# Multi-Threaded Compression

`ZstdCompressor` accepts a `threads` argument that controls the number of threads to use for compression. The way this works is that input is split into segments and each segment is fed into a worker pool for compression. Once a segment is compressed, it is flushed/appended to the output.

Note

These threads are created at the C layer and are not Python threads. So they work outside the GIL. It is therefore possible to CPU saturate multiple cores from Python.

The segment size for multi-threaded compression is chosen from the window size of the compressor. This is derived from the `window_log` attribute of a `ZstdCompressionParameters` instance. By default, segment sizes are in the 1+MB range.

If multi-threaded compression is requested and the input is smaller than the configured segment size, only a single compression thread will be used. If the input is smaller than the segment size multiplied by the thread pool size or if data cannot be delivered to the compressor fast enough, not all requested compressor threads may be active simultaneously.

Compared to non-multi-threaded compression, multi-threaded compression has higher per-operation overhead. This includes extra memory operations, thread creation, lock acquisition, etc.

Due to the nature of multi-threaded compression using N compression states, the output from multi-threaded compression will likely be larger than non-multi-threaded compression. The difference is usually small. But there is a CPU/wall time versus size trade off that may warrant investigation.

Output from multi-threaded compression does not require any special handling on the decompression side. To the decompressor, data generated with single threaded compressor looks the same as data generated by a multi-threaded compressor and does not require any special handling or additional resource requirements.