The benchmark generates the following output files:

benchmark_language.json – A summary file in JSON format containing: Data preparation time(s). Data writing time(s). Total execution time(s). Writing throughput (points/s)

memory_usage_{language}.csv – A CSV file tracking memory usage over time during execution.

Profile output files (for Python and C++): Flamegraph-related profiling data will be generated to assist with performance analysis.

python: tqdm

1. Clone TsFile Source Code

   Clone the latest TsFile repository from GitHub to your local machine.

2. Start Docker with Volume Mounts

   Launch a Docker container and mount the following directories into the container:

   1. The cloned TsFile source code
   2. The TsFile-benchmark repository itself
   3. A result directory, which should be mounted to /result inside the container to store output files

3. Build and Run Benchmarks in Docker The Docker container will automatically:

   1. Compile and install the TsFile project
   2. Run performance benchmarks
   3. Collect profiling data using perf. Flamegraph results (for C++ and Python) will be generated and stored under the /result directory.