Support (order by / sort) for DataFrameWriteOptions

datafusion/core/src/dataframe/mod.rs

@@ -77,6 +77,9 @@ pub struct DataFrameWriteOptions {
     /// Sets which columns should be used for hive-style partitioned writes by name.
     /// Can be set to empty vec![] for non-partitioned writes.
     partition_by: Vec<String>,
+    /// Sets which columns should be used for sorting the output by name.
+    /// Can be set to empty vec![] for non-sorted writes.
+    sort_by: Vec<SortExpr>,
 }
 
 impl DataFrameWriteOptions {
@@ -86,6 +89,7 @@ impl DataFrameWriteOptions {
             insert_op: InsertOp::Append,
             single_file_output: false,
             partition_by: vec![],
+            sort_by: vec![],
         }
     }
 
@@ -106,6 +110,12 @@ impl DataFrameWriteOptions {
         self.partition_by = partition_by;
         self
     }
+
+    /// Sets the sort_by columns for output sorting
+    pub fn with_sort_by(mut self, sort_by: Vec<SortExpr>) -> Self {
+        self.sort_by = sort_by;
+        self
+    }
 }
 
 impl Default for DataFrameWriteOptions {
@@ -1517,8 +1527,17 @@ impl DataFrame {
         write_options: DataFrameWriteOptions,
     ) -> Result<Vec<RecordBatch>, DataFusionError> {
         let arrow_schema = Schema::from(self.schema());
+
+        let plan = if write_options.sort_by.is_empty() {
+            self.plan
+        } else {
+            LogicalPlanBuilder::from(self.plan)
+                .sort(write_options.sort_by)?
+                .build()?
+        };
+
         let plan = LogicalPlanBuilder::insert_into(
-            self.plan,
+            plan,
             table_name.to_owned(),
             &arrow_schema,
             write_options.insert_op,
@@ -1577,8 +1596,16 @@ impl DataFrame {
 
         let file_type = format_as_file_type(format);
 
+        let plan = if options.sort_by.is_empty() {
+            self.plan
+        } else {
+            LogicalPlanBuilder::from(self.plan)
+                .sort(options.sort_by)?
+                .build()?
+        };
+
         let plan = LogicalPlanBuilder::copy_to(
-            self.plan,
+            plan,
             path.into(),
             file_type,
             HashMap::new(),
@@ -1638,8 +1665,16 @@ impl DataFrame {
 
         let file_type = format_as_file_type(format);
 
+        let plan = if options.sort_by.is_empty() {
+            self.plan
+        } else {
+            LogicalPlanBuilder::from(self.plan)
+                .sort(options.sort_by)?
+                .build()?
+        };
+
         let plan = LogicalPlanBuilder::copy_to(
-            self.plan,
+            plan,
             path.into(),
             file_type,
             Default::default(),
@@ -1940,6 +1975,7 @@ mod tests {
     use crate::physical_plan::{ColumnarValue, Partitioning, PhysicalExpr};
     use crate::test_util::{register_aggregate_csv, test_table, test_table_with_name};
 
+    use crate::prelude::{CsvReadOptions, NdJsonReadOptions, ParquetReadOptions};
     use arrow::array::Int32Array;
     use datafusion_common::{assert_batches_eq, Constraint, Constraints, ScalarValue};
     use datafusion_common_runtime::SpawnedTask;
@@ -1954,6 +1990,7 @@ mod tests {
     use datafusion_physical_expr::expressions::Column;
     use datafusion_physical_plan::{get_plan_string, ExecutionPlanProperties};
     use sqlparser::ast::NullTreatment;
+    use tempfile::TempDir;
 
     // Get string representation of the plan
     async fn assert_physical_plan(df: &DataFrame, expected: Vec<&str>) {
@@ -4057,4 +4094,178 @@ mod tests {
 
         Ok(())
     }
+
+    // Test issue: https://github.com/apache/datafusion/issues/13873
+    #[tokio::test]
+    async fn write_parquet_with_order() -> Result<()> {
+        let tmp_dir = TempDir::new()?;
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("a", DataType::Int32, true),
+            Field::new("b", DataType::Int32, true),
+        ]));
+
+        let ctx = SessionContext::new();
+        let write_df = ctx.read_batch(RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 5, 7, 3, 2])),
+                Arc::new(Int32Array::from(vec![2, 3, 4, 5, 6])),
+            ],
+        )?)?;
+
+        let test_path = tmp_dir.path().join("test.parquet");
+
+        write_df
+            .clone()
+            .write_parquet(
+                test_path.to_str().unwrap(),
+                DataFrameWriteOptions::new()
+                    .with_sort_by(vec![col("a").sort(true, true)]),
+                None,
+            )
+            .await?;
+
+        let ctx = SessionContext::new();
+        ctx.register_parquet(
+            "data",
+            test_path.to_str().unwrap(),
+            ParquetReadOptions::default(),
+        )
+        .await?;
+
+        let df = ctx.sql("SELECT * FROM data").await?;
+        let results = df.collect().await?;
+
+        assert_batches_eq!(
+            &[
+                "+---+---+",
+                "| a | b |",
+                "+---+---+",
+                "| 1 | 2 |",
+                "| 2 | 6 |",
+                "| 3 | 5 |",
+                "| 5 | 3 |",
+                "| 7 | 4 |",
+                "+---+---+",
+            ],
+            &results
+        );
+        Ok(())
+    }
+
+    // Test issue: https://github.com/apache/datafusion/issues/13873
+    #[tokio::test]
+    async fn write_csv_with_order() -> Result<()> {
+        let tmp_dir = TempDir::new()?;
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("a", DataType::Int32, true),
+            Field::new("b", DataType::Int32, true),
+        ]));
+
+        let ctx = SessionContext::new();
+        let write_df = ctx.read_batch(RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 5, 7, 3, 2])),
+                Arc::new(Int32Array::from(vec![2, 3, 4, 5, 6])),
+            ],
+        )?)?;
+
+        let test_path = tmp_dir.path().join("test.csv");
+
+        write_df
+            .clone()
+            .write_csv(
+                test_path.to_str().unwrap(),
+                DataFrameWriteOptions::new()
+                    .with_sort_by(vec![col("a").sort(true, true)]),
+                None,
+            )
+            .await?;
+
+        let ctx = SessionContext::new();
+        ctx.register_csv(
+            "data",
+            test_path.to_str().unwrap(),
+            CsvReadOptions::new().schema(&schema),
+        )
+        .await?;
+
+        let df = ctx.sql("SELECT * FROM data").await?;
+        let results = df.collect().await?;
+
+        assert_batches_eq!(
+            &[
+                "+---+---+",
+                "| a | b |",
+                "+---+---+",
+                "| 1 | 2 |",
+                "| 2 | 6 |",
+                "| 3 | 5 |",
+                "| 5 | 3 |",
+                "| 7 | 4 |",
+                "+---+---+",
+            ],
+            &results
+        );
+        Ok(())
+    }
+
+    // Test issue: https://github.com/apache/datafusion/issues/13873
+    #[tokio::test]
+    async fn write_json_with_order() -> Result<()> {
+        let tmp_dir = TempDir::new()?;
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("a", DataType::Int32, true),
+            Field::new("b", DataType::Int32, true),
+        ]));
+
+        let ctx = SessionContext::new();
+        let write_df = ctx.read_batch(RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 5, 7, 3, 2])),
+                Arc::new(Int32Array::from(vec![2, 3, 4, 5, 6])),
+            ],
+        )?)?;
+
+        let test_path = tmp_dir.path().join("test.json");
+
+        write_df
+            .clone()
+            .write_json(
+                test_path.to_str().unwrap(),
+                DataFrameWriteOptions::new()
+                    .with_sort_by(vec![col("a").sort(true, true)]),
+                None,
+            )
+            .await?;
+
+        let ctx = SessionContext::new();
+        ctx.register_json(
+            "data",
+            test_path.to_str().unwrap(),
+            NdJsonReadOptions::default().schema(&schema),
+        )
+        .await?;
+
+        let df = ctx.sql("SELECT * FROM data").await?;
+        let results = df.collect().await?;
+
+        assert_batches_eq!(
+            &[
+                "+---+---+",
+                "| a | b |",
+                "+---+---+",
+                "| 1 | 2 |",
+                "| 2 | 6 |",
+                "| 3 | 5 |",
+                "| 5 | 3 |",
+                "| 7 | 4 |",
+                "+---+---+",
+            ],
+            &results
+        );
+        Ok(())
+    }
 }

datafusion/core/src/dataframe/parquet.rs

@@ -74,8 +74,16 @@ impl DataFrame {
 
         let file_type = format_as_file_type(format);
 
+        let plan = if options.sort_by.is_empty() {
+            self.plan
+        } else {
+            LogicalPlanBuilder::from(self.plan)
+                .sort(options.sort_by)?
+                .build()?
+        };
+
         let plan = LogicalPlanBuilder::copy_to(
-            self.plan,
+            plan,
             path.into(),
             file_type,
             Default::default(),