Data compression symmetry

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Symmetry and asymmetry, in the context of data compression, refer to the time relation between compression and decompression for a given compression algorithm.

If an algorithm takes the same time to compress a data archive as it does to decompress it, it is considered symmetrical. Note that compression and decompression, even for a symmetric algorithm, may not be perfectly symmetric in practice, depending on the devices the data is being copied to and from, and other factors such as latency and the fragmentation on the device.

In turn, if the compression and decompression times of an algorithm are vastly different, it is considered asymmetrical.

7zip algorithms comparison[1]
(in nanoseconds/bytes)  Algorithm | Compression | Decompression | Symmetry

|
|
|

LZMA | 2286 | 63 | Asymmetrical
BWT | 1974 | 176 | Asymmetrical
PPMd | 647 | 655 | Symmetrical

## Uses

Symmetric algorithms are typically used for media streaming protocols, as either the server taking too long to compress the data, or the client taking too long to decompress, would lead to delays in the viewing of the data.

Asymmetrical algorithms wherein the compression is faster than the decompression can be useful for backing up or archiving data, as in these cases data is typically much more often stored than retrieved.

Also asymmetrical algorithm are used in audio compression because decompression must happen in real-time, otherwise playback might get interrupted. [2]

## References

1. ↑ Mahoney, Matt. "Large Text Compression Benchmark". https://mattmahoney.net/dc/text.html#1789.
2. ↑ David Salomon (2008). A Concise Introduction to Data Compression. Springer. ISBN 9781848000711. https://archive.org/details/conciseintroduct00salo_179.

## Further reading

* Peter D. Symes (2004). "Symmetric and Asymetric Systems". Digital Video Compression. McGraw-Hill Professional. pp. 11. ISBN 9780071424875. https://archive.org/details/isbn_9780071424875/page/11.

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Data compression methods

Lossless|

| Entropy type|

* Arithmetic
* Asymmetric numeral systems
* Golomb
* Huffman
* Adaptive
* Canonical
* Modified
* Range
* Shannon
* Shannon–Fano
* Shannon–Fano–Elias
* Tunstall
* Unary
* Universal
* Exp-Golomb
* Fibonacci
* Gamma
* Levenshtein

|

Dictionary type|

* Byte pair encoding
* Lempel–Ziv
* Brotli
* DEFLATE
* LZ4
* LZFSE
* LZJB
* LZMA
* LZO
* LZRW
* LZS
* LZSS
* LZW
* LZWL
* LZX
* Snappy
* Zstandard

Other types|

* BWT
* CTW
* Delta
* DMC
* DPCM
* LDCT
* MTF
* PAQ
* PPM
* RLE

Lossy|

| Transform type|

* Discrete cosine transform
* DCT
* MDCT
* DST
* FFT
* Wavelet
* Daubechies
* DWT
* SPIHT

|

Predictive type|

* DPCM
* ADPCM
* LPC
* ACELP
* CELP
* LAR
* LSP
* WLPC
* Motion
* Compensation
* Estimation
* Vector
* Psychoacoustic

Audio|

| Concepts|

* Bit rate
* ABR
* CBR
* VBR
* Companding
* Convolution
* Dynamic range
* Latency
* Nyquist–Shannon theorem
* Sampling
* Sound quality
* Speech coding
* Sub-band coding

|

Codec parts|

* A-law
* μ-law
* DPCM
* ADPCM
* FT
* FFT
* LPC
* ACELP
* CELP
* LAR
* LSP
* WLPC
* MDCT
* Psychoacoustic model

Image|

| Concepts|

* Chroma subsampling
* Coding tree unit
* Color space
* Compression artifact
* Image resolution
* Macroblock
* Pixel
* PSNR
* Quantization
* Standard test image

|

Methods|

* Chain code
* DCT
* DEFLATE
* Fractal
* KLT
* LP
* RLE
* Wavelet
* Daubechies
* DWT
* EZW
* SPIHT

Video|

| Concepts|

* Bit rate
* ABR
* CBR
* VBR
* Display resolution
* Frame
* Frame rate
* Frame types
* Interlace
* Video characteristics
* Video quality

|

Codec parts|

* DCT
* DPCM
* Deblocking filter
* Lapped transform
* Motion
* Compensation
* Estimation
* Vector
* Wavelet
* Daubechies
* DWT

Theory|

* Entropy
* Information theory
* Timeline
* Kolmogorov complexity
* Quantization
* Rate–distortion
* Redundancy

* Compression formats
* Compression software (codecs)

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