feat: Expand microbenchmarks

README.md

@@ -25,6 +25,9 @@ This repository is intended as a central resource for documentation and scripts
 industry standard TPC-H and TPC-DS benchmarks against DataFusion and its subprojects, as well as against other
 open-source query engines for comparison.
 
+Additionally, this repository contains [microbenchmarks](./microbenchmarks) for comparing individual SQL function
+performance between DataFusion and other engines like DuckDB.
+
 TPC-H and TPC-DS both operate on synthetic data, which can be generated at different "scale factors". A scale factor
 of 1 means that approximately 1 GB of CSV data is generated, and a scale factor of 1000 means that approximately 1 TB
 of data is generated.

microbenchmarks/README.md

@@ -0,0 +1,109 @@
+<!---
+  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.
+-->
+
+# Microbenchmarks
+
+This directory contains microbenchmarks for comparing DataFusion and DuckDB performance on individual SQL functions. Unlike the TPC-H and TPC-DS benchmarks which test full query execution, these microbenchmarks focus on the performance of specific SQL functions and expressions.
+
+## Overview
+
+The benchmarks generate synthetic data, write it to Parquet format, and then measure the execution time of various SQL functions across both DataFusion and DuckDB. Results include per-function timing comparisons and summary statistics.
+
+## Benchmark Suites
+
+Three benchmark suites are available:
+
+- **string**: String manipulation functions (trim, lower, upper, concat, substring, regex, etc.)
+- **temporal**: Date/time functions (extract, date_trunc, date_part, interval arithmetic, formatting)
+- **conditional**: Conditional expressions (CASE WHEN, COALESCE, NULLIF, GREATEST/LEAST)
+
+## Setup
+
+Create a virtual environment and install dependencies:
+
+```shell
+cd microbenchmarks
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+```
+
+## Usage
+
+Run a benchmark suite:
+
+```shell
+python string_functions_benchmark.py --suite <suite_name>
+```
+
+### Options
+
+| Option | Default | Description |
+|--------|---------|-------------|
+| `--suite` | `string` | Benchmark suite to run: `string`, `temporal`, or `conditional` |
+| `--rows` | `1000000` | Number of rows in the generated test data |
+| `--warmup` | `2` | Number of warmup iterations before timing |
+| `--iterations` | `5` | Number of timed iterations (results are averaged) |
+| `--output` | stdout | Output file path for markdown results |
+
+### Examples
+
+Run the string functions benchmark with default settings:
+
+```shell
+python string_functions_benchmark.py
+```
+
+Run the temporal functions benchmark with 10 million rows:
+
+```shell
+python string_functions_benchmark.py --suite temporal --rows 10000000
+```
+
+Run the conditional expressions benchmark and save results to a file:
+
+```shell
+python string_functions_benchmark.py --suite conditional --output results.md
+```
+
+## Output
+
+The benchmark outputs a markdown table comparing execution times:
+
+| Function | DataFusion (ms) | DuckDB (ms) | Speedup | Faster |
+|----------|----------------:|------------:|--------:|--------|
+| trim | 12.34 | 15.67 | 1.27x | DataFusion |
+| lower | 8.90 | 7.50 | 1.19x | DuckDB |
+| ... | ... | ... | ... | ... |
+
+A summary section shows overall statistics including how many functions each engine won and total execution times.
+
+## Adding New Benchmarks
+
+To add new functions to an existing suite, add a `BenchmarkFunction` entry to the appropriate list in `string_functions_benchmark.py`:
+
+```python
+BenchmarkFunction(
+    "function_name",
+    "datafusion_sql_expression({col})",
+    "duckdb_sql_expression({col})"
+)
+```
+
+The placeholders (e.g., `{col}`, `{str_col}`, `{ts_col}`) are replaced with actual column names at runtime.

microbenchmarks/requirements.txt

@@ -0,0 +1,3 @@
+pyarrow>=14.0.0
+datafusion==50.0.0
+duckdb==1.4.3