Dandandan commented on code in PR #7192:
URL: https://github.com/apache/arrow-datafusion/pull/7192#discussion_r1287494273
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datafusion/core/src/physical_plan/aggregates/priority_queue.rs:
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@@ -0,0 +1,235 @@
+use uuid::Uuid;
+use std::collections::{BTreeMap, HashMap};
+use std::pin::Pin;
+use std::sync::Arc;
+use std::task::{Context, Poll};
+use arrow::row::{OwnedRow, RowConverter, SortField};
+use arrow::util::pretty::print_batches;
+use arrow_array::{RecordBatch};
+use arrow_schema::{DataType, SchemaRef, SortOptions};
+use futures::stream::{Stream, StreamExt};
+use hashbrown::HashSet;
+use datafusion_common::DataFusionError;
+use datafusion_execution::TaskContext;
+use datafusion_physical_expr::{PhysicalExpr};
+use crate::physical_plan::aggregates::{aggregate_expressions, AggregateExec,
evaluate_group_by, evaluate_many, group_schema, PhysicalGroupBy};
+use crate::physical_plan::{RecordBatchStream, SendableRecordBatchStream};
+use datafusion_common::Result;
+use datafusion_physical_expr::expressions::{Max, Min};
+
+pub(crate) struct GroupedPriorityQueueAggregateStream {
+ schema: SchemaRef,
+ input: SendableRecordBatchStream,
+ aggregate_arguments: Vec<Vec<Arc<dyn PhysicalExpr>>>,
+ group_by: PhysicalGroupBy,
+ group_converter: RowConverter,
+ value_converter: RowConverter, // TODO: use accumulators
+ group_to_val: HashMap<OwnedRow, OwnedRow>, // TODO: BTreeMap->BinaryHeap,
OwnedRow->Rows
+ val_to_group: BTreeMap<OwnedRow, HashSet<OwnedRow>>,
Review Comment:
Yeah of course :).
I think once we have some benchmarks / queries to test against we can do
some profiling and see if it's worth optimizing.
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