Add sorted data benchmark.

benchmarks/README.md

@@ -787,3 +787,41 @@ Getting results...
 cancelling thread
 done dropping runtime in 83.531417ms
 ```
+
+## Sorted Data Benchmarks
+
+### Data Sorted ClickBench
+
+Benchmark for queries on pre-sorted data to test sort order optimization.
+This benchmark uses a subset of the ClickBench dataset (hits.parquet, ~14GB) that has been pre-sorted by the EventTime column. The queries are designed to test DataFusion's performance when the data is already sorted as is common in timeseries workloads.
+
+The benchmark includes queries that:
+- Scan pre-sorted data with ORDER BY clauses that match the sort order
+- Test reverse scans on sorted data
+- Verify the performance result
+
+#### Generating Sorted Data
+
+The sorted dataset is automatically generated from the ClickBench partitioned dataset. You can configure the memory used during the sorting process with the `DATAFUSION_MEMORY_GB` environment variable. The default memory limit is 12GB.
+```bash
+./bench.sh data data_sorted_clickbench
+```
+
+To create the sorted dataset, for example with 16GB of memory, run:
+
+```bash
+DATAFUSION_MEMORY_GB=16 ./bench.sh data data_sorted_clickbench
+```
+
+This command will:
+1. Download the ClickBench partitioned dataset if not present
+2. Sort hits.parquet by EventTime in ascending order
+3. Save the sorted file as hits_sorted.parquet
+
+#### Running the Benchmark
+
+```bash
+./bench.sh run data_sorted_clickbench
+```
+
+This runs queries against the pre-sorted dataset with the `--sorted-by EventTime` flag, which informs DataFusion that the data is pre-sorted, allowing it to optimize away redundant sort operations.

benchmarks/bench.sh

@@ -99,6 +99,9 @@ clickbench_partitioned: ClickBench queries against partitioned (100 files) parqu
 clickbench_pushdown:    ClickBench queries against partitioned (100 files) parquet w/ filter_pushdown enabled
 clickbench_extended:    ClickBench \"inspired\" queries against a single parquet (DataFusion specific)
 
+# Sorted Data Benchmarks (ORDER BY Optimization)
+clickbench_sorted:     ClickBench queries on pre-sorted data using prefer_existing_sort (tests sort elimination optimization)
+
 # H2O.ai Benchmarks (Group By, Join, Window)
 h2o_small:                      h2oai benchmark with small dataset (1e7 rows) for groupby,  default file format is csv
 h2o_medium:                     h2oai benchmark with medium dataset (1e8 rows) for groupby, default file format is csv
@@ -318,6 +321,9 @@ main() {
                 compile_profile)
                     data_tpch "1" "parquet"
                     ;;
+                clickbench_sorted)
+                    clickbench_sorted
+                    ;;
                 *)
                     echo "Error: unknown benchmark '$BENCHMARK' for data generation"
                     usage
@@ -449,7 +455,7 @@ main() {
                 h2o_medium_window)
                     run_h2o_window "MEDIUM" "CSV" "window"
                     ;;
-                h2o_big_window) 
+                h2o_big_window)
                     run_h2o_window "BIG" "CSV" "window"
                     ;;
                 h2o_small_parquet)
@@ -501,6 +507,9 @@ main() {
                 compile_profile)
                     run_compile_profile "${PROFILE_ARGS[@]}"
                     ;;
+                clickbench_sorted)
+                    run_clickbench_sorted
+                    ;;
                 *)
                     echo "Error: unknown benchmark '$BENCHMARK' for run"
                     usage
@@ -1201,6 +1210,113 @@ compare_benchmarks() {
 
 }
 
+# Creates sorted ClickBench data from hits.parquet (full dataset)
+# The data is sorted by EventTime in ascending order
+# Uses datafusion-cli to reduce dependencies
+clickbench_sorted() {
+    SORTED_FILE="${DATA_DIR}/hits_sorted.parquet"
+    ORIGINAL_FILE="${DATA_DIR}/hits.parquet"
+
+    # Default memory limit is 12GB, can be overridden with DATAFUSION_MEMORY_GB env var
+    MEMORY_LIMIT_GB=${DATAFUSION_MEMORY_GB:-12}
+
+    echo "Creating sorted ClickBench dataset from hits.parquet..."
+    echo "Configuration:"
+    echo "  Memory limit: ${MEMORY_LIMIT_GB}G"
+    echo "  Row group size: 64K rows"
+    echo "  Compression: uncompressed"
+
+    if [ ! -f "${ORIGINAL_FILE}" ]; then
+        echo "hits.parquet not found. Running data_clickbench_1 first..."
+        data_clickbench_1
+    fi
+
+    if [ -f "${SORTED_FILE}" ]; then
+        echo "Sorted hits.parquet already exists at ${SORTED_FILE}"
+        return 0
+    fi
+
+    echo "Sorting hits.parquet by EventTime (this may take several minutes)..."
+
+    pushd "${DATAFUSION_DIR}" > /dev/null
+    echo "Building datafusion-cli..."
+    cargo build --release --bin datafusion-cli
+    DATAFUSION_CLI="${DATAFUSION_DIR}/target/release/datafusion-cli"
+    popd > /dev/null
+
+
+    START_TIME=$(date +%s)
+    echo "Start time: $(date '+%Y-%m-%d %H:%M:%S')"
+    echo "Using datafusion-cli to create sorted parquet file..."
+    "${DATAFUSION_CLI}" << EOF
+-- Memory and performance configuration
+SET datafusion.runtime.memory_limit = '${MEMORY_LIMIT_GB}G';
+SET datafusion.execution.spill_compression = 'uncompressed';
+SET datafusion.execution.sort_spill_reservation_bytes = 10485760; -- 10MB
+SET datafusion.execution.batch_size = 8192;
+SET datafusion.execution.target_partitions = 1;
+
+-- Parquet output configuration
+SET datafusion.execution.parquet.max_row_group_size = 65536;
+SET datafusion.execution.parquet.compression = 'uncompressed';
+
+-- Execute sort and write
+COPY (SELECT * FROM '${ORIGINAL_FILE}' ORDER BY "EventTime")
+TO '${SORTED_FILE}'
+STORED AS PARQUET;
+EOF
+
+    local result=$?
+
+    END_TIME=$(date +%s)
+    DURATION=$((END_TIME - START_TIME))
+    echo "End time: $(date '+%Y-%m-%d %H:%M:%S')"
+
+    if [ $result -eq 0 ]; then
+        echo "✓ Successfully created sorted ClickBench dataset"
+
+        INPUT_SIZE=$(stat -f%z "${ORIGINAL_FILE}" 2>/dev/null || stat -c%s "${ORIGINAL_FILE}" 2>/dev/null)
+        OUTPUT_SIZE=$(stat -f%z "${SORTED_FILE}" 2>/dev/null || stat -c%s "${SORTED_FILE}" 2>/dev/null)
+        INPUT_MB=$((INPUT_SIZE / 1024 / 1024))
+        OUTPUT_MB=$((OUTPUT_SIZE / 1024 / 1024))
+
+        echo "  Input:  ${INPUT_MB} MB"
+        echo "  Output: ${OUTPUT_MB} MB"
+
+        echo ""
+        echo "Time Statistics:"
+        echo "  Total duration: ${DURATION} seconds ($(printf '%02d:%02d:%02d' $((DURATION/3600)) $((DURATION%3600/60)) $((DURATION%60))))"
+        echo "  Throughput: $((INPUT_MB / DURATION)) MB/s"
+
+        return 0
+    else
+        echo "✗ Error: Failed to create sorted dataset"
+        echo "💡 Tip: Try increasing memory with: DATAFUSION_MEMORY_GB=16 ./bench.sh data clickbench_sorted"
+        return 1
+    fi
+}
+
+# Runs the sorted data benchmark with prefer_existing_sort configuration
+run_clickbench_sorted() {
+    RESULTS_FILE="${RESULTS_DIR}/clickbench_sorted.json"
+    echo "RESULTS_FILE: ${RESULTS_FILE}"
+    echo "Running sorted data benchmark with prefer_existing_sort optimization..."
+
+    # Ensure sorted data exists
+    clickbench_sorted
+
+    # Run benchmark with prefer_existing_sort configuration
+    # This allows DataFusion to optimize away redundant sorts while maintaining parallelism
+    debug_run $CARGO_COMMAND --bin dfbench -- clickbench \
+        --iterations 5 \
+        --path "${DATA_DIR}/hits_sorted.parquet" \
+        --queries-path "${SCRIPT_DIR}/queries/clickbench/queries/sorted_data" \
+        --sorted-by "EventTime" \
+        -c datafusion.optimizer.prefer_existing_sort=true \
+        -o "${RESULTS_FILE}" \
+        ${QUERY_ARG}
+}
+
 setup_venv() {
     python3 -m venv "$VIRTUAL_ENV"
     PATH=$VIRTUAL_ENV/bin:$PATH python3 -m pip install -r requirements.txt

benchmarks/queries/clickbench/queries/sorted_data/q0.sql

@@ -0,0 +1,3 @@
+-- Must set for ClickBench hits_partitioned dataset. See https://github.com/apache/datafusion/issues/16591
+-- set datafusion.execution.parquet.binary_as_string = true
+SELECT * FROM hits ORDER BY "EventTime" DESC limit 10;

benchmarks/src/clickbench.rs

@@ -78,6 +78,27 @@ pub struct RunOpt {
     /// If present, write results json here
     #[structopt(parse(from_os_str), short = "o", long = "output")]
     output_path: Option<PathBuf>,
+
+    /// Column name that the data is sorted by (e.g., "EventTime")
+    /// If specified, DataFusion will be informed that the data has this sort order
+    /// using CREATE EXTERNAL TABLE with WITH ORDER clause.
+    ///
+    /// Recommended to use with: -c datafusion.optimizer.prefer_existing_sort=true
+    /// This allows DataFusion to optimize away redundant sorts while maintaining
+    /// multi-core parallelism for other operations.
+    #[structopt(long = "sorted-by")]
+    sorted_by: Option<String>,
+
+    /// Sort order: ASC or DESC (default: ASC)
+    #[structopt(long = "sort-order", default_value = "ASC")]
+    sort_order: String,
+
+    /// Configuration options in the format key=value
+    /// Can be specified multiple times.
+    ///
+    /// Example: -c datafusion.optimizer.prefer_existing_sort=true
+    #[structopt(short = "c", long = "config")]
+    config_options: Vec<String>,
 }
 
 /// Get the SQL file path
@@ -125,6 +146,37 @@ impl RunOpt {
 
         // configure parquet options
         let mut config = self.common.config()?;
+
+        if self.sorted_by.is_some() {
+            println!("ℹ️  Data is registered with sort order");
+
+            let has_prefer_sort = self
+                .config_options
+                .iter()
+                .any(|opt| opt.contains("prefer_existing_sort=true"));
+
+            if !has_prefer_sort {
+                println!("ℹ️  Consider using -c datafusion.optimizer.prefer_existing_sort=true");
+                println!("ℹ️  to optimize queries while maintaining parallelism");
+            }
+        }
+
+        // Apply user-provided configuration options
+        for config_opt in &self.config_options {
+            let parts: Vec<&str> = config_opt.splitn(2, '=').collect();
+            if parts.len() != 2 {
+                return Err(exec_datafusion_err!(
+                    "Invalid config option format: '{}'. Expected 'key=value'",
+                    config_opt
+                ));
+            }
+            let key = parts[0];
+            let value = parts[1];
+
+            println!("Setting config: {key} = {value}");
+            config = config.set_str(key, value);
+        }
+
         {
             let parquet_options = &mut config.options_mut().execution.parquet;
             // The hits_partitioned dataset specifies string columns
@@ -136,10 +188,18 @@ impl RunOpt {
                 parquet_options.pushdown_filters = true;
                 parquet_options.reorder_filters = true;
             }
+
+            if self.sorted_by.is_some() {
+                // We should compare the dynamic topk optimization when data is sorted, so we make the
+                // assumption that filter pushdown is also enabled in this case.
+                parquet_options.pushdown_filters = true;
+                parquet_options.reorder_filters = true;
+            }
         }
 
         let rt_builder = self.common.runtime_env_builder()?;
         let ctx = SessionContext::new_with_config_rt(config, rt_builder.build_arc()?);
+
         self.register_hits(&ctx).await?;
 
         let mut benchmark_run = BenchmarkRun::new();
@@ -214,17 +274,54 @@ impl RunOpt {
     }
 
     /// Registers the `hits.parquet` as a table named `hits`
+    /// If sorted_by is specified, uses CREATE EXTERNAL TABLE with WITH ORDER
     async fn register_hits(&self, ctx: &SessionContext) -> Result<()> {
-        let options = Default::default();
         let path = self.path.as_os_str().to_str().unwrap();
-        ctx.register_parquet("hits", path, options)
-            .await
-            .map_err(|e| {
-                DataFusionError::Context(
-                    format!("Registering 'hits' as {path}"),
-                    Box::new(e),
-                )
-            })
+
+        // If sorted_by is specified, use CREATE EXTERNAL TABLE with WITH ORDER
+        if let Some(ref sort_column) = self.sorted_by {
+            println!(
+                "Registering table with sort order: {} {}",
+                sort_column, self.sort_order
+            );
+
+            // Escape column name with double quotes
+            let escaped_column = if sort_column.contains('"') {
+                sort_column.clone()
+            } else {
+                format!("\"{sort_column}\"")
+            };
+
+            // Build CREATE EXTERNAL TABLE DDL with WITH ORDER clause
+            // Schema will be automatically inferred from the Parquet file
+            let create_table_sql = format!(
+                "CREATE EXTERNAL TABLE hits \
+                 STORED AS PARQUET \
+                 LOCATION '{}' \
+                 WITH ORDER ({} {})",
+                path,
+                escaped_column,
+                self.sort_order.to_uppercase()
+            );
+
+            println!("Executing: {create_table_sql}");
+
+            // Execute the CREATE EXTERNAL TABLE statement
+            ctx.sql(&create_table_sql).await?.collect().await?;
+
+            Ok(())
+        } else {
+            // Original registration without sort order
+            let options = Default::default();
+            ctx.register_parquet("hits", path, options)
+                .await
+                .map_err(|e| {
+                    DataFusionError::Context(
+                        format!("Registering 'hits' as {path}"),
+                        Box::new(e),
+                    )
+                })
+        }
     }
 
     fn iterations(&self) -> usize {