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The following page has been changed by EricEvans: http://wiki.apache.org/cassandra/DataModel The comment on the change is: imported from confluence wiki New page: = Introduction = Basic unit of access control within Cassandra is a Column Family. A table in Cassandra is made up of one or many column families. A row in a table is uniquely identified using a unique key. The is key is a string and can be of any size. The number of column families and the name of each column family must currently be fixed at the time the cluster is started. There is no limitation on the number of column families but it is expected that there would be relatively few of these. A column family can be of one of two type: Simple or Super. Columns within both of these are dynamically created and there is no limit on the number of these. Columns are constructs that are uniquely identified by a name, a value and a user-defined time stamp. The number of columns that can be contained in a column family could be very large. This can also vary per key. For instance key K1 could have 1024 columns/supercolumns while key K2 could have 64 columns/supercolumns. Supercolumns are constructs t hat have a name and an infinite number of columns associated with them. The number of supercolumns associated with any column family may be very large. They exhibit the same characteristics as columns. The columns can be sorted by name or time and this can be explicitly expressed via the configuration file, for any given column family. The main limitation on column and supercolumn size is that all data for a single key must fit on a single machine in the cluster. Because keys alone are used to determine the nodes responsible for replicating their data, the amount of data associated with a single key has this upper bound. = More Detail = A row-oriented database stores rows in a row major fashion (i.e. all the columns in the row are kept together). A column-oriented database on the other hand stores data on a per-column basis. Column Families allow a hybrid approach. It allows you to break your row (the data corresponding to a key) into a static number of groups a.k.a Column Families. In Cassandra, the data in a table is stored in a separate file on a per-Column Family basis. And within each column family, the data is stored in row (i.e. key) major order. Related columns, those that you'll access together, should ideally be kept within the same column family for access efficiency. Furthermore columns in a column family can be sorted and stored on disk either in time sorted order or in name sorted order. However, individual SuperColumns are always sorted by name. Columns within a super column may be sorted by time. Suppose we define a table called !MyTable with column families !MySuperColumnFamily (this a colu mn family of type Super) and !MyColumnFamily (this is simple column family). Any super column, SC in the !MySuperColumnFamily is addressed as "!MySuperColumnFamily:SC" and any column "C" within "SC" is addressed as !MySuperColumnFamily:SC:C. Any column C within !MySimpleColumnFamily is addressed as "!MySimpleColumnFamily:C". In short ":" is reserved word and should not be used as part of a Column Family name or as part of the name for a Super Column or Column. (We plan to address this limitation for the 0.4 release.) = Range queries = Cassandra supports pluggable partitioning schemes with a relatively small amount of code. Out of the box, Cassandra provides the hash-based RandomPartitioner and an OrderPreservingPartitioner. RandomPartitioner gives you pretty good load balancing with no further work required. OrderPreservingPartitioner on the other hand lets you perform range queries on the keys you have stored. Systems that only support hash-based partitioning cannot perform range queries efficiently. = Example: SuperColumns for Search Apps = You can think of each supercolumn name as a term and the columns within as the docids with rank info and other attributes being a part of it. If you have keys as the userids then you can have a per-user index stored in this form. This is how the per user index for term search is laid out for Inbox search at Facebook. Furthermore since one has the option of storing data on disk sorted by "Time" it is very easy for the system to answer queries of the form "Give me the top 10 messages". For a pictorial explanation please refer to the Cassandra powerpoint slides presented at SIGMOD 2008.
