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[branch-52] fix: use spill writer's schema instead of the first batch schema for spill files (#21293) #21403
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162 changes: 162 additions & 0 deletions
162
datafusion/core/tests/memory_limit/union_nullable_spill.rs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,162 @@ | ||
| // 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. | ||
|
|
||
| use std::sync::Arc; | ||
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|
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| use arrow::array::{Array, Int64Array, RecordBatch}; | ||
| use arrow::compute::SortOptions; | ||
| use arrow::datatypes::{DataType, Field, Schema}; | ||
| use datafusion::datasource::memory::MemorySourceConfig; | ||
| use datafusion_execution::config::SessionConfig; | ||
| use datafusion_execution::memory_pool::FairSpillPool; | ||
| use datafusion_execution::runtime_env::RuntimeEnvBuilder; | ||
| use datafusion_physical_expr::expressions::col; | ||
| use datafusion_physical_expr::{LexOrdering, PhysicalSortExpr}; | ||
| use datafusion_physical_plan::repartition::RepartitionExec; | ||
| use datafusion_physical_plan::sorts::sort::sort_batch; | ||
| use datafusion_physical_plan::union::UnionExec; | ||
| use datafusion_physical_plan::{ExecutionPlan, Partitioning}; | ||
| use futures::StreamExt; | ||
|
|
||
| const NUM_BATCHES: usize = 200; | ||
| const ROWS_PER_BATCH: usize = 10; | ||
|
|
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| fn non_nullable_schema() -> Arc<Schema> { | ||
| Arc::new(Schema::new(vec![ | ||
| Field::new("key", DataType::Int64, false), | ||
| Field::new("val", DataType::Int64, false), | ||
| ])) | ||
| } | ||
|
|
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| fn nullable_schema() -> Arc<Schema> { | ||
| Arc::new(Schema::new(vec![ | ||
| Field::new("key", DataType::Int64, false), | ||
| Field::new("val", DataType::Int64, true), | ||
| ])) | ||
| } | ||
|
|
||
| fn non_nullable_batches() -> Vec<RecordBatch> { | ||
| (0..NUM_BATCHES) | ||
| .map(|i| { | ||
| let start = (i * ROWS_PER_BATCH) as i64; | ||
| let keys: Vec<i64> = (start..start + ROWS_PER_BATCH as i64).collect(); | ||
| RecordBatch::try_new( | ||
| non_nullable_schema(), | ||
| vec![ | ||
| Arc::new(Int64Array::from(keys)), | ||
| Arc::new(Int64Array::from(vec![0i64; ROWS_PER_BATCH])), | ||
| ], | ||
| ) | ||
| .unwrap() | ||
| }) | ||
| .collect() | ||
| } | ||
|
|
||
| fn nullable_batches() -> Vec<RecordBatch> { | ||
| (0..NUM_BATCHES) | ||
| .map(|i| { | ||
| let start = (i * ROWS_PER_BATCH) as i64; | ||
| let keys: Vec<i64> = (start..start + ROWS_PER_BATCH as i64).collect(); | ||
| let vals: Vec<Option<i64>> = (0..ROWS_PER_BATCH) | ||
| .map(|j| if j % 3 == 1 { None } else { Some(j as i64) }) | ||
| .collect(); | ||
| RecordBatch::try_new( | ||
| nullable_schema(), | ||
| vec![ | ||
| Arc::new(Int64Array::from(keys)), | ||
| Arc::new(Int64Array::from(vals)), | ||
| ], | ||
| ) | ||
| .unwrap() | ||
| }) | ||
| .collect() | ||
| } | ||
|
|
||
| fn build_task_ctx(pool_size: usize) -> Arc<datafusion_execution::TaskContext> { | ||
| let session_config = SessionConfig::new().with_batch_size(2); | ||
| let runtime = RuntimeEnvBuilder::new() | ||
| .with_memory_pool(Arc::new(FairSpillPool::new(pool_size))) | ||
| .build_arc() | ||
| .unwrap(); | ||
| Arc::new( | ||
| datafusion_execution::TaskContext::default() | ||
| .with_session_config(session_config) | ||
| .with_runtime(runtime), | ||
| ) | ||
| } | ||
|
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||
| /// Exercises spilling through UnionExec -> RepartitionExec where union children | ||
| /// have mismatched nullability (one child's `val` is non-nullable, the other's | ||
| /// is nullable with NULLs). A tiny FairSpillPool forces all batches to spill. | ||
| /// | ||
| /// UnionExec returns child streams without schema coercion, so batches from | ||
| /// different children carry different per-field nullability into the shared | ||
| /// SpillPool. The IPC writer must use the SpillManager's canonical (nullable) | ||
| /// schema — not the first batch's schema — so readback batches are valid. | ||
| /// | ||
| /// Otherwise, sort_batch will panic with | ||
| /// `Column 'val' is declared as non-nullable but contains null values` | ||
| #[tokio::test] | ||
| async fn test_sort_union_repartition_spill_mixed_nullability() { | ||
| let non_nullable_exec = MemorySourceConfig::try_new_exec( | ||
| &[non_nullable_batches()], | ||
| non_nullable_schema(), | ||
| None, | ||
| ) | ||
| .unwrap(); | ||
|
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||
| let nullable_exec = | ||
| MemorySourceConfig::try_new_exec(&[nullable_batches()], nullable_schema(), None) | ||
| .unwrap(); | ||
|
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| let union_exec = UnionExec::try_new(vec![non_nullable_exec, nullable_exec]).unwrap(); | ||
| assert!(union_exec.schema().field(1).is_nullable()); | ||
|
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| let repartition = Arc::new( | ||
| RepartitionExec::try_new(union_exec, Partitioning::RoundRobinBatch(1)).unwrap(), | ||
| ); | ||
|
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| let task_ctx = build_task_ctx(200); | ||
| let mut stream = repartition.execute(0, task_ctx).unwrap(); | ||
|
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| let sort_expr = LexOrdering::new(vec![PhysicalSortExpr { | ||
| expr: col("key", &nullable_schema()).unwrap(), | ||
| options: SortOptions::default(), | ||
| }]) | ||
| .unwrap(); | ||
|
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| let mut total_rows = 0usize; | ||
| let mut total_nulls = 0usize; | ||
| while let Some(result) = stream.next().await { | ||
| let batch = result.unwrap(); | ||
|
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| let batch = sort_batch(&batch, &sort_expr, None).unwrap(); | ||
|
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| total_rows += batch.num_rows(); | ||
| total_nulls += batch.column(1).null_count(); | ||
| } | ||
|
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| assert_eq!( | ||
| total_rows, | ||
| NUM_BATCHES * ROWS_PER_BATCH * 2, | ||
| "All rows from both UNION branches should be present" | ||
| ); | ||
| assert!( | ||
| total_nulls > 0, | ||
| "Expected some null values in output (i.e. nullable batches were processed)" | ||
| ); | ||
| } |
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this is the code change. The rest are test changes