Towards the end, it takes you through the use of libraries and third party applications with Cassandra and Cassandra integration with Hadoop.
Apache Cassandra is a fault-tolerant, distributed data store which offers linear scalability allowing it to be a storage platform for large high volume websites. This is a cookbook and all tasks are approached as recipes. A recipe describes a task and outlines the steps necessary to complete this task. Some recipes in the book are examples of writing code. An example of this is a recipe that stores and accesses the entries of a phone book in Cassandra. The recipe consists of a description of the program, a full code example is given, the example is run, the output is displayed, and finally the how it works section describes the process or code in greater detail.
Other recipes in the book describe a task. An example of this is a recipe that takes a snapshot back up of data in Cassandra. This book is designed for administrators, developers, and data architects who are interested in Apache Cassandra for redundant, highly performing, and scalable data storage.
Recipes cover topics ranging from setting up Cassandra for the first time to complex multiple data center installations. The recipe format presents the information in a concise actionable form.
The book describes in detail how features of Cassandra can be tuned and what the possible effects of tuning can be.
Recipes include how to access data stored in Cassandra and use third party tools to help you out. The book also describes how to monitor and do capacity planning to ensure it is performing at a high level.
Towards the end, it takes you through the use of libraries and third party applications with Cassandra and Cassandra integration with Hadoop. The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together a fully distributed design and a ColumnFamily-based data model.
The chapter contains recipes that allow users to hit the ground running with Cassandra. We show several recipes to set up Cassandra. These include cursory explanations of the key configuration files. It also contains recipes for connecting to Cassandra and executing commands both from the application programmer interface and the command-line interface. Also described are the Java profiling tools such as JConsole.
The recipes in this chapter should help the user understand the basics of running and working with Cassandra. Cassandra is a highly scalable distributed database. While it is designed to run on multiple production class servers, it can be installed on desktop computers for functional testing and experimentation. This recipe shows how to set up a single instance of Cassandra.
New releases happen often. For reference, this recipe will assume apache-cassandra These locations will likely not exist and will require root-level privileges to create. To avoid permission issues, carry out the installation in user-writable directories. Create a cassandra directory in your home directory.
Use the echo command to display the path to your home directory. You will need this when editing the configuration file:. This tar file extracts to apache-cassandra Start the Cassandra instance and confirm it is running by connecting with nodetool :. Cassandra comes as a compiled Java application in a tar file. By changing options in the cassandra. It is broadly useful for programming needs ranging from configuration files and Internet messaging to object persistence and data auditing.
After startup, Cassandra detaches from the console and runs as a daemon. It opens several ports, including the Thrift port and JMX port on For versions of Cassandra higher than 0. X, the default port is The nodetool program communicates with the JMX port to confirm that the server is alive.
Due to the distributed design, many of the features require multiple instances of Cassandra running to utilize. For example, you cannot experiment with Replication Factor , the setting that controls how many nodes data is stored on, larger than one.
Replication Factor dictates what Consistency Level settings can be used for. The next recipe, Reading and writing test data using the command-line interface. The command - line interface CLI presents users with an interactive tool to communicate with the Cassandra server and execute the same operations that can be done from client server code. This recipe takes you through all the steps required to insert and read data.
New clusters do not have any preexisting keyspaces or column families. These need to be created so data can be stored in them:. Insert and read back data using the set and get commands:. After connecting, users can carry out administrative or troubleshooting tasks.
Chapter 2 , Command-line Interface is dedicated to CLI recipes defined in the preceding statements in greater detail. Cassandra is typically deployed on clusters of multiple servers. While it can be run on a single node, simulating a production cluster of multiple nodes is best done by running multiple instances of Cassandra. This recipe is similar to A simple single node Cassandra installation earlier in this chapter.
However in order to run multiple instances on a single machine, we create different sets of directories and modified configuration files for each node. Ensure your system has proper loopback address support. Each system should have the entire range of Confirm this by pinging Create a hpcas directory in your home directory.
Download and extract a binary distribution of Cassandra. Change the default storage locations and IP addresses to accommodate our multiple instances on the same machine without clashing with each other:.
Each instance will have a separate logfile. This will aid in troubleshooting. Cassandra uses JMX Java Management Extensions , which allows you to configure an explicit port but always binds to all interfaces on the system.
As a result, each instance will require its own management port. Edit cassandra-env. At this point your cluster is comprised of single node. To join other nodes to the cluster, carry out the preceding steps replacing '1' with '2' , '3' , '4' , and so on:. The Thrift port has to be the same for all instances in a cluster. Thus, it is impossible to run multiple nodes in the same cluster on one IP address.
However, computers have multiple loopback addresses: These addresses do not usually need to be configured explicitly. Each instance also needs its own storage directories. Following this recipe you can run as many instances on your computer as you wish, or even multiple distinct clusters. You are only limited by resources such as memory, CPU time, and hard disk space.
The next recipe, Scripting a multiple instance installation does this process with a single script. Cassandra is an active open source project. Setting up a multiple-node test environment is not complex, but has several steps and smaller errors happen. Each time you wish to try a new release, the installation process will have to be repeated.
This recipe achieves the same result of the Running multiple instances on a single machine recipe, but only involves running a single script.
Copy the tar to the base directory and then use pushd to change to that directory. Recipes cover topics ranging from setting up Cassandra for the first time to complex multiple data center installations.
The recipe format presents the information in a concise actionable form. The book describes in detail how features of Cassandra can be tuned and what the possible effects of tuning can be. Recipes include how to access data stored in Cassandra and use third party tools to help you out. The book also describes how to monitor and do capacity planning to ensure it is performing at a high level. Towards the end, it takes you through the use of libraries and third party applications with Cassandra and Cassandra integration with Hadoop.
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