mirror of https://github.com/go-gitea/gitea.git
68 lines
2.9 KiB
Markdown
68 lines
2.9 KiB
Markdown
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# Govarint
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This project aims to provide a simple API for the performant encoding and decoding of 32 and 64 bit integers using a variety of algorithms.
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[](https://www.flickr.com/photos/tsevis/8648521649/)
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## Usage
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Each integer encoding algorithm conforms to an encoding and decoding interface.
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The interfaces also specify the size of the unsigned integer, either 32 or 64 bits, and will be referred to as XX below.
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To create an encoder:
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NewU32Base128Encoder(w io.Writer)
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NewU64Base128Encoder(w io.Writer)
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NewU32GroupVarintEncoder(w io.Writer)
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For encoders, the only two commands are `PutUXX` and `Close`.
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`Close` must be called as some integer encoding algorithms write in multiples.
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var buf bytes.Buffer
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enc := NewU32Base128Encoder(&buf)
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enc.PutU32(117)
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enc.PutU32(343)
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enc.Close()
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To create a decoder:
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NewU32Base128Decoder(r io.ByteReader)
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NewU64Base128Decoder(r io.ByteReader)
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NewU32GroupVarintDecoder(r io.ByteReader)
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For decoders, the only command is `GetUXX`.
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`GetUXX` returns the value and any potential errors.
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When reading is complete, `GetUXX` will return an `EOF` (End Of File).
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dec := NewU32Base128Decoder(&buf)
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x, err := dec.GetU32()
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## Use Cases
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Using fixed width integers, such as uint32 and uint64, usually waste large amounts of space, especially when encoding small values.
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Optimally, smaller numbers should take less space to represent.
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Using integer encoding algorithms is especially common in specific applications, such as storing edge lists or indexes for search engines.
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In these situations, you have a sorted list of numbers that you want to keep as compactly as possible in memory.
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Additionally, by storing only the difference between the given number and the previous (delta encoding), the numbers are quite small, and thus compress well.
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For an explicit example, the Web Data Commons Hyperlink Graph contains 128 billion edges linking page A to page B, where each page is represented by a 32 bit integer.
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By converting all these edges to 64 bit integers (32 | 32), sorting them, and then using delta encoding, memory usage can be reduced from 64 bits per edge down to only 9 bits per edge using the Base128 integer encoding algorithm.
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This figure improves even further if compressed using conventional compression algorithms (3 bits per edge).
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## Encodings supported
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`govarint` supports:
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+ Base128 [32, 64] - each byte uses 7 bits for encoding the integer and 1 bit for indicating if the integer requires another byte
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+ Group Varint [32] - integers are encoded in blocks of four - one byte encodes the size of the following four integers, then the values of the four integers follows
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Group Varint consistently beats Base128 in decompression speed but Base128 may offer improved compression ratios depending on the distribution of the supplied integers.
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## Tests
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go test -v -bench=.
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## License
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MIT License, as per `LICENSE`
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