martin-g commented on code in PR #19042: URL: https://github.com/apache/datafusion/pull/19042#discussion_r2581331565
########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', + verify: bool = True +): + """Sort parquet file by EventTime column with optimized settings.""" + + input_file = Path(input_path) + output_file = Path(output_path) + + if not input_file.exists(): + print(f"Error: Input file not found: {input_file}") + sys.exit(1) + + if output_file.exists(): + print(f"Sorted file already exists: {output_file}") + if verify: + verify_sorted_file(output_file) + return + + try: + print(f"Reading {input_file.name}...") + table = pq.read_table(str(input_file)) + + print(f"Original table has {len(table):,} rows") + print("Sorting by EventTime...") + + # Sort the table by EventTime + sorted_indices = pc.sort_indices(table, sort_keys=[("EventTime", "ascending")]) + sorted_table = pc.take(table, sorted_indices) + + print(f"Sorted table has {len(sorted_table):,} rows") + + # Verify sort + event_times = sorted_table.column('EventTime').to_pylist() + if event_times and verify: + print(f"First EventTime: {event_times[0]}") + print(f"Last EventTime: {event_times[-1]}") + # Verify ascending order + is_sorted = all(event_times[i] <= event_times[i+1] for i in range(min(1000, len(event_times)-1))) + print(f"Sort verification (first 1000 rows): {'✓ PASS' if is_sorted else '✗ FAIL'}") + + print(f"Writing sorted file to {output_file}...") + print(f" Row group size: {row_group_size:,} rows") + print(f" Compression: {compression}") + + # Write sorted table with optimized settings + pq.write_table( + sorted_table, + str(output_file), + compression=compression, + use_dictionary=True, + write_statistics=True, + # Optimize row group size for better performance + row_group_size=row_group_size, + # Set data page size (1MB is good for most cases) + data_page_size=1024 * 1024, + # Use v2 data page format for better compression + use_deprecated_int96_timestamps=False, + coerce_timestamps='us', # Use microsecond precision + # Batch size for writing + write_batch_size=min(row_group_size, 1024 * 64), + # Enable compression for all columns + compression_level=None, # Use default compression level + ) + + # Report results + input_size_mb = input_file.stat().st_size / (1024**2) + output_size_mb = output_file.stat().st_size / (1024**2) + + # Read metadata to verify row groups + parquet_file = pq.ParquetFile(str(output_file)) + num_row_groups = parquet_file.num_row_groups + + print(f"\n✓ Successfully created sorted file!") + print(f" Input: {input_size_mb:.1f} MB") + print(f" Output: {output_size_mb:.1f} MB") + print(f" Compression ratio: {input_size_mb/output_size_mb:.2f}x") + print(f"\nRow Group Statistics:") + print(f" Total row groups: {num_row_groups}") + print(f" Total rows: {len(sorted_table):,}") + + # Show row group details + for i in range(min(3, num_row_groups)): + rg_metadata = parquet_file.metadata.row_group(i) + print(f" Row group {i}: {rg_metadata.num_rows:,} rows, {rg_metadata.total_byte_size / 1024**2:.1f} MB") + + if num_row_groups > 3: + print(f" ... and {num_row_groups - 3} more row groups") + + avg_rows_per_group = len(sorted_table) / num_row_groups if num_row_groups > 0 else 0 + print(f" Average rows per group: {avg_rows_per_group:,.0f}") + + except Exception as e: + print(f"Error: {e}") + import traceback + traceback.print_exc() + sys.exit(1) + + +def verify_sorted_file(file_path: Path): + """Verify that a parquet file is sorted by EventTime.""" + try: + print(f"Verifying sorted file: {file_path}") + parquet_file = pq.ParquetFile(str(file_path)) + + num_row_groups = parquet_file.num_row_groups + file_size_mb = file_path.stat().st_size / (1024**2) + + print(f" File size: {file_size_mb:.1f} MB") + print(f" Row groups: {num_row_groups}") + + # Read first and last row group to verify sort + first_rg = parquet_file.read_row_group(0) + last_rg = parquet_file.read_row_group(num_row_groups - 1) + + first_time = first_rg.column('EventTime')[0].as_py() + last_time = last_rg.column('EventTime')[-1].as_py() + + print(f" First EventTime: {first_time}") + print(f" Last EventTime: {last_time}") + print(f" Sorted: {'✓ YES' if first_time <= last_time else '✗ NO'}") + + except Exception as e: + print(f"Error during verification: {e}") + + +def main(): + parser = argparse.ArgumentParser( + description='Sort ClickBench parquet file by EventTime', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Basic usage (1M rows per group) + %(prog)s input.parquet output.parquet + + # Custom row group size (2M rows) + %(prog)s input.parquet output.parquet --row-group-size 2097152 + + # Use zstd compression + %(prog)s input.parquet output.parquet --compression zstd + + # Verify existing file + %(prog)s --verify-only output.parquet + """ + ) + + parser.add_argument( + 'input', + nargs='?', + help='Input parquet file path' + ) + parser.add_argument( + 'output', + nargs='?', + help='Output sorted parquet file path' + ) + parser.add_argument( + '--row-group-size', + type=int, + default=64 * 1024, # 64K rows + help='Number of rows per row group (default: 65536 = 64K)' + ) + parser.add_argument( + '--compression', + choices=['snappy', 'gzip', 'brotli', 'lz4', 'zstd', 'none'], + default='zstd', + help='Compression codec (default: zstd)' + ) + parser.add_argument( + '--compression-level', + type=int, + default=3, + help='Compression level (default: 3 for zstd)' + ) + parser.add_argument( + '--no-verify', + action='store_true', + help='Skip sort verification' + ) + parser.add_argument( + '--verify-only', + action='store_true', + help='Only verify an existing sorted file (no sorting)' + ) + + args = parser.parse_args() + + if args.verify_only: + if not args.input: + parser.error("--verify-only requires input file") + verify_sorted_file(Path(args.input)) + return + + if not args.input or not args.output: + parser.error("input and output paths are required") + + sort_clickbench_data( + args.input, + args.output, + row_group_size=args.row_group_size, + compression=args.compression, + verify=not args.no_verify + ) + + +if __name__ == '__main__': + if len(sys.argv) == 1: + print("Usage: python3 sort_clickbench_enhanced.py <input_file> <output_file>") Review Comment: ```suggestion print("Usage: python3 sort_clickbench.py <input_file> <output_file>") ``` ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 Review Comment: ```suggestion ``` ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', + verify: bool = True +): + """Sort parquet file by EventTime column with optimized settings.""" + + input_file = Path(input_path) + output_file = Path(output_path) + + if not input_file.exists(): + print(f"Error: Input file not found: {input_file}") + sys.exit(1) + + if output_file.exists(): + print(f"Sorted file already exists: {output_file}") + if verify: + verify_sorted_file(output_file) + return + + try: + print(f"Reading {input_file.name}...") + table = pq.read_table(str(input_file)) + + print(f"Original table has {len(table):,} rows") + print("Sorting by EventTime...") + + # Sort the table by EventTime + sorted_indices = pc.sort_indices(table, sort_keys=[("EventTime", "ascending")]) + sorted_table = pc.take(table, sorted_indices) + + print(f"Sorted table has {len(sorted_table):,} rows") + + # Verify sort + event_times = sorted_table.column('EventTime').to_pylist() + if event_times and verify: + print(f"First EventTime: {event_times[0]}") + print(f"Last EventTime: {event_times[-1]}") + # Verify ascending order + is_sorted = all(event_times[i] <= event_times[i+1] for i in range(min(1000, len(event_times)-1))) + print(f"Sort verification (first 1000 rows): {'✓ PASS' if is_sorted else '✗ FAIL'}") + + print(f"Writing sorted file to {output_file}...") + print(f" Row group size: {row_group_size:,} rows") + print(f" Compression: {compression}") + + # Write sorted table with optimized settings + pq.write_table( + sorted_table, + str(output_file), + compression=compression, + use_dictionary=True, + write_statistics=True, + # Optimize row group size for better performance + row_group_size=row_group_size, + # Set data page size (1MB is good for most cases) + data_page_size=1024 * 1024, + # Use v2 data page format for better compression + use_deprecated_int96_timestamps=False, + coerce_timestamps='us', # Use microsecond precision + # Batch size for writing + write_batch_size=min(row_group_size, 1024 * 64), + # Enable compression for all columns + compression_level=None, # Use default compression level + ) + + # Report results + input_size_mb = input_file.stat().st_size / (1024**2) + output_size_mb = output_file.stat().st_size / (1024**2) + + # Read metadata to verify row groups + parquet_file = pq.ParquetFile(str(output_file)) + num_row_groups = parquet_file.num_row_groups + + print(f"\n✓ Successfully created sorted file!") + print(f" Input: {input_size_mb:.1f} MB") + print(f" Output: {output_size_mb:.1f} MB") + print(f" Compression ratio: {input_size_mb/output_size_mb:.2f}x") + print(f"\nRow Group Statistics:") + print(f" Total row groups: {num_row_groups}") + print(f" Total rows: {len(sorted_table):,}") + + # Show row group details + for i in range(min(3, num_row_groups)): + rg_metadata = parquet_file.metadata.row_group(i) + print(f" Row group {i}: {rg_metadata.num_rows:,} rows, {rg_metadata.total_byte_size / 1024**2:.1f} MB") + + if num_row_groups > 3: + print(f" ... and {num_row_groups - 3} more row groups") + + avg_rows_per_group = len(sorted_table) / num_row_groups if num_row_groups > 0 else 0 + print(f" Average rows per group: {avg_rows_per_group:,.0f}") + + except Exception as e: + print(f"Error: {e}") + import traceback + traceback.print_exc() + sys.exit(1) + + +def verify_sorted_file(file_path: Path): + """Verify that a parquet file is sorted by EventTime.""" + try: + print(f"Verifying sorted file: {file_path}") + parquet_file = pq.ParquetFile(str(file_path)) + + num_row_groups = parquet_file.num_row_groups + file_size_mb = file_path.stat().st_size / (1024**2) + + print(f" File size: {file_size_mb:.1f} MB") + print(f" Row groups: {num_row_groups}") + + # Read first and last row group to verify sort + first_rg = parquet_file.read_row_group(0) + last_rg = parquet_file.read_row_group(num_row_groups - 1) + + first_time = first_rg.column('EventTime')[0].as_py() + last_time = last_rg.column('EventTime')[-1].as_py() + + print(f" First EventTime: {first_time}") + print(f" Last EventTime: {last_time}") + print(f" Sorted: {'✓ YES' if first_time <= last_time else '✗ NO'}") + + except Exception as e: + print(f"Error during verification: {e}") + + +def main(): + parser = argparse.ArgumentParser( + description='Sort ClickBench parquet file by EventTime', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Basic usage (1M rows per group) + %(prog)s input.parquet output.parquet + + # Custom row group size (2M rows) + %(prog)s input.parquet output.parquet --row-group-size 2097152 + + # Use zstd compression + %(prog)s input.parquet output.parquet --compression zstd + + # Verify existing file + %(prog)s --verify-only output.parquet + """ + ) + + parser.add_argument( + 'input', + nargs='?', + help='Input parquet file path' + ) + parser.add_argument( + 'output', + nargs='?', + help='Output sorted parquet file path' + ) + parser.add_argument( + '--row-group-size', + type=int, + default=64 * 1024, # 64K rows + help='Number of rows per row group (default: 65536 = 64K)' + ) + parser.add_argument( + '--compression', + choices=['snappy', 'gzip', 'brotli', 'lz4', 'zstd', 'none'], + default='zstd', + help='Compression codec (default: zstd)' + ) + parser.add_argument( + '--compression-level', Review Comment: The compression_level is ignored and None is always used - https://github.com/apache/datafusion/pull/19042/files#diff-e69296826ec4a87d5995601df87bb71ea4346532b1b4055641ca8959febe510aR104 ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', Review Comment: ```suggestion compression: str = 'zstd', ``` below it uses `zstd` as default - https://github.com/apache/datafusion/pull/19042/files#diff-e69296826ec4a87d5995601df87bb71ea4346532b1b4055641ca8959febe510aR207 ########## benchmarks/bench.sh: ########## @@ -1197,6 +1206,86 @@ compare_benchmarks() { } +# Sorted Data Benchmark Functions (Optimized for hits_0.parquet) +# Add these functions to bench.sh + +# Creates sorted ClickBench data from hits_0.parquet (partitioned dataset) +# The data is sorted by EventTime in ascending order +# Using hits_0.parquet (~150MB) instead of full hits.parquet (~14GB) for faster testing +data_sorted_clickbench() { + SORTED_FILE="${DATA_DIR}/hits_0_sorted.parquet" + ORIGINAL_FILE="${DATA_DIR}/hits_partitioned/hits_0.parquet" + + echo "Creating sorted ClickBench dataset from hits_0.parquet..." + + # Check if partitioned data exists + if [ ! -f "${ORIGINAL_FILE}" ]; then + echo "hits_partitioned/hits_0.parquet not found. Running data_clickbench_partitioned first..." + data_clickbench_partitioned + fi + + # Check if sorted file already exists + if [ -f "${SORTED_FILE}" ]; then + echo "Sorted hits_0.parquet already exists at ${SORTED_FILE}" + return 0 + fi + + echo "Sorting hits_0.parquet by EventTime (this takes ~10 seconds)..." + + # Ensure virtual environment exists and has pyarrow + if [ ! -d "$VIRTUAL_ENV" ]; then + echo "Creating virtual environment at $VIRTUAL_ENV..." + python3 -m venv "$VIRTUAL_ENV" + fi + + # Activate virtual environment + source "$VIRTUAL_ENV/bin/activate" + + # Check and install pyarrow if needed + if ! python3 -c "import pyarrow" 2>/dev/null; then + echo "Installing pyarrow (this may take a minute)..." + pip install --quiet pyarrow + fi + + # Use the standalone Python script to sort + python3 "${SCRIPT_DIR}"/sort_clickbench.py "${ORIGINAL_FILE}" "${SORTED_FILE}" + local result=$? + + # Deactivate virtual environment + deactivate + + if [ $result -eq 0 ]; then + echo "✓ Successfully created sorted ClickBench dataset" + return 0 + else + echo "✗ Error: Failed to create sorted dataset" + return 1 + fi +} + +# Sorted Data Benchmark Functions for bench.sh +# Add these functions to your bench.sh script Review Comment: What is the purpose of this comment ? ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', + verify: bool = True +): + """Sort parquet file by EventTime column with optimized settings.""" + + input_file = Path(input_path) + output_file = Path(output_path) + + if not input_file.exists(): + print(f"Error: Input file not found: {input_file}") + sys.exit(1) + + if output_file.exists(): + print(f"Sorted file already exists: {output_file}") + if verify: + verify_sorted_file(output_file) + return + + try: + print(f"Reading {input_file.name}...") + table = pq.read_table(str(input_file)) + + print(f"Original table has {len(table):,} rows") + print("Sorting by EventTime...") + + # Sort the table by EventTime + sorted_indices = pc.sort_indices(table, sort_keys=[("EventTime", "ascending")]) + sorted_table = pc.take(table, sorted_indices) + + print(f"Sorted table has {len(sorted_table):,} rows") + + # Verify sort + event_times = sorted_table.column('EventTime').to_pylist() + if event_times and verify: + print(f"First EventTime: {event_times[0]}") + print(f"Last EventTime: {event_times[-1]}") + # Verify ascending order + is_sorted = all(event_times[i] <= event_times[i+1] for i in range(min(1000, len(event_times)-1))) + print(f"Sort verification (first 1000 rows): {'✓ PASS' if is_sorted else '✗ FAIL'}") + + print(f"Writing sorted file to {output_file}...") + print(f" Row group size: {row_group_size:,} rows") + print(f" Compression: {compression}") + + # Write sorted table with optimized settings + pq.write_table( + sorted_table, + str(output_file), + compression=compression, + use_dictionary=True, + write_statistics=True, + # Optimize row group size for better performance + row_group_size=row_group_size, + # Set data page size (1MB is good for most cases) + data_page_size=1024 * 1024, + # Use v2 data page format for better compression + use_deprecated_int96_timestamps=False, + coerce_timestamps='us', # Use microsecond precision + # Batch size for writing + write_batch_size=min(row_group_size, 1024 * 64), + # Enable compression for all columns + compression_level=None, # Use default compression level + ) + + # Report results + input_size_mb = input_file.stat().st_size / (1024**2) + output_size_mb = output_file.stat().st_size / (1024**2) + + # Read metadata to verify row groups + parquet_file = pq.ParquetFile(str(output_file)) + num_row_groups = parquet_file.num_row_groups + + print(f"\n✓ Successfully created sorted file!") + print(f" Input: {input_size_mb:.1f} MB") + print(f" Output: {output_size_mb:.1f} MB") + print(f" Compression ratio: {input_size_mb/output_size_mb:.2f}x") + print(f"\nRow Group Statistics:") Review Comment: ```suggestion print("\nRow Group Statistics:") ``` ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default Review Comment: Below it says that the default is 64K - https://github.com/apache/datafusion/pull/19042/files#diff-e69296826ec4a87d5995601df87bb71ea4346532b1b4055641ca8959febe510aR201 ########## benchmarks/src/clickbench.rs: ########## @@ -78,6 +78,16 @@ 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 + #[structopt(long = "sorted-by")] + sorted_by: Option<String>, + + /// Sort order: ASC or DESC (default: ASC) + #[structopt(long = "sort-order", default_value = "ASC")] Review Comment: The user may provide any value here. Consider validating it with a custom parse function. ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', + verify: bool = True +): + """Sort parquet file by EventTime column with optimized settings.""" + + input_file = Path(input_path) + output_file = Path(output_path) + + if not input_file.exists(): + print(f"Error: Input file not found: {input_file}") + sys.exit(1) + + if output_file.exists(): + print(f"Sorted file already exists: {output_file}") + if verify: + verify_sorted_file(output_file) + return + + try: + print(f"Reading {input_file.name}...") + table = pq.read_table(str(input_file)) + + print(f"Original table has {len(table):,} rows") + print("Sorting by EventTime...") + + # Sort the table by EventTime + sorted_indices = pc.sort_indices(table, sort_keys=[("EventTime", "ascending")]) + sorted_table = pc.take(table, sorted_indices) + + print(f"Sorted table has {len(sorted_table):,} rows") + + # Verify sort + event_times = sorted_table.column('EventTime').to_pylist() + if event_times and verify: + print(f"First EventTime: {event_times[0]}") + print(f"Last EventTime: {event_times[-1]}") + # Verify ascending order + is_sorted = all(event_times[i] <= event_times[i+1] for i in range(min(1000, len(event_times)-1))) + print(f"Sort verification (first 1000 rows): {'✓ PASS' if is_sorted else '✗ FAIL'}") + + print(f"Writing sorted file to {output_file}...") + print(f" Row group size: {row_group_size:,} rows") + print(f" Compression: {compression}") + + # Write sorted table with optimized settings + pq.write_table( + sorted_table, + str(output_file), + compression=compression, + use_dictionary=True, + write_statistics=True, + # Optimize row group size for better performance + row_group_size=row_group_size, + # Set data page size (1MB is good for most cases) + data_page_size=1024 * 1024, + # Use v2 data page format for better compression + use_deprecated_int96_timestamps=False, + coerce_timestamps='us', # Use microsecond precision + # Batch size for writing + write_batch_size=min(row_group_size, 1024 * 64), + # Enable compression for all columns + compression_level=None, # Use default compression level + ) + + # Report results + input_size_mb = input_file.stat().st_size / (1024**2) + output_size_mb = output_file.stat().st_size / (1024**2) + + # Read metadata to verify row groups + parquet_file = pq.ParquetFile(str(output_file)) + num_row_groups = parquet_file.num_row_groups + + print(f"\n✓ Successfully created sorted file!") + print(f" Input: {input_size_mb:.1f} MB") + print(f" Output: {output_size_mb:.1f} MB") + print(f" Compression ratio: {input_size_mb/output_size_mb:.2f}x") + print(f"\nRow Group Statistics:") + print(f" Total row groups: {num_row_groups}") + print(f" Total rows: {len(sorted_table):,}") + + # Show row group details + for i in range(min(3, num_row_groups)): + rg_metadata = parquet_file.metadata.row_group(i) + print(f" Row group {i}: {rg_metadata.num_rows:,} rows, {rg_metadata.total_byte_size / 1024**2:.1f} MB") + + if num_row_groups > 3: + print(f" ... and {num_row_groups - 3} more row groups") + + avg_rows_per_group = len(sorted_table) / num_row_groups if num_row_groups > 0 else 0 + print(f" Average rows per group: {avg_rows_per_group:,.0f}") + + except Exception as e: + print(f"Error: {e}") + import traceback + traceback.print_exc() + sys.exit(1) + + +def verify_sorted_file(file_path: Path): + """Verify that a parquet file is sorted by EventTime.""" + try: + print(f"Verifying sorted file: {file_path}") + parquet_file = pq.ParquetFile(str(file_path)) + + num_row_groups = parquet_file.num_row_groups + file_size_mb = file_path.stat().st_size / (1024**2) + + print(f" File size: {file_size_mb:.1f} MB") + print(f" Row groups: {num_row_groups}") + + # Read first and last row group to verify sort + first_rg = parquet_file.read_row_group(0) + last_rg = parquet_file.read_row_group(num_row_groups - 1) + + first_time = first_rg.column('EventTime')[0].as_py() + last_time = last_rg.column('EventTime')[-1].as_py() + + print(f" First EventTime: {first_time}") + print(f" Last EventTime: {last_time}") + print(f" Sorted: {'✓ YES' if first_time <= last_time else '✗ NO'}") + + except Exception as e: + print(f"Error during verification: {e}") + + +def main(): + parser = argparse.ArgumentParser( + description='Sort ClickBench parquet file by EventTime', + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + # Basic usage (1M rows per group) Review Comment: Actually the default is 64K - https://github.com/apache/datafusion/pull/19042/files#diff-e69296826ec4a87d5995601df87bb71ea4346532b1b4055641ca8959febe510aR201 ########## benchmarks/src/clickbench.rs: ########## @@ -136,10 +158,24 @@ impl RunOpt { parquet_options.pushdown_filters = true; parquet_options.reorder_filters = true; } + + if self.sorted_by.is_some() { Review Comment: ```suggestion else if self.sorted_by.is_some() { ``` nit: I guess you kept them separate intentionally, so feel free to ignore this one ########## benchmarks/sort_clickbench.py: ########## @@ -0,0 +1,253 @@ +#!/usr/bin/env python3 + +# 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. + +#!/usr/bin/env python3 +""" +Sort ClickBench data by EventTime for reverse scan benchmark. +Enhanced version with configurable row group size and optimization options. +""" + +import sys +import argparse +from pathlib import Path + +try: + import pyarrow.parquet as pq + import pyarrow.compute as pc +except ImportError: + print("Error: pyarrow is not installed.") + print("Please install it with: pip install pyarrow") + sys.exit(1) + + +def sort_clickbench_data( + input_path: str, + output_path: str, + row_group_size: int = 1024 * 1024, # 1M rows default + compression: str = 'snappy', + verify: bool = True +): + """Sort parquet file by EventTime column with optimized settings.""" + + input_file = Path(input_path) + output_file = Path(output_path) + + if not input_file.exists(): + print(f"Error: Input file not found: {input_file}") + sys.exit(1) + + if output_file.exists(): + print(f"Sorted file already exists: {output_file}") + if verify: + verify_sorted_file(output_file) + return + + try: + print(f"Reading {input_file.name}...") + table = pq.read_table(str(input_file)) + + print(f"Original table has {len(table):,} rows") + print("Sorting by EventTime...") + + # Sort the table by EventTime + sorted_indices = pc.sort_indices(table, sort_keys=[("EventTime", "ascending")]) + sorted_table = pc.take(table, sorted_indices) + + print(f"Sorted table has {len(sorted_table):,} rows") + + # Verify sort + event_times = sorted_table.column('EventTime').to_pylist() + if event_times and verify: + print(f"First EventTime: {event_times[0]}") + print(f"Last EventTime: {event_times[-1]}") + # Verify ascending order + is_sorted = all(event_times[i] <= event_times[i+1] for i in range(min(1000, len(event_times)-1))) + print(f"Sort verification (first 1000 rows): {'✓ PASS' if is_sorted else '✗ FAIL'}") + + print(f"Writing sorted file to {output_file}...") + print(f" Row group size: {row_group_size:,} rows") + print(f" Compression: {compression}") + + # Write sorted table with optimized settings + pq.write_table( + sorted_table, + str(output_file), + compression=compression, + use_dictionary=True, + write_statistics=True, + # Optimize row group size for better performance + row_group_size=row_group_size, + # Set data page size (1MB is good for most cases) + data_page_size=1024 * 1024, + # Use v2 data page format for better compression + use_deprecated_int96_timestamps=False, + coerce_timestamps='us', # Use microsecond precision + # Batch size for writing + write_batch_size=min(row_group_size, 1024 * 64), + # Enable compression for all columns + compression_level=None, # Use default compression level + ) + + # Report results + input_size_mb = input_file.stat().st_size / (1024**2) + output_size_mb = output_file.stat().st_size / (1024**2) + + # Read metadata to verify row groups + parquet_file = pq.ParquetFile(str(output_file)) + num_row_groups = parquet_file.num_row_groups + + print(f"\n✓ Successfully created sorted file!") Review Comment: ```suggestion print("\n✓ Successfully created sorted file!") ``` ########## benchmarks/bench.sh: ########## @@ -1197,6 +1206,86 @@ compare_benchmarks() { } +# Sorted Data Benchmark Functions (Optimized for hits_0.parquet) +# Add these functions to bench.sh Review Comment: What is the purpose of this comment ? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
