Question 1

How do I compress signed integers with StreamVByte?

Accepted Answer

Use the zigzag_encode function provided in the library to convert signed integers to unsigned before compression, and zigzag_decode after decompression. This adds a minor preprocessing step but allows compatibility with the core unsigned integer functions.

Question 2

Is StreamVByte faster than FastPFor for decompression?

Accepted Answer

Yes, StreamVByte is specifically designed for faster decompression speeds by using SIMD-accelerated byte-oriented compression, as highlighted in benchmarks and technical posts. FastPFor may offer better compression ratios but often at the cost of slower decompression.

Question 3

Does StreamVByte work on Raspberry Pi or other ARM devices?

Accepted Answer

Yes, it supports ARM processors with NEON instructions, which includes most modern ARM cores like those in Raspberry Pi. The library's CI tests include ARM builds, ensuring performance on embedded and mobile platforms.

Question 4

How to build StreamVByte with CMake on Windows?

Accepted Answer

Use the provided CMakeLists.txt with a recent CMake and Visual Studio 2019 or later. Run 'cmake -B build' and 'cmake --build build' in the command line, as shown in the README's VS16-CI and VS17-CI workflows for Windows compatibility.

Question 5

What's the typical compression ratio for 32-bit integers with StreamVByte?

Accepted Answer

Compression ratio varies with data distribution; for random integers, it's modest (e.g., 2-4 bytes per integer), but for sorted or sequential data with delta coding, it can achieve significant savings, often reducing size by 50% or more in real-world use cases like databases.

Question 6

Can I use StreamVByte for 64-bit integers?

Accepted Answer

No, StreamVByte is specifically designed for 32-bit integers. For 64-bit integers, you'd need to split them into 32-bit chunks or consider alternative libraries from the same author, such as SIMDCompressionAndIntersection, which may offer different trade-offs.

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