Wrap immutable plan parts into Arc

datafusion/common/src/stats.rs

@@ -391,8 +391,8 @@ impl Statistics {
     /// For example, if we had statistics for columns `{"a", "b", "c"}`,
     /// projecting to `vec![2, 1]` would return statistics for columns `{"c",
     /// "b"}`.
-    pub fn project(mut self, projection: Option<&Vec<usize>>) -> Self {
-        let Some(projection) = projection else {
+    pub fn project(mut self, projection: Option<&impl AsRef<[usize]>>) -> Self {
+        let Some(projection) = projection.map(AsRef::as_ref) else {
             return self;
         };
 
@@ -410,7 +410,7 @@ impl Statistics {
             .map(Slot::Present)
             .collect();
 
-        for idx in projection {
+        for idx in projection.iter() {
             let next_idx = self.column_statistics.len();
             let slot = std::mem::replace(
                 columns.get_mut(*idx).expect("projection out of bounds"),
@@ -1066,8 +1066,8 @@ mod tests {
 
     #[test]
     fn test_project_none() {
-        let projection = None;
-        let stats = make_stats(vec![10, 20, 30]).project(projection.as_ref());
+        let projection: Option<&Vec<usize>> = None;
+        let stats = make_stats(vec![10, 20, 30]).project(projection);
         assert_eq!(stats, make_stats(vec![10, 20, 30]));
     }
 

datafusion/common/src/utils/mod.rs

@@ -70,9 +70,9 @@ use std::thread::available_parallelism;
 /// ```
 pub fn project_schema(
     schema: &SchemaRef,
-    projection: Option<&Vec<usize>>,
+    projection: Option<&impl AsRef<[usize]>>,
 ) -> Result<SchemaRef> {
-    let schema = match projection {
+    let schema = match projection.map(AsRef::as_ref) {
         Some(columns) => Arc::new(schema.project(columns)?),
         None => Arc::clone(schema),
     };

datafusion/core/src/physical_planner.rs

@@ -984,7 +984,7 @@ impl DefaultPhysicalPlanner {
                         // project the output columns excluding the async functions
                         // The async functions are always appended to the end of the schema.
                         .apply_projection(Some(
-                            (0..input.schema().fields().len()).collect(),
+                            (0..input.schema().fields().len()).collect::<Vec<_>>(),
                         ))?
                         .with_batch_size(session_state.config().batch_size())
                         .build()?

datafusion/core/tests/physical_optimizer/join_selection.rs

@@ -762,7 +762,7 @@ async fn test_hash_join_swap_on_joins_with_projections(
             "ProjectionExec won't be added above if HashJoinExec contains embedded projection",
         );
 
-    assert_eq!(swapped_join.projection, Some(vec![0_usize]));
+    assert_eq!(swapped_join.projection.as_ref().unwrap(), [0_usize]);
     assert_eq!(swapped.schema().fields.len(), 1);
     assert_eq!(swapped.schema().fields[0].name(), "small_col");
     Ok(())

datafusion/physical-expr/src/projection.rs

@@ -125,7 +125,7 @@ impl From<ProjectionExpr> for (Arc<dyn PhysicalExpr>, String) {
 /// indices.
 #[derive(Debug, Clone, PartialEq, Eq)]
 pub struct ProjectionExprs {
-    exprs: Vec<ProjectionExpr>,
+    exprs: Arc<[ProjectionExpr]>,
 }
 
 impl std::fmt::Display for ProjectionExprs {
@@ -137,22 +137,24 @@ impl std::fmt::Display for ProjectionExprs {
 
 impl From<Vec<ProjectionExpr>> for ProjectionExprs {
     fn from(value: Vec<ProjectionExpr>) -> Self {
-        Self { exprs: value }
+        Self {
+            exprs: value.into(),
+        }
     }
 }
 
 impl From<&[ProjectionExpr]> for ProjectionExprs {
     fn from(value: &[ProjectionExpr]) -> Self {
         Self {
-            exprs: value.to_vec(),
+            exprs: value.iter().cloned().collect(),
         }
     }
 }
 
 impl FromIterator<ProjectionExpr> for ProjectionExprs {
     fn from_iter<T: IntoIterator<Item = ProjectionExpr>>(exprs: T) -> Self {
         Self {
-            exprs: exprs.into_iter().collect::<Vec<_>>(),
+            exprs: exprs.into_iter().collect(),
         }
     }
 }
@@ -164,12 +166,17 @@ impl AsRef<[ProjectionExpr]> for ProjectionExprs {
 }
 
 impl ProjectionExprs {
-    pub fn new<I>(exprs: I) -> Self
-    where
-        I: IntoIterator<Item = ProjectionExpr>,
-    {
+    /// Make a new [`ProjectionExprs`] from expressions iterator.
+    pub fn new(exprs: impl IntoIterator<Item = ProjectionExpr>) -> Self {
+        Self {
+            exprs: exprs.into_iter().collect(),
+        }
+    }
+
+    /// Make a new [`ProjectionExprs`] from expressions.
+    pub fn from_expressions(exprs: impl Into<Arc<[ProjectionExpr]>>) -> Self {
         Self {
-            exprs: exprs.into_iter().collect::<Vec<_>>(),
+            exprs: exprs.into(),
         }
     }
 
@@ -285,13 +292,14 @@ impl ProjectionExprs {
     {
         let exprs = self
             .exprs
-            .into_iter()
+            .iter()
+            .cloned()
             .map(|mut proj| {
                 proj.expr = f(proj.expr)?;
                 Ok(proj)
             })
-            .collect::<Result<Vec<_>>>()?;
-        Ok(Self::new(exprs))
+            .collect::<Result<Arc<_>>>()?;
+        Ok(Self::from_expressions(exprs))
     }
 
     /// Apply another projection on top of this projection, returning the combined projection.
@@ -361,7 +369,7 @@ impl ProjectionExprs {
     /// applied on top of this projection.
     pub fn try_merge(&self, other: &ProjectionExprs) -> Result<ProjectionExprs> {
         let mut new_exprs = Vec::with_capacity(other.exprs.len());
-        for proj_expr in &other.exprs {
+        for proj_expr in other.exprs.iter() {
             let new_expr = update_expr(&proj_expr.expr, &self.exprs, true)?
                 .ok_or_else(|| {
                     internal_datafusion_err!(
@@ -607,7 +615,7 @@ impl ProjectionExprs {
     ) -> Result<datafusion_common::Statistics> {
         let mut column_statistics = vec![];
 
-        for proj_expr in &self.exprs {
+        for proj_expr in self.exprs.iter() {
             let expr = &proj_expr.expr;
             let col_stats = if let Some(col) = expr.as_any().downcast_ref::<Column>() {
                 std::mem::take(&mut stats.column_statistics[col.index()])
@@ -754,15 +762,6 @@ impl Projector {
     }
 }
 
-impl IntoIterator for ProjectionExprs {
-    type Item = ProjectionExpr;
-    type IntoIter = std::vec::IntoIter<ProjectionExpr>;
-
-    fn into_iter(self) -> Self::IntoIter {
-        self.exprs.into_iter()
-    }
-}
-
 /// The function operates in two modes:
 ///
 /// 1) When `sync_with_child` is `true`:

datafusion/physical-optimizer/src/enforce_sorting/sort_pushdown.rs

@@ -723,7 +723,7 @@ fn handle_hash_join(
         .collect();
 
     let column_indices = build_join_column_index(plan);
-    let projected_indices: Vec<_> = if let Some(projection) = &plan.projection {
+    let projected_indices: Vec<_> = if let Some(projection) = plan.projection.as_ref() {
         projection.iter().map(|&i| &column_indices[i]).collect()
     } else {
         column_indices.iter().collect()

datafusion/physical-optimizer/src/projection_pushdown.rs

@@ -135,7 +135,7 @@ fn try_push_down_join_filter(
     );
 
     let new_lhs_length = lhs_rewrite.data.0.schema().fields.len();
-    let projections = match projections {
+    let projections = match projections.as_ref() {
         None => match join.join_type() {
             JoinType::Inner | JoinType::Left | JoinType::Right | JoinType::Full => {
                 // Build projections that ignore the newly projected columns.

datafusion/physical-plan/src/aggregates/mod.rs

@@ -544,11 +544,11 @@ pub struct AggregateExec {
     /// Aggregation mode (full, partial)
     mode: AggregateMode,
     /// Group by expressions
-    group_by: PhysicalGroupBy,
+    group_by: Arc<PhysicalGroupBy>,
     /// Aggregate expressions
-    aggr_expr: Vec<Arc<AggregateFunctionExpr>>,
+    aggr_expr: Arc<[Arc<AggregateFunctionExpr>]>,
     /// FILTER (WHERE clause) expression for each aggregate expression
-    filter_expr: Vec<Option<Arc<dyn PhysicalExpr>>>,
+    filter_expr: Arc<[Option<Arc<dyn PhysicalExpr>>]>,
     /// Configuration for limit-based optimizations
     limit_options: Option<LimitOptions>,
     /// Input plan, could be a partial aggregate or the input to the aggregate
@@ -582,18 +582,18 @@ impl AggregateExec {
     /// Rewrites aggregate exec with new aggregate expressions.
     pub fn with_new_aggr_exprs(
         &self,
-        aggr_expr: Vec<Arc<AggregateFunctionExpr>>,
+        aggr_expr: impl Into<Arc<[Arc<AggregateFunctionExpr>]>>,
     ) -> Self {
         Self {
-            aggr_expr,
+            aggr_expr: aggr_expr.into(),
             // clone the rest of the fields
             required_input_ordering: self.required_input_ordering.clone(),
             metrics: ExecutionPlanMetricsSet::new(),
             input_order_mode: self.input_order_mode.clone(),
             cache: self.cache.clone(),
             mode: self.mode,
-            group_by: self.group_by.clone(),
-            filter_expr: self.filter_expr.clone(),
+            group_by: Arc::clone(&self.group_by),
+            filter_expr: Arc::clone(&self.filter_expr),
             limit_options: self.limit_options,
             input: Arc::clone(&self.input),
             schema: Arc::clone(&self.schema),
@@ -612,9 +612,9 @@ impl AggregateExec {
             input_order_mode: self.input_order_mode.clone(),
             cache: self.cache.clone(),
             mode: self.mode,
-            group_by: self.group_by.clone(),
-            aggr_expr: self.aggr_expr.clone(),
-            filter_expr: self.filter_expr.clone(),
+            group_by: Arc::clone(&self.group_by),
+            aggr_expr: Arc::clone(&self.aggr_expr),
+            filter_expr: Arc::clone(&self.filter_expr),
             input: Arc::clone(&self.input),
             schema: Arc::clone(&self.schema),
             input_schema: Arc::clone(&self.input_schema),
@@ -629,12 +629,13 @@ impl AggregateExec {
     /// Create a new hash aggregate execution plan
     pub fn try_new(
         mode: AggregateMode,
-        group_by: PhysicalGroupBy,
+        group_by: impl Into<Arc<PhysicalGroupBy>>,
         aggr_expr: Vec<Arc<AggregateFunctionExpr>>,
         filter_expr: Vec<Option<Arc<dyn PhysicalExpr>>>,
         input: Arc<dyn ExecutionPlan>,
         input_schema: SchemaRef,
     ) -> Result<Self> {
+        let group_by = group_by.into();
         let schema = create_schema(&input.schema(), &group_by, &aggr_expr, mode)?;
 
         let schema = Arc::new(schema);
@@ -659,13 +660,16 @@ impl AggregateExec {
     /// the schema in such cases.
     fn try_new_with_schema(
         mode: AggregateMode,
-        group_by: PhysicalGroupBy,
+        group_by: impl Into<Arc<PhysicalGroupBy>>,
         mut aggr_expr: Vec<Arc<AggregateFunctionExpr>>,
-        filter_expr: Vec<Option<Arc<dyn PhysicalExpr>>>,
+        filter_expr: impl Into<Arc<[Option<Arc<dyn PhysicalExpr>>]>>,
         input: Arc<dyn ExecutionPlan>,
         input_schema: SchemaRef,
         schema: SchemaRef,
     ) -> Result<Self> {
+        let group_by = group_by.into();
+        let filter_expr = filter_expr.into();
+
         // Make sure arguments are consistent in size
         assert_eq_or_internal_err!(
             aggr_expr.len(),
@@ -732,13 +736,13 @@ impl AggregateExec {
             &group_expr_mapping,
             &mode,
             &input_order_mode,
-            aggr_expr.as_slice(),
+            aggr_expr.as_ref(),
         )?;
 
         let mut exec = AggregateExec {
             mode,
             group_by,
-            aggr_expr,
+            aggr_expr: aggr_expr.into(),
             filter_expr,
             input,
             schema,
@@ -1287,9 +1291,9 @@ impl ExecutionPlan for AggregateExec {
     ) -> Result<Arc<dyn ExecutionPlan>> {
         let mut me = AggregateExec::try_new_with_schema(
             self.mode,
-            self.group_by.clone(),
-            self.aggr_expr.clone(),
-            self.filter_expr.clone(),
+            Arc::clone(&self.group_by),
+            self.aggr_expr.to_vec(),
+            Arc::clone(&self.filter_expr),
             Arc::clone(&children[0]),
             Arc::clone(&self.input_schema),
             Arc::clone(&self.schema),

datafusion/physical-plan/src/aggregates/no_grouping.rs

@@ -61,7 +61,7 @@ struct AggregateStreamInner {
     mode: AggregateMode,
     input: SendableRecordBatchStream,
     aggregate_expressions: Vec<Vec<Arc<dyn PhysicalExpr>>>,
-    filter_expressions: Vec<Option<Arc<dyn PhysicalExpr>>>,
+    filter_expressions: Arc<[Option<Arc<dyn PhysicalExpr>>]>,
 
     // ==== Runtime States/Buffers ====
     accumulators: Vec<AccumulatorItem>,
@@ -276,7 +276,7 @@ impl AggregateStream {
         partition: usize,
     ) -> Result<Self> {
         let agg_schema = Arc::clone(&agg.schema);
-        let agg_filter_expr = agg.filter_expr.clone();
+        let agg_filter_expr = Arc::clone(&agg.filter_expr);
 
         let baseline_metrics = BaselineMetrics::new(&agg.metrics, partition);
         let input = agg.input.execute(partition, Arc::clone(context))?;
@@ -287,7 +287,7 @@ impl AggregateStream {
             | AggregateMode::Single
             | AggregateMode::SinglePartitioned => agg_filter_expr,
             AggregateMode::Final | AggregateMode::FinalPartitioned => {
-                vec![None; agg.aggr_expr.len()]
+                vec![None; agg.aggr_expr.len()].into()
             }
         };
         let accumulators = create_accumulators(&agg.aggr_expr)?;

datafusion/physical-plan/src/aggregates/row_hash.rs

@@ -377,10 +377,10 @@ pub(crate) struct GroupedHashAggregateStream {
     ///
     /// For example, for an aggregate like `SUM(x) FILTER (WHERE x >= 100)`,
     /// the filter expression is  `x > 100`.
-    filter_expressions: Vec<Option<Arc<dyn PhysicalExpr>>>,
+    filter_expressions: Arc<[Option<Arc<dyn PhysicalExpr>>]>,
 
     /// GROUP BY expressions
-    group_by: PhysicalGroupBy,
+    group_by: Arc<PhysicalGroupBy>,
 
     /// max rows in output RecordBatches
     batch_size: usize,
@@ -465,8 +465,8 @@ impl GroupedHashAggregateStream {
     ) -> Result<Self> {
         debug!("Creating GroupedHashAggregateStream");
         let agg_schema = Arc::clone(&agg.schema);
-        let agg_group_by = agg.group_by.clone();
-        let agg_filter_expr = agg.filter_expr.clone();
+        let agg_group_by = Arc::clone(&agg.group_by);
+        let agg_filter_expr = Arc::clone(&agg.filter_expr);
 
         let batch_size = context.session_config().batch_size();
         let input = agg.input.execute(partition, Arc::clone(context))?;
@@ -475,7 +475,7 @@ impl GroupedHashAggregateStream {
 
         let timer = baseline_metrics.elapsed_compute().timer();
 
-        let aggregate_exprs = agg.aggr_expr.clone();
+        let aggregate_exprs = Arc::clone(&agg.aggr_expr);
 
         // arguments for each aggregate, one vec of expressions per
         // aggregate
@@ -496,7 +496,7 @@ impl GroupedHashAggregateStream {
             | AggregateMode::Single
             | AggregateMode::SinglePartitioned => agg_filter_expr,
             AggregateMode::Final | AggregateMode::FinalPartitioned => {
-                vec![None; agg.aggr_expr.len()]
+                vec![None; agg.aggr_expr.len()].into()
             }
         };
 

datafusion/physical-plan/src/aggregates/topk_stream.rs

@@ -50,7 +50,7 @@ pub struct GroupedTopKAggregateStream {
     baseline_metrics: BaselineMetrics,
     group_by_metrics: GroupByMetrics,
     aggregate_arguments: Vec<Vec<Arc<dyn PhysicalExpr>>>,
-    group_by: PhysicalGroupBy,
+    group_by: Arc<PhysicalGroupBy>,
     priority_map: PriorityMap,
 }
 
@@ -62,7 +62,7 @@ impl GroupedTopKAggregateStream {
         limit: usize,
     ) -> Result<Self> {
         let agg_schema = Arc::clone(&aggr.schema);
-        let group_by = aggr.group_by.clone();
+        let group_by = Arc::clone(&aggr.group_by);
         let input = aggr.input.execute(partition, Arc::clone(context))?;
         let baseline_metrics = BaselineMetrics::new(&aggr.metrics, partition);
         let group_by_metrics = GroupByMetrics::new(&aggr.metrics, partition);