Chapters: Shard, Partition, Shared Nothing Architecture, Data Striping. Source: Wikipedia. Pages: 20. Not illustrated. Free updates online. Purchase includes a free trial membership in the publisher's book club where you can select from more than a million books without charge. Excerpt: Database sharding is a method of horizontal partitioning in a database or search engine. Each individual partition is referred to as a shard or database shard. Horizontal partitioning is a design principle whereby rows of a database table are held separately, rather than splitting by columns (as for normalization). Each partition forms part of a shard, which may in turn be located on a separate database server or physical location. The advantage is the number of rows in each table is reduced (this reduces index size, thus improving search performance). If the sharding is based on some real-world aspect of the data (e.g. European customers vs. American customers) then it may be possible to infer the appropriate shard membership easily and automatically, and query only the relevant shard. Sharding is in practice far more difficult than this. Although it has been done for a long time by hand-coding (especially where rows have an obvious grouping, as per the example above), this is often inflexible. There is a desire to support sharding automatically, both in terms of adding code support for it, and for identifying candidates to be sharded separately. Where distributed computing is used to separate load between multiple servers (either for performance or reliability reasons) a shard approach may also be useful. Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which table a particular row will be found, without first needing to sea...http: //booksllc.net/?id=1946760