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http://wiki.apache.org/cassandra/DataModel

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- = Introduction =
+ deleted
  
- 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 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 th
 at 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 and column must fit (on disk) 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.  This is an inherent limitation of the distribution model.
- 
- Currently Cassandra also has the limitation that in the worst case, data for 
a key / ColumnFamily pair will all be deserialized into memory for a read 
request.  (But never for writes!)  This will be fixed in a future release.
- 
- = 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. They allow you to break your row (the data corresponding to a key) 
into a static number of groups a.k.a Column Families. In Cassandra, each Column 
Family in a table is stored in a separate file, and the file is sorted 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. SuperColumns, on the other hand, 
are always sorted by name. Columns within a super column may be sorted by time.
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- Suppose we define a table called !MyTable with column families 
!MySuperColumnFamily (this a column 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.
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