Separating Benchmarks for physical sorted union over large columns in SQL planner based on Datatype (#18599)

## Which issue does this PR close?

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 - as discussed in #17261


## Rationale for this change
Logical Plan for datatype Int64 and UInt64 differs, UInt64 Logical
Plan's Union are wrapped up in Projection, and EliminateNestedUnion
OptimezerRule is not applied leading to significantly longer execution
time.
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## What changes are included in this PR?
Separating Benchmarks based on datatype, converting a datatype specific
function to a generic one.
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## Are these changes tested?
Yes.
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## Are there any user-facing changes?
No, benchmarks only.
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---------

Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>

Author: logan-keede

datafusion/core/benches/sql_planner.rs

@@ -23,13 +23,17 @@ extern crate datafusion;
 mod data_utils;
 
 use crate::criterion::Criterion;
+use arrow::array::PrimitiveArray;
 use arrow::array::{ArrayRef, RecordBatch};
+use arrow::datatypes::ArrowNativeTypeOp;
+use arrow::datatypes::ArrowPrimitiveType;
 use arrow::datatypes::{DataType, Field, Fields, Schema};
 use criterion::Bencher;
 use datafusion::datasource::MemTable;
 use datafusion::execution::context::SessionContext;
 use datafusion_common::{config::Dialect, ScalarValue};
 use datafusion_expr::col;
+use rand_distr::num_traits::NumCast;
 use std::hint::black_box;
 use std::path::PathBuf;
 use std::sync::Arc;
@@ -155,18 +159,30 @@ fn benchmark_with_param_values_many_columns(
 /// 0,100...9900
 /// 0,200...19800
 /// 0,300...29700
-fn register_union_order_table(ctx: &SessionContext, num_columns: usize, num_rows: usize) {
-    // ("c0", [0, 0, ...])
-    // ("c1": [100, 200, ...])
-    // etc
-    let iter = (0..num_columns).map(|i| i as u64).map(|i| {
-        let array: ArrayRef = Arc::new(arrow::array::UInt64Array::from_iter_values(
-            (0..num_rows)
-                .map(|j| j as u64 * 100 + i)
-                .collect::<Vec<_>>(),
-        ));
+fn register_union_order_table_generic<T>(
+    ctx: &SessionContext,
+    num_columns: usize,
+    num_rows: usize,
+) where
+    T: ArrowPrimitiveType,
+    T::Native: ArrowNativeTypeOp + NumCast,
+{
+    let iter = (0..num_columns).map(|i| {
+        let array_data: Vec<T::Native> = (0..num_rows)
+            .map(|j| {
+                let value = (j as u64) * 100 + (i as u64);
+                <T::Native as NumCast>::from(value).unwrap_or_else(|| {
+                    panic!("Failed to cast numeric value to Native type")
+                })
+            })
+            .collect();
+
+        // Use PrimitiveArray which is generic over the ArrowPrimitiveType T
+        let array: ArrayRef = Arc::new(PrimitiveArray::<T>::from_iter_values(array_data));
+
         (format!("c{i}"), array)
     });
+
     let batch = RecordBatch::try_from_iter(iter).unwrap();
     let schema = batch.schema();
     let partitions = vec![vec![batch]];
@@ -183,7 +199,6 @@ fn register_union_order_table(ctx: &SessionContext, num_columns: usize, num_rows
 
     ctx.register_table("t", Arc::new(table)).unwrap();
 }
-
 /// return a query like
 /// ```sql
 /// select c1, 2 as c2, ... n as cn from t ORDER BY c1
@@ -403,13 +418,40 @@ fn criterion_benchmark(c: &mut Criterion) {
 
     // -- Sorted Queries --
     // 100, 200 && 300 is taking too long - https://github.com/apache/datafusion/issues/18366
+    // Logical Plan for datatype Int64 and UInt64 differs, UInt64 Logical Plan's Union are wrapped
+    // up in Projection, and EliminateNestedUnion OptimezerRule is not applied leading to significantly
+    // longer execution time.
+    // https://github.com/apache/datafusion/issues/17261
+
     for column_count in [10, 50 /* 100, 200, 300 */] {
-        register_union_order_table(&ctx, column_count, 1000);
+        register_union_order_table_generic::<arrow::datatypes::Int64Type>(
+            &ctx,
+            column_count,
+            1000,
+        );
 
         // this query has many expressions in its sort order so stresses
         // order equivalence validation
         c.bench_function(
-            &format!("physical_sorted_union_order_by_{column_count}"),
+            &format!("physical_sorted_union_order_by_{column_count}_int64"),
+            |b| {
+                // SELECT ... UNION ALL ...
+                let query = union_orderby_query(column_count);
+                b.iter(|| physical_plan(&ctx, &rt, &query))
+            },
+        );
+
+        let _ = ctx.deregister_table("t");
+    }
+
+    for column_count in [10, 50 /* 100, 200, 300 */] {
+        register_union_order_table_generic::<arrow::datatypes::UInt64Type>(
+            &ctx,
+            column_count,
+            1000,
+        );
+        c.bench_function(
+            &format!("physical_sorted_union_order_by_{column_count}_uint64"),
             |b| {
                 // SELECT ... UNION ALL ...
                 let query = union_orderby_query(column_count);