revert schema change v2

xinlifoobar · Aug 4, 2024 · 1ccc740 · 1ccc740
1 parent 5d97345
commit 1ccc740
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Showing 6 changed files with 13 additions and 19 deletions.
diff --git a/datafusion/functions-aggregate/src/array_agg.rs b/datafusion/functions-aggregate/src/array_agg.rs
@@ -117,8 +117,7 @@ impl AggregateUDFImpl for ArrayAgg {
     }
 
     fn accumulator(&self, acc_args: AccumulatorArgs) -> Result<Box<dyn Accumulator>> {
-        let data_type =
-            acc_args.input_exprs[0].data_type(acc_args.schema)?;
+        let data_type = acc_args.input_exprs[0].data_type(acc_args.schema)?;
 
         if acc_args.is_distinct {
             return Ok(Box::new(DistinctArrayAggAccumulator::try_new(&data_type)?));

diff --git a/datafusion/functions-aggregate/src/average.rs b/datafusion/functions-aggregate/src/average.rs
@@ -93,8 +93,7 @@ impl AggregateUDFImpl for Avg {
         }
         use DataType::*;
         // instantiate specialized accumulator based for the type
-        let input_type =
-            acc_args.input_exprs[0].data_type(acc_args.schema)?;
+        let input_type = acc_args.input_exprs[0].data_type(acc_args.schema)?;
 
         match (&input_type, acc_args.data_type) {
             (Float64, Float64) => Ok(Box::<AvgAccumulator>::default()),

diff --git a/datafusion/functions-aggregate/src/count.rs b/datafusion/functions-aggregate/src/count.rs
@@ -148,8 +148,7 @@ impl AggregateUDFImpl for Count {
             return not_impl_err!("COUNT DISTINCT with multiple arguments");
         }
 
-        let data_type =
-            &acc_args.input_exprs[0].data_type(acc_args.schema)?;
+        let data_type = &acc_args.input_exprs[0].data_type(acc_args.schema)?;
         Ok(match data_type {
             // try and use a specialized accumulator if possible, otherwise fall back to generic accumulator
             DataType::Int8 => Box::new(

diff --git a/datafusion/physical-plan/src/aggregates/mod.rs b/datafusion/physical-plan/src/aggregates/mod.rs
@@ -1192,7 +1192,7 @@ mod tests {
     use arrow_array::{Float32Array, Int32Array};
     use datafusion_common::{
         assert_batches_eq, assert_batches_sorted_eq, internal_err, DFSchema, DFSchemaRef,
-        DataFusionError, ScalarValue, ToDFSchema,
+        DataFusionError, ScalarValue,
     };
     use datafusion_execution::config::SessionConfig;
     use datafusion_execution::memory_pool::FairSpillPool;
@@ -1349,7 +1349,7 @@ mod tests {
         };
 
         let aggregates = vec![AggregateExprBuilder::new(count_udaf(), vec![lit(1i8)])
-            .dfschema(Arc::clone(&input_schema).to_dfschema()?)
+            .schema(Arc::clone(&input_schema))
             .name("COUNT(1)")
             .logical_exprs(vec![datafusion_expr::lit(1i8)])
             .build()?];
@@ -1494,7 +1494,7 @@ mod tests {
         let aggregates: Vec<Arc<dyn AggregateExpr>> =
             vec![
                 AggregateExprBuilder::new(avg_udaf(), vec![col("b", &input_schema)?])
-                    .dfschema(Arc::clone(&input_schema).to_dfschema()?)
+                    .schema(Arc::clone(&input_schema))
                     .name("AVG(b)")
                     .build()?,
             ];
@@ -1790,7 +1790,7 @@ mod tests {
     // Median(a)
     fn test_median_agg_expr(schema: SchemaRef) -> Result<Arc<dyn AggregateExpr>> {
         AggregateExprBuilder::new(median_udaf(), vec![col("a", &schema)?])
-            .dfschema(schema.to_dfschema()?)
+            .schema(Arc::clone(&schema))
             .name("MEDIAN(a)")
             .build()
     }
@@ -1821,7 +1821,7 @@ mod tests {
         let aggregates_v2: Vec<Arc<dyn AggregateExpr>> =
             vec![
                 AggregateExprBuilder::new(avg_udaf(), vec![col("b", &input_schema)?])
-                    .dfschema(Arc::clone(&input_schema).to_dfschema()?)
+                    .schema(Arc::clone(&input_schema))
                     .name("AVG(b)")
                     .build()?,
             ];
@@ -1881,7 +1881,7 @@ mod tests {
         let aggregates: Vec<Arc<dyn AggregateExpr>> =
             vec![
                 AggregateExprBuilder::new(avg_udaf(), vec![col("a", &schema)?])
-                    .dfschema(Arc::clone(&schema).to_dfschema()?)
+                    .schema(Arc::clone(&schema))
                     .name("AVG(a)")
                     .build()?,
             ];
@@ -1921,7 +1921,7 @@ mod tests {
         let aggregates: Vec<Arc<dyn AggregateExpr>> =
             vec![
                 AggregateExprBuilder::new(avg_udaf(), vec![col("b", &schema)?])
-                    .dfschema(Arc::clone(&schema).to_dfschema()?)
+                    .schema(Arc::clone(&schema))
                     .name("AVG(b)")
                     .build()?,
             ];
@@ -2350,7 +2350,7 @@ mod tests {
 
         let aggregates: Vec<Arc<dyn AggregateExpr>> =
             vec![AggregateExprBuilder::new(count_udaf(), vec![lit(1)])
-                .dfschema(Arc::clone(&schema).to_dfschema()?)
+                .schema(Arc::clone(&schema))
                 .name("1")
                 .build()?];
 

diff --git a/datafusion/physical-plan/src/windows/mod.rs b/datafusion/physical-plan/src/windows/mod.rs
@@ -395,7 +395,6 @@ impl BuiltInWindowFunctionExpr for WindowUDFExpr {
     }
 }
 
-#[allow(clippy::needless_borrow)]
 pub(crate) fn calc_requirements<
     T: Borrow<Arc<dyn PhysicalExpr>>,
     S: Borrow<PhysicalSortExpr>,
@@ -413,7 +412,7 @@ pub(crate) fn calc_requirements<
         let PhysicalSortExpr { expr, options } = element.borrow();
         if !sort_reqs.iter().any(|e| e.expr.eq(expr)) {
             sort_reqs.push(PhysicalSortRequirement::new(
-                Arc::clone(&expr),
+                Arc::clone(expr),
                 Some(*options),
             ));
         }

diff --git a/datafusion/proto/tests/cases/roundtrip_physical_plan.rs b/datafusion/proto/tests/cases/roundtrip_physical_plan.rs
@@ -81,9 +81,7 @@ use datafusion_common::file_options::csv_writer::CsvWriterOptions;
 use datafusion_common::file_options::json_writer::JsonWriterOptions;
 use datafusion_common::parsers::CompressionTypeVariant;
 use datafusion_common::stats::Precision;
-use datafusion_common::{
-    internal_err, not_impl_err, DataFusionError, Result,
-};
+use datafusion_common::{internal_err, not_impl_err, DataFusionError, Result};
 use datafusion_expr::{
     Accumulator, AccumulatorFactoryFunction, AggregateUDF, ColumnarValue, ScalarUDF,
     Signature, SimpleAggregateUDF, WindowFrame, WindowFrameBound,