAs, DisplayFormatType, ReplaceChildrenOptions, +}; + +/// The buffered output of one body partition: an in-memory prefix followed by +/// an optional spill file with the remaining batches. +struct BufferedPartition { + batches: Vec<RecordBatch>, + spill_file: Option<Arc<dyn SpillFile>>, + /// Released when the buffer is dropped. + _reservation: MemoryReservation, +} + +/// The materialized output of a CTE body. +struct MaterializedOutput { + partitions: Vec<BufferedPartition>, + spill_manager: SpillManager, +} + +/// State shared by one [`MaterializedCteExec`] and all its +/// [`MaterializedCteScanExec`]s. +pub struct MaterializedCteBuffer { + id: u64, + name: String, + /// The body to run. [`MaterializedCteExec`] updates it every time it is + /// rebuilt (for example by a physical optimizer rule), so it is the body of + /// the final plan. A scan can run the body before the owning + /// `MaterializedCteExec` executes, for example from a scalar subquery. + body: Mutex<Option<Arc<dyn ExecutionPlan>>>, + output: Mutex<Arc<OnceAsync<MaterializedOutput>>>, + metrics: ExecutionPlanMetricsSet, +} + +impl fmt::Debug for MaterializedCteBuffer { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + f.debug_struct("MaterializedCteBuffer") + .field("name", &self.name) + .finish_non_exhaustive() + } +} + +impl MaterializedCteBuffer { + pub fn new(id: u64, name: impl Into<String>) -> Self { + Self { + id, + name: name.into(), + body: Mutex::new(None), + output: Mutex::new(Arc::default()), + metrics: ExecutionPlanMetricsSet::new(), + } + } + + /// The id that binds scans to this buffer. + pub fn id(&self) -> u64 { + self.id + } + + fn set_body(&self, body: Arc<dyn ExecutionPlan>) { + *self.body.lock() = Some(body); + } + + fn reset(&self) { + *self.output.lock() = Arc::default(); + } + + /// Return a future that resolves once the body has been fully buffered. + /// The body runs at most once, whichever consumer asks first. + fn materialize( + self: &Arc<Self>, + context: Arc<TaskContext>, + ) -> Result<OnceFut<MaterializedOutput>> { + let Some(body) = self.body.lock().clone() else { + return internal_err!("MaterializedCte {} has no body", self.name); + }; + let once = Arc::clone(&self.output.lock()); + let name = self.name.clone(); + let metrics = self.metrics.clone(); + once.try_once(move || Ok(buffer_body(name, body, context, metrics))) + } +} + +async fn buffer_body( + name: String, + body: Arc<dyn ExecutionPlan>, + context: Arc<TaskContext>, + metrics: ExecutionPlanMetricsSet, +) -> Result<MaterializedOutput> { + let spill_manager = SpillManager::new( + context.runtime_env(), + SpillMetrics::new(&metrics, 0), + body.schema(), + ) + .with_compression_type(context.session_config().spill_compression()); + let buffered_rows = MetricBuilder::new(&metrics).global_counter("buffered_rows"); + + let mut join_set = JoinSet::new(); + for partition in 0..body.output_partitioning().partition_count() { + let stream = body.execute(partition, Arc::clone(&context))?; + let reservation = + MemoryConsumer::new(format!("MaterializedCte[{name}][{partition}]")) + .with_can_spill(true) + .register(context.memory_pool()); + let spill_manager = spill_manager.clone(); + let buffered_rows = buffered_rows.clone(); + join_set.spawn(async move { + let result = + buffer_partition(stream, reservation, &spill_manager, &buffered_rows) + .await; + (partition, result) + }); + } + + let mut partitions = Vec::with_capacity(join_set.len()); + while let Some(joined) = join_set.join_next().await { + match joined { + Ok((partition, result)) => partitions.push((partition, result?)), + Err(e) if e.is_panic() => std::panic::resume_unwind(e.into_panic()), + Err(e) => return internal_err!("MaterializedCte task failed: {e}"), + } + } + partitions.sort_by_key(|(partition, _)| *partition); + Ok(MaterializedOutput { + partitions: partitions.into_iter().map(|(_, p)| p).collect(), + spill_manager, + }) +} + +async fn buffer_partition( + mut stream: SendableRecordBatchStream, + reservation: MemoryReservation, + spill_manager: &SpillManager, + buffered_rows: &crate::metrics::Count, +) -> Result<BufferedPartition> { + let mut batches = vec![]; + let mut spill = None; + while let Some(batch) = stream.next().await.transpose()? { + buffered_rows.add(batch.num_rows()); + // Once a partition spills, every later batch goes to the same file, + // so replay keeps the order of the partition. + if spill.is_none() && reservation.try_grow(batch.get_array_memory_size()).is_ok() + { + batches.push(batch); + continue; + } + if spill.is_none() { + spill = Some(spill_manager.create_in_progress_file("MaterializedCte")?); + } + if let Some(file) = spill.as_mut() { + file.append_batch(&batch)?; + } + } + let spill_file = match spill { + Some(mut file) => file.finish()?, + None => None, + }; + Ok(BufferedPartition { + batches, + spill_file, + _reservation: reservation, + }) +} + +/// Stream the buffered partitions `partition, partition + n, ...` of `output`, +/// where `n` is the number of output partitions of the scan. +fn replay( + output: &MaterializedOutput, + partition: usize, + output_partitions: usize, +) -> Result<Vec<SendableRecordBatchStream>> { + let mut streams = vec![]; + for buffered in output + .partitions + .iter() + .skip(partition) + .step_by(output_partitions) + { + let schema = Arc::clone(output.spill_manager.schema()); + let batches = buffered.batches.clone(); + streams.push(Box::pin(RecordBatchStreamAdapter::new( + schema, + futures::stream::iter(batches.into_iter().map(Ok)), + )) as SendableRecordBatchStream); + if let Some(file) = &buffered.spill_file { + streams.push( + output + .spill_manager + .read_spill_as_stream(Arc::clone(file), None)?, + ); Review Comment: Each replay calls the buffered spill reader, which decodes up to two batches ahead, but this memory is not covered by any `MemoryReservation`. The retained in-memory prefix can already consume nearly the entire pool, and every concurrent CTE reference adds another untracked read-ahead buffer, so a query can substantially exceed `memory_limit` after spilling. Replay needs accounted headroom/reservations (or an unbuffered, bounded-memory strategy), especially for multiple readers. ########## datafusion/physical-plan/src/materialized_cte.rs: ########## @@ -0,0 +1,606 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Execution plans for `WITH x AS MATERIALIZED (...)`. +//! +//! [`MaterializedCteExec`] owns the CTE body and the continuation (the rest of +//! the query). Every [`MaterializedCteScanExec`] in the continuation shares one +//! [`MaterializedCteBuffer`] with it. The first consumer to execute runs every +//! partition of the body to completion and buffers the output; every scan then +//! replays that buffer. +//! +//! The body is fully materialized before any scan yields a row. This is a +//! pipeline break, but it cannot deadlock when two consumers of the same CTE +//! are read at different rates (for example the build and probe side of one +//! hash join), which a bounded fan-out channel can. +//! +//! Buffered batches are accounted in the memory pool. When a reservation +//! fails, the rest of that partition is written to a spill file, and the scans +//! read the in-memory prefix and then the spill file, so row order within a +//! partition is kept. + +use std::fmt; +use std::sync::Arc; + +use arrow::datatypes::SchemaRef; +use arrow::record_batch::RecordBatch; +use datafusion_common::config::ConfigOptions; +use datafusion_common::tree_node::TreeNodeRecursion; +use datafusion_common::{Result, Statistics, internal_err}; +use datafusion_common_runtime::JoinSet; +use datafusion_execution::memory_pool::{MemoryConsumer, MemoryReservation}; +use datafusion_execution::{SendableRecordBatchStream, SpillFile, TaskContext}; +use datafusion_physical_expr::{EquivalenceProperties, Partitioning, PhysicalExpr}; +use futures::{StreamExt, TryStreamExt}; +use parking_lot::Mutex; + +use crate::coop::cooperative; +use crate::execution_plan::{ + Boundedness, CardinalityEffect, EmissionType, ExecutionPlan, ExecutionPlanProperties, + PlanProperties, SchedulingType, +}; +use crate::filter_pushdown::{ + ChildFilterDescription, ChildPushdownResult, FilterDescription, FilterPushdownPhase, + FilterPushdownPropagation, +}; +use crate::joins::utils::{OnceAsync, OnceFut}; +use crate::metrics::{ + BaselineMetrics, ExecutionPlanMetricsSet, MetricBuilder, MetricsSet, SpillMetrics, +}; +use crate::spill::spill_manager::SpillManager; +use crate::statistics::{ChildStats, StatisticsArgs}; +use crate::stream::RecordBatchStreamAdapter; +use crate::{ + ChildrenPropertiesMode, DisplayAs, DisplayFormatType, ReplaceChildrenOptions, +}; + +/// The buffered output of one body partition: an in-memory prefix followed by +/// an optional spill file with the remaining batches. +struct BufferedPartition { + batches: Vec<RecordBatch>, + spill_file: Option<Arc<dyn SpillFile>>, + /// Released when the buffer is dropped. + _reservation: MemoryReservation, +} + +/// The materialized output of a CTE body. +struct MaterializedOutput { + partitions: Vec<BufferedPartition>, + spill_manager: SpillManager, +} + +/// State shared by one [`MaterializedCteExec`] and all its +/// [`MaterializedCteScanExec`]s. +pub struct MaterializedCteBuffer { + id: u64, + name: String, + /// The body to run. [`MaterializedCteExec`] updates it every time it is + /// rebuilt (for example by a physical optimizer rule), so it is the body of + /// the final plan. A scan can run the body before the owning + /// `MaterializedCteExec` executes, for example from a scalar subquery. + body: Mutex<Option<Arc<dyn ExecutionPlan>>>, + output: Mutex<Arc<OnceAsync<MaterializedOutput>>>, + metrics: ExecutionPlanMetricsSet, +} + +impl fmt::Debug for MaterializedCteBuffer { + fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { + f.debug_struct("MaterializedCteBuffer") + .field("name", &self.name) + .finish_non_exhaustive() + } +} + +impl MaterializedCteBuffer { + pub fn new(id: u64, name: impl Into<String>) -> Self { + Self { + id, + name: name.into(), + body: Mutex::new(None), + output: Mutex::new(Arc::default()), + metrics: ExecutionPlanMetricsSet::new(), + } + } + + /// The id that binds scans to this buffer. + pub fn id(&self) -> u64 { + self.id + } + + fn set_body(&self, body: Arc<dyn ExecutionPlan>) { + *self.body.lock() = Some(body); + } + + fn reset(&self) { + *self.output.lock() = Arc::default(); + } + + /// Return a future that resolves once the body has been fully buffered. + /// The body runs at most once, whichever consumer asks first. + fn materialize( + self: &Arc<Self>, + context: Arc<TaskContext>, + ) -> Result<OnceFut<MaterializedOutput>> { + let Some(body) = self.body.lock().clone() else { + return internal_err!("MaterializedCte {} has no body", self.name); + }; + let once = Arc::clone(&self.output.lock()); + let name = self.name.clone(); + let metrics = self.metrics.clone(); + once.try_once(move || Ok(buffer_body(name, body, context, metrics))) + } +} + +async fn buffer_body( + name: String, + body: Arc<dyn ExecutionPlan>, + context: Arc<TaskContext>, + metrics: ExecutionPlanMetricsSet, +) -> Result<MaterializedOutput> { + let spill_manager = SpillManager::new( + context.runtime_env(), + SpillMetrics::new(&metrics, 0), + body.schema(), + ) + .with_compression_type(context.session_config().spill_compression()); + let buffered_rows = MetricBuilder::new(&metrics).global_counter("buffered_rows"); + + let mut join_set = JoinSet::new(); + for partition in 0..body.output_partitioning().partition_count() { + let stream = body.execute(partition, Arc::clone(&context))?; + let reservation = + MemoryConsumer::new(format!("MaterializedCte[{name}][{partition}]")) + .with_can_spill(true) + .register(context.memory_pool()); + let spill_manager = spill_manager.clone(); + let buffered_rows = buffered_rows.clone(); + join_set.spawn(async move { + let result = + buffer_partition(stream, reservation, &spill_manager, &buffered_rows) + .await; + (partition, result) + }); + } + + let mut partitions = Vec::with_capacity(join_set.len()); + while let Some(joined) = join_set.join_next().await { + match joined { + Ok((partition, result)) => partitions.push((partition, result?)), + Err(e) if e.is_panic() => std::panic::resume_unwind(e.into_panic()), + Err(e) => return internal_err!("MaterializedCte task failed: {e}"), + } + } + partitions.sort_by_key(|(partition, _)| *partition); + Ok(MaterializedOutput { + partitions: partitions.into_iter().map(|(_, p)| p).collect(), + spill_manager, + }) +} + +async fn buffer_partition( + mut stream: SendableRecordBatchStream, + reservation: MemoryReservation, + spill_manager: &SpillManager, + buffered_rows: &crate::metrics::Count, +) -> Result<BufferedPartition> { + let mut batches = vec![]; + let mut spill = None; + while let Some(batch) = stream.next().await.transpose()? { + buffered_rows.add(batch.num_rows()); + // Once a partition spills, every later batch goes to the same file, + // so replay keeps the order of the partition. + if spill.is_none() && reservation.try_grow(batch.get_array_memory_size()).is_ok() + { + batches.push(batch); + continue; + } + if spill.is_none() { + spill = Some(spill_manager.create_in_progress_file("MaterializedCte")?); + } + if let Some(file) = spill.as_mut() { + file.append_batch(&batch)?; + } + } + let spill_file = match spill { + Some(mut file) => file.finish()?, + None => None, + }; + Ok(BufferedPartition { + batches, + spill_file, + _reservation: reservation, + }) +} + +/// Stream the buffered partitions `partition, partition + n, ...` of `output`, +/// where `n` is the number of output partitions of the scan. +fn replay( + output: &MaterializedOutput, + partition: usize, + output_partitions: usize, +) -> Result<Vec<SendableRecordBatchStream>> { + let mut streams = vec![]; + for buffered in output + .partitions + .iter() + .skip(partition) + .step_by(output_partitions) + { + let schema = Arc::clone(output.spill_manager.schema()); + let batches = buffered.batches.clone(); + streams.push(Box::pin(RecordBatchStreamAdapter::new( + schema, + futures::stream::iter(batches.into_iter().map(Ok)), + )) as SendableRecordBatchStream); + if let Some(file) = &buffered.spill_file { + streams.push( + output + .spill_manager + .read_spill_as_stream(Arc::clone(file), None)?, + ); + } + } + Ok(streams) +} + +/// Computes a CTE body once and runs the continuation, whose +/// [`MaterializedCteScanExec`]s read the buffered body output. +/// +/// Children: `[body, continuation]`. The output is the output of the +/// continuation. +#[derive(Debug)] +pub struct MaterializedCteExec { + body: Arc<dyn ExecutionPlan>, + continuation: Arc<dyn ExecutionPlan>, + buffer: Arc<MaterializedCteBuffer>, + cache: Arc<PlanProperties>, +} + +impl MaterializedCteExec { + pub fn new( + body: Arc<dyn ExecutionPlan>, + continuation: Arc<dyn ExecutionPlan>, + buffer: Arc<MaterializedCteBuffer>, + ) -> Self { + buffer.set_body(Arc::clone(&body)); + let cache = Arc::clone(continuation.properties()); + Self { + body, + continuation, + buffer, + cache, + } + } + + pub fn buffer(&self) -> &Arc<MaterializedCteBuffer> { + &self.buffer + } +} + +impl DisplayAs for MaterializedCteExec { + fn fmt_as(&self, t: DisplayFormatType, f: &mut fmt::Formatter) -> fmt::Result { + match t { + DisplayFormatType::Default | DisplayFormatType::Verbose => { + write!(f, "MaterializedCteExec: name={}", self.buffer.name) + } + DisplayFormatType::TreeRender => write!(f, "name={}", self.buffer.name), + } + } +} + +impl ExecutionPlan for MaterializedCteExec { + fn name(&self) -> &'static str { + "MaterializedCteExec" + } + + fn properties(&self) -> &Arc<PlanProperties> { + &self.cache + } + + fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> { + vec![&self.body, &self.continuation] + } + + fn apply_expressions( + &self, + _f: &mut dyn FnMut(&Arc<dyn PhysicalExpr>) -> Result<TreeNodeRecursion>, + ) -> Result<TreeNodeRecursion> { + Ok(TreeNodeRecursion::Continue) + } + + fn replace_children( + self: Arc<Self>, + mut children: Vec<Arc<dyn ExecutionPlan>>, + _: ReplaceChildrenOptions, + ) -> Result<Arc<dyn ExecutionPlan>> { + if children.len() != 2 { + return internal_err!("MaterializedCteExec takes 2 children"); + } + let continuation = children.pop().unwrap(); + let body = children.pop().unwrap(); + Ok(Arc::new(Self::new( + body, + continuation, + Arc::clone(&self.buffer), + ))) + } + + fn with_new_children( + self: Arc<Self>, + children: Vec<Arc<dyn ExecutionPlan>>, + ) -> Result<Arc<dyn ExecutionPlan>> { + self.replace_children( + children, + ReplaceChildrenOptions::new(ChildrenPropertiesMode::Recompute), + ) + } + + fn reset_state(self: Arc<Self>) -> Result<Arc<dyn ExecutionPlan>> { + self.buffer.reset(); + Ok(self) + } + + fn maintains_input_order(&self) -> Vec<bool> { + vec![false, true] + } + + fn benefits_from_input_partitioning(&self) -> Vec<bool> { + vec![true, false] + } + + fn execute( + &self, + partition: usize, + context: Arc<TaskContext>, + ) -> Result<SendableRecordBatchStream> { + // The body runs lazily, when the first scan polls it. + self.buffer.set_body(Arc::clone(&self.body)); + self.continuation.execute(partition, context) + } + + fn metrics(&self) -> Option<MetricsSet> { + Some(self.buffer.metrics.clone_inner()) + } + + fn child_stats_requests(&self, partition: Option<usize>) -> Vec<ChildStats> { + vec![ChildStats::Skip, ChildStats::At(partition)] + } + + fn statistics_from_inputs( + &self, + input_stats: &[Arc<Statistics>], + _args: &StatisticsArgs, + ) -> Result<Arc<Statistics>> { + Ok(Arc::clone(&input_stats[1])) + } + + fn cardinality_effect(&self) -> CardinalityEffect { + CardinalityEffect::Equal + } + + /// The output is the output of the continuation, so parent filters go to + /// the continuation only. The body is shared by every scan and must not + /// be filtered for one consumer. + fn gather_filters_for_pushdown( + &self, + _phase: FilterPushdownPhase, + parent_filters: Vec<Arc<dyn PhysicalExpr>>, + _config: &ConfigOptions, + ) -> Result<FilterDescription> { + Ok(FilterDescription::new() + .with_child(ChildFilterDescription::all_unsupported(&parent_filters)) + .with_child(ChildFilterDescription::from_child( + &parent_filters, + &self.continuation, + )?)) + } + + fn handle_child_pushdown_result( + &self, + _phase: FilterPushdownPhase, + child_pushdown_result: ChildPushdownResult, + _config: &ConfigOptions, + ) -> Result<FilterPushdownPropagation<Arc<dyn ExecutionPlan>>> { + // The body always reports `No`, so a filter is handled when the + // continuation handles it. + Ok(FilterPushdownPropagation::if_any(child_pushdown_result)) + } +} + +/// Reads the buffered output of a [`MaterializedCteExec`] body. +#[derive(Debug)] +pub struct MaterializedCteScanExec { + id: u64, + name: String, + schema: SchemaRef, + buffer: Option<Arc<MaterializedCteBuffer>>, + metrics: ExecutionPlanMetricsSet, + cache: Arc<PlanProperties>, +} + +impl MaterializedCteScanExec { + /// Create a scan that is not yet bound to a buffer. See [`Self::bind`]. + pub fn new( + id: u64, + name: impl Into<String>, + schema: SchemaRef, + partitions: usize, + ) -> Self { + let cache = PlanProperties::new( + EquivalenceProperties::new(Arc::clone(&schema)), + Partitioning::UnknownPartitioning(partitions.max(1)), + EmissionType::Final, + Boundedness::Bounded, Review Comment: The scan is declared bounded even when the CTE body is an unbounded source. Because the full-buffering pipeline break happens inside `materialize()` rather than in the scan's child tree, `SanityCheckPlan` sees a bounded final scan and accepts the query; execution then buffers/spills forever and never emits a row. The bound body must be propagated during binding, or materialized CTE planning must reject unbounded bodies. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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