xudong963 commented on code in PR #15503: URL: https://github.com/apache/datafusion/pull/15503#discussion_r2032603449
########## datafusion/core/tests/physical_optimizer/partition_statistics.rs: ########## @@ -0,0 +1,244 @@ +// 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. + +#[cfg(test)] +mod test { + use arrow_schema::{DataType, Field, Schema, SortOptions}; + use datafusion::datasource::listing::ListingTable; + use datafusion::prelude::SessionContext; + use datafusion_catalog::TableProvider; + use datafusion_common::stats::Precision; + use datafusion_common::{ColumnStatistics, ScalarValue, Statistics}; + use datafusion_execution::config::SessionConfig; + use datafusion_expr_common::operator::Operator; + use datafusion_physical_expr::expressions::{binary, lit, Column}; + use datafusion_physical_expr_common::physical_expr::PhysicalExpr; + use datafusion_physical_expr_common::sort_expr::{LexOrdering, PhysicalSortExpr}; + use datafusion_physical_plan::filter::FilterExec; + use datafusion_physical_plan::projection::ProjectionExec; + use datafusion_physical_plan::sorts::sort::SortExec; + use datafusion_physical_plan::union::UnionExec; + use datafusion_physical_plan::ExecutionPlan; + use std::sync::Arc; + + /// Creates a test table with statistics from the test data directory. + /// + /// This function: + /// - Creates an external table from './tests/data/test_statistics_per_partition' + /// - If we set the `target_partition` to `2, the data contains 2 partitions, each with 2 rows + /// - Each partition has an "id" column (INT) with the following values: + /// - First partition: [3, 4] + /// - Second partition: [1, 2] + /// - Each row is 110 bytes in size + /// + /// @param target_partition Optional parameter to set the target partitions + /// @return ExecutionPlan representing the scan of the table with statistics + async fn generate_listing_table_with_statistics( + target_partition: Option<usize>, + ) -> Arc<dyn ExecutionPlan> { + let mut session_config = SessionConfig::new().with_collect_statistics(true); + if let Some(partition) = target_partition { + session_config = session_config.with_target_partitions(partition); + } + let ctx = SessionContext::new_with_config(session_config); + // Create table with partition + let create_table_sql = "CREATE EXTERNAL TABLE t1 (id INT not null, date DATE) STORED AS PARQUET LOCATION './tests/data/test_statistics_per_partition' PARTITIONED BY (date) WITH ORDER (id ASC);"; + ctx.sql(create_table_sql) + .await + .unwrap() + .collect() + .await + .unwrap(); + let table = ctx.table_provider("t1").await.unwrap(); + let listing_table = table + .as_any() + .downcast_ref::<ListingTable>() + .unwrap() + .clone(); + listing_table + .scan(&ctx.state(), None, &[], None) + .await + .unwrap() + } + + /// Helper function to create expected statistics for a partition with Int32 column + fn create_partition_statistics( + num_rows: usize, + total_byte_size: usize, + min_value: i32, + max_value: i32, + include_date_column: bool, + ) -> Statistics { + let mut column_stats = vec![ColumnStatistics { + null_count: Precision::Exact(0), + max_value: Precision::Exact(ScalarValue::Int32(Some(max_value))), + min_value: Precision::Exact(ScalarValue::Int32(Some(min_value))), + sum_value: Precision::Absent, + distinct_count: Precision::Absent, + }]; + + if include_date_column { + column_stats.push(ColumnStatistics { + null_count: Precision::Absent, + max_value: Precision::Absent, + min_value: Precision::Absent, + sum_value: Precision::Absent, + distinct_count: Precision::Absent, + }); + } + + Statistics { + num_rows: Precision::Exact(num_rows), + total_byte_size: Precision::Exact(total_byte_size), + column_statistics: column_stats, + } + } + + #[tokio::test] + async fn test_statistics_by_partition_of_data_source() -> datafusion_common::Result<()> + { + let scan = generate_listing_table_with_statistics(Some(2)).await; + let statistics = scan.statistics_by_partition()?; + let expected_statistic_partition_1 = + create_partition_statistics(2, 110, 3, 4, true); + let expected_statistic_partition_2 = + create_partition_statistics(2, 110, 1, 2, true); + // Check the statistics of each partition + assert_eq!(statistics.len(), 2); + assert_eq!(statistics[0], expected_statistic_partition_1); + assert_eq!(statistics[1], expected_statistic_partition_2); + Ok(()) + } Review Comment: Done in https://github.com/apache/datafusion/pull/15503/commits/d94c149e574cf95738cb2b4c0805a20eb64ed284, now the tests look very promising! -- This is an automated message from the Apache Git Service. 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