Once the compression has started, there's four different element types to consider: I'll start off by writing the length of the uncompressed data (as a little-endian varint) at the beginning of the compressed stream. Snappy will turn this string into an array of bytes because it is byte-oriented, rather than bit oriented. 'Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project.' I'll focus on the stream format, since the data is only chunked between blocks for large files, which doesn't provide an accessible introduction to the algorithm. So how does it all work? Snappy operates with both a block-level and stream format. So since compute resources are generally more expensive than storage resources, Google can use Snappy to make these queries ultra fast, at the (lower) cost of storage.

In a small business, this may be 100s of lines of text, but on the scale of a tech giant, these results could easily be 100,000 lines of text. A database receives a query, and then returns all matching results. A keen reader may recognize many of these as database tools, which makes total sense when considering what is going on under the hood. Google has used it for multiple of its own projects, such as BigTable, MapReduce, MongoDB, and its own RPC system. We're used to compression algorithms focusing almost entirely on compression ratio, but it turns out there's some intuitive applications for a high data-rate algorithm. Part of this speed differential comes from the fact that Snappy doesn't use an entropy coder, like a Huffman tree or arithmetic encoder. Snappy uses 64-bit operations to allow efficient operation on multiple cores of modern consumer processors, boasting speeds upward of 250 MB/s compress and 500 MB/s decompress on just a single core of a 2015 i7 CPU. This means it has a mediocre compression rate of 1.5x to 1.7x for plain text and 2x-4x for HTML, but can compress and decompress at rates much faster than other algorithms. The algorithm focuses on the time-efficient compression of the data rather than peak compression ratio. Previously known as Zippy, it's a lossless, data compression algorithm implemented by Google used primarily on text.

Mac snappy compression