Prevent repartitioning of certain operator's direct children (#1731)

Author: tustvold

datafusion/src/physical_optimizer/repartition.rs

@@ -19,10 +19,10 @@
 use std::sync::Arc;
 
 use super::optimizer::PhysicalOptimizerRule;
+use crate::physical_plan::Partitioning::*;
 use crate::physical_plan::{
     empty::EmptyExec, repartition::RepartitionExec, ExecutionPlan,
 };
-use crate::physical_plan::{Distribution, Partitioning::*};
 use crate::{error::Result, execution::context::ExecutionConfig};
 
 /// Optimizer that introduces repartition to introduce more parallelism in the plan
@@ -38,26 +38,24 @@ impl Repartition {
 
 fn optimize_partitions(
     target_partitions: usize,
-    requires_single_partition: bool,
     plan: Arc<dyn ExecutionPlan>,
+    should_repartition: bool,
 ) -> Result<Arc<dyn ExecutionPlan>> {
     // Recurse into children bottom-up (added nodes should be as deep as possible)
 
     let new_plan = if plan.children().is_empty() {
         // leaf node - don't replace children
         plan.clone()
     } else {
+        let should_repartition_children = plan.should_repartition_children();
         let children = plan
             .children()
             .iter()
             .map(|child| {
                 optimize_partitions(
                     target_partitions,
-                    matches!(
-                        plan.required_child_distribution(),
-                        Distribution::SinglePartition
-                    ),
                     child.clone(),
+                    should_repartition_children,
                 )
             })
             .collect::<Result<_>>()?;
@@ -77,7 +75,7 @@ fn optimize_partitions(
     // But also not very useful to inlude
     let is_empty_exec = plan.as_any().downcast_ref::<EmptyExec>().is_some();
 
-    if perform_repartition && !requires_single_partition && !is_empty_exec {
+    if perform_repartition && should_repartition && !is_empty_exec {
         Ok(Arc::new(RepartitionExec::try_new(
             new_plan,
             RoundRobinBatch(target_partitions),
@@ -97,7 +95,7 @@ impl PhysicalOptimizerRule for Repartition {
         if config.target_partitions == 1 {
             Ok(plan)
         } else {
-            optimize_partitions(config.target_partitions, true, plan)
+            optimize_partitions(config.target_partitions, plan, false)
         }
     }
 
@@ -107,93 +105,148 @@ impl PhysicalOptimizerRule for Repartition {
 }
 #[cfg(test)]
 mod tests {
-    use arrow::datatypes::Schema;
+    use arrow::datatypes::{DataType, Field, Schema, SchemaRef};
 
     use super::*;
     use crate::datasource::PartitionedFile;
+    use crate::physical_plan::expressions::col;
     use crate::physical_plan::file_format::{FileScanConfig, ParquetExec};
-    use crate::physical_plan::projection::ProjectionExec;
-    use crate::physical_plan::Statistics;
+    use crate::physical_plan::filter::FilterExec;
+    use crate::physical_plan::hash_aggregate::{AggregateMode, HashAggregateExec};
+    use crate::physical_plan::limit::{GlobalLimitExec, LocalLimitExec};
+    use crate::physical_plan::{displayable, Statistics};
     use crate::test::object_store::TestObjectStore;
 
+    fn schema() -> SchemaRef {
+        Arc::new(Schema::new(vec![Field::new("c1", DataType::Boolean, true)]))
+    }
+
+    fn parquet_exec() -> Arc<ParquetExec> {
+        Arc::new(ParquetExec::new(
+            FileScanConfig {
+                object_store: TestObjectStore::new_arc(&[("x", 100)]),
+                file_schema: schema(),
+                file_groups: vec![vec![PartitionedFile::new("x".to_string(), 100)]],
+                statistics: Statistics::default(),
+                projection: None,
+                limit: None,
+                table_partition_cols: vec![],
+            },
+            None,
+        ))
+    }
+
+    fn filter_exec(input: Arc<dyn ExecutionPlan>) -> Arc<dyn ExecutionPlan> {
+        Arc::new(FilterExec::try_new(col("c1", &schema()).unwrap(), input).unwrap())
+    }
+
+    fn hash_aggregate(input: Arc<dyn ExecutionPlan>) -> Arc<dyn ExecutionPlan> {
+        let schema = schema();
+        Arc::new(
+            HashAggregateExec::try_new(
+                AggregateMode::Final,
+                vec![],
+                vec![],
+                Arc::new(
+                    HashAggregateExec::try_new(
+                        AggregateMode::Partial,
+                        vec![],
+                        vec![],
+                        input,
+                        schema.clone(),
+                    )
+                    .unwrap(),
+                ),
+                schema,
+            )
+            .unwrap(),
+        )
+    }
+
+    fn limit_exec(input: Arc<dyn ExecutionPlan>) -> Arc<dyn ExecutionPlan> {
+        Arc::new(GlobalLimitExec::new(
+            Arc::new(LocalLimitExec::new(input, 100)),
+            100,
+        ))
+    }
+
+    fn trim_plan_display(plan: &str) -> Vec<&str> {
+        plan.split('\n')
+            .map(|s| s.trim())
+            .filter(|s| !s.is_empty())
+            .collect()
+    }
+
     #[test]
     fn added_repartition_to_single_partition() -> Result<()> {
-        let file_schema = Arc::new(Schema::empty());
-        let parquet_project = ProjectionExec::try_new(
-            vec![],
-            Arc::new(ParquetExec::new(
-                FileScanConfig {
-                    object_store: TestObjectStore::new_arc(&[("x", 100)]),
-                    file_schema,
-                    file_groups: vec![vec![PartitionedFile::new("x".to_string(), 100)]],
-                    statistics: Statistics::default(),
-                    projection: None,
-                    limit: None,
-                    table_partition_cols: vec![],
-                },
-                None,
-            )),
-        )?;
-
         let optimizer = Repartition {};
 
         let optimized = optimizer.optimize(
-            Arc::new(parquet_project),
+            hash_aggregate(parquet_exec()),
             &ExecutionConfig::new().with_target_partitions(10),
         )?;
 
-        assert_eq!(
-            optimized.children()[0]
-                .output_partitioning()
-                .partition_count(),
-            10
-        );
+        let plan = displayable(optimized.as_ref()).indent().to_string();
+
+        let expected = &[
+            "HashAggregateExec: mode=Final, gby=[], aggr=[]",
+            "HashAggregateExec: mode=Partial, gby=[], aggr=[]",
+            "RepartitionExec: partitioning=RoundRobinBatch(10)",
+            "ParquetExec: limit=None, partitions=[x]",
+        ];
 
+        assert_eq!(&trim_plan_display(&plan), &expected);
         Ok(())
     }
 
     #[test]
     fn repartition_deepest_node() -> Result<()> {
-        let file_schema = Arc::new(Schema::empty());
-        let parquet_project = ProjectionExec::try_new(
-            vec![],
-            Arc::new(ProjectionExec::try_new(
-                vec![],
-                Arc::new(ParquetExec::new(
-                    FileScanConfig {
-                        object_store: TestObjectStore::new_arc(&[("x", 100)]),
-                        file_schema,
-                        file_groups: vec![vec![PartitionedFile::new(
-                            "x".to_string(),
-                            100,
-                        )]],
-                        statistics: Statistics::default(),
-                        projection: None,
-                        limit: None,
-                        table_partition_cols: vec![],
-                    },
-                    None,
-                )),
-            )?),
+        let optimizer = Repartition {};
+
+        let optimized = optimizer.optimize(
+            hash_aggregate(filter_exec(parquet_exec())),
+            &ExecutionConfig::new().with_target_partitions(10),
         )?;
 
+        let plan = displayable(optimized.as_ref()).indent().to_string();
+
+        let expected = &[
+            "HashAggregateExec: mode=Final, gby=[], aggr=[]",
+            "HashAggregateExec: mode=Partial, gby=[], aggr=[]",
+            "FilterExec: c1@0",
+            "RepartitionExec: partitioning=RoundRobinBatch(10)",
+            "ParquetExec: limit=None, partitions=[x]",
+        ];
+
+        assert_eq!(&trim_plan_display(&plan), &expected);
+        Ok(())
+    }
+
+    #[test]
+    fn repartition_ignores() -> Result<()> {
         let optimizer = Repartition {};
 
         let optimized = optimizer.optimize(
-            Arc::new(parquet_project),
+            hash_aggregate(limit_exec(filter_exec(limit_exec(parquet_exec())))),
             &ExecutionConfig::new().with_target_partitions(10),
         )?;
 
-        // RepartitionExec is added to deepest node
-        assert!(optimized.children()[0]
-            .as_any()
-            .downcast_ref::<RepartitionExec>()
-            .is_none());
-        assert!(optimized.children()[0].children()[0]
-            .as_any()
-            .downcast_ref::<RepartitionExec>()
-            .is_some());
-
+        let plan = displayable(optimized.as_ref()).indent().to_string();
+
+        let expected = &[
+            "HashAggregateExec: mode=Final, gby=[], aggr=[]",
+            "HashAggregateExec: mode=Partial, gby=[], aggr=[]",
+            "RepartitionExec: partitioning=RoundRobinBatch(10)",
+            "GlobalLimitExec: limit=100",
+            "LocalLimitExec: limit=100",
+            "FilterExec: c1@0",
+            "RepartitionExec: partitioning=RoundRobinBatch(10)",
+            "GlobalLimitExec: limit=100",
+            "LocalLimitExec: limit=100", // Should not repartition for LocalLimitExec
+            "ParquetExec: limit=None, partitions=[x]",
+        ];
+
+        assert_eq!(&trim_plan_display(&plan), &expected);
         Ok(())
     }
 }

datafusion/src/physical_plan/limit.rs

@@ -300,6 +300,10 @@ impl ExecutionPlan for LocalLimitExec {
             _ => Statistics::default(),
         }
     }
+
+    fn should_repartition_children(&self) -> bool {
+        false
+    }
 }
 
 /// Truncate a RecordBatch to maximum of n rows

datafusion/src/physical_plan/mod.rs

@@ -135,14 +135,32 @@ pub trait ExecutionPlan: Debug + Send + Sync {
     /// Returns the execution plan as [`Any`](std::any::Any) so that it can be
     /// downcast to a specific implementation.
     fn as_any(&self) -> &dyn Any;
+
     /// Get the schema for this execution plan
     fn schema(&self) -> SchemaRef;
+
     /// Specifies the output partitioning scheme of this plan
     fn output_partitioning(&self) -> Partitioning;
+
     /// Specifies the data distribution requirements of all the children for this operator
     fn required_child_distribution(&self) -> Distribution {
         Distribution::UnspecifiedDistribution
     }
+
+    /// Returns `true` if the direct children of this `ExecutionPlan` should be repartitioned
+    /// to introduce greater concurrency to the plan
+    ///
+    /// The default implementation returns `true` unless `Self::request_child_distribution`
+    /// returns `Distribution::SinglePartition`
+    ///
+    /// Operators that do not benefit from additional partitioning may want to return `false`
+    fn should_repartition_children(&self) -> bool {
+        !matches!(
+            self.required_child_distribution(),
+            Distribution::SinglePartition
+        )
+    }
+
     /// Get a list of child execution plans that provide the input for this plan. The returned list
     /// will be empty for leaf nodes, will contain a single value for unary nodes, or two
     /// values for binary nodes (such as joins).

datafusion/src/physical_plan/projection.rs

@@ -185,6 +185,10 @@ impl ExecutionPlan for ProjectionExec {
             self.expr.iter().map(|(e, _)| Arc::clone(e)),
         )
     }
+
+    fn should_repartition_children(&self) -> bool {
+        false
+    }
 }
 
 /// If e is a direct column reference, returns the field level

datafusion/src/physical_plan/union.rs

@@ -143,6 +143,10 @@ impl ExecutionPlan for UnionExec {
             .reduce(stats_union)
             .unwrap_or_default()
     }
+
+    fn should_repartition_children(&self) -> bool {
+        false
+    }
 }
 
 /// Stream wrapper that records `BaselineMetrics` for a particular