Apache Cassandra The Crash-Proof Nosql Database (Part 2)

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The data model

The data model for Cassandra is column-family-based, which resembles the design for relational databases using tables. In this case, however, the data model works in a fundamentally different manner to fixed-size columns.

In Cassandra, the database schema is not required to be fixed before the application is used – and it can actually be updated on the fly without any problems on the server. In most cases, the client can arbitrarily determine the number of columns and metadata it wants to store in a particular column family. This results in much more flexibility for the application and in rows that vary in size and in the number of columns.

Keyspaces are used to define the namespace for each application’s column families. Hence, these can be defined on a per-application basis, or according to any other schema design that is required. Column families can be of two types – static and dynamic. The static column family allows predefined columns in which a value may or may not be stored. Dynamic column families, on the other hand, allow the application to define columns whenever they are needed according to their usage. While specifying a column, its name, value and timestamp are needed. So basically, a column is the most basic unit in which a piece of information can be stored. Cassandra also supports structures like super columns and composite columns, which allow for further nesting.

Cassandra is based on google big table data model. It is called “Column DB”. It is totally different from traditional RDBMS.

Cassandra is based on google big table data model. It is called “Column DB”. It is totally different from traditional RDBMS.

Almost all RDBMS' require you to specify a data type for each column. Though Cassandra does not have any such strong requirements, it allows specification of comparators and validators, which act like a data type for the column name and the column’s value, respectively. Except for counters, almost all data types like integer, float, double, text, Boolean, etc., can be used for comparators and validators.

Installation and configuration

The binary for installing Cassandra can be found at This is available in the form of a compressed file, which can be easily extracted on any OS. Before installation, ensure that Java 1.6 is available on the system, and that the JAVA_HOME environment variable has been set. Once the extracted files have been placed in the desired directory, the following commands can be used (on Linux) to set up the environment:

sudo mkdir -p /var/log/cassandra

sudo chown -R `whoami` /var/log/cassandra

sudo mkdir -p /var/lib/cassandra

sudo chown -R `whoami` /var/lib/Cassandra

For Debian-based Linux distributions like Ubuntu, you can directly install it from the Apache repositories, for which you can add the following lines to ‘Software Sources’:

Deb 12 x main

Deb-src 12 x main

Additionally, there are two GPG keys to be added, as follows:

gpg --keyserver --recv-keys F758CE318D77295D

gpg --export --armor F758CE318D77295D | sudo apt-key add -

gpg --keyserver --recv-keys 2B5C1B00

gpg --export --armor 2B5C1B00 | sudo apt-key add –

Cassandra can now be installed with the simple sudo apt-get install Cassandra. The most basic configuration starts by confirming that all the files and folders have proper permissions. The file conf/cassandra.yaml lists all the defaults for other important locations. Cassandra can now be started by running the following command, which starts the server in the foreground and logs all the output on the terminal:

bin/cassandra –f

To run it in the background as a daemon, use the same command without the -f option. To check if it is running properly, try and access the command-line interface by running the bin/Cassandra-cli command. If there are still no errors and you are greeted with a prompt, then your installation has been successful. You can also try and run the CQL prompt (bin/cqlsh). For detailed instructions on how to set up a cluster, access the official documentation, although it does not cover much beyond some basic configuration. In short, you need to install Cassandra on each node similarly, and specify the earlier node as the seed. An IP interface for Gossip and Thrift are also required to be set up beforehand.

For further details about the persistency APIs used see Space Persistency.

For further details about the persistency APIs used see Space Persistency.

Connecting to Cassandra and using client libraries

Cassandra provides several client APIs to access the database directly from your development environment and a lot of client libraries for many languages like Python, Java, Ruby, Perl, PHP, .NET, C++, Erlang, etc. Even if the required library isn't available, you can use the Thrift interface directly. The Thrift framework supports almost every available language, and allows for cross-platform development by writing simple Thrift files that define the interface between a client and server application.

Cassandra also supports a new interface known as CQL (Cassandra Query Language), which is an SQL clone. It syntactically resembles SQL, besides being more suitable for this data model by allowing for column families and skipping on features like joins, which are not required in the context of a NoSQL data model. CQL is basically a wrapper that provides abstraction to the internal Thrift API, and makes the developer's job much easier by simplifying things. A CQL sample used to create a keyspace looks like what’s shown below:


WITH replication = {‘class’: ‘SimpleStrategy’, ‘replication_factor’: 3};

These commands can be run at the cqlsh prompt or using drivers available for languages like Java, Python, PHP, Ruby, etc. (These drivers require Thrift to be installed before use.)

The best part about using Cassandra is that it doesn't miss out on the analytical power provided by Hadoop's MapReduce. Setting this up is pretty easy, as Hadoop can directly be overlaid on top of a Cassandra cluster by having Task Trackers that are local to the Cassandra Analytics cluster, while Hadoop's Name Node and Job Tracker remain separate from the cluster on a different machine. Cassandra provides very good integration to facilitate working with Hadoop MapReduce jobs, and to provide easier access to data stored in Cassandra so that it can be used with other higher-level tools like Pig and Hive.

Connecting to Cassandra and using client libraries

Connecting to Cassandra and using client libraries

So, we have covered enough about Cassandra for a basic understanding of the important terminology. I have, however, skipped a lot of details that would have been beyond the scope of this article, including the various methods by which we can work with Cassandra, and other theoretical portions like replication strategies, network topology management, security, maintenance and performance tuning.

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