CASSANDRA DATABASE EBOOK
Download this free book excerpt from O'Reilly to learn about the architecture and technical details to put Apache Cassandra to work in your production. Data Design. Hotel App RDBMS Design. Hotel App Cassandra Design. Hotel Application Code. Creating the Database. Data Structures. Apache Cassandra is the perfect choice for building fault-tolerant and scalable databases. Mastering Apache Cassandra 3.x teaches you how.
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Download your free copy of Apache Cassandra High Performance. Free PDF eBook: Learning OpenCV 3 Computer Vision with Python. Free PDF eBook. Editorial Reviews. About the Author. Sandeep Yarabarla. Sandeep Yarabarla is a professional Learning Apache Cassandra - Second Edition Kindle Edition. custom-speeches.com: Learning Apache Cassandra - Manage Fault Tolerant and Scalable Real-Time Data eBook: Mat Brown: Kindle Store.
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O’Reilly eBook: Learn How to Use Cassandra in Production
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6 Best Books to Learn Cassandra
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What is Cassandra? An introductory eBook
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Build, manage, and configure high-performing, reliable NoSQL database for your applications with Cassandra. Quick links: Description Table of Contents Reviews Authors. Skip to the end of the images gallery. Skip to the beginning of the images gallery.
Read Now Look inside. More Information Learn Write programs more efficiently using Cassandra's features more efficiently Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine JVM Use CQL3 in your application in order to simplify working with Cassandra Configure Cassandra and fine-tune its parameters depending on your needs Set up a cluster and learn how to scale it Monitor a Cassandra cluster in different ways Use Apache Spark and other big data processing tools About With ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need.
Features Write programs more efficiently using Cassandra's features with the help of examples Configure Cassandra and fine-tune its parameters depending on your needs Integrate Cassandra database with Apache Spark and build strong data analytics pipeline Page Count Course Length 10 hours 26 minutes ISBN Date Of Publication 31 Oct Table of contents.
Why was Cassandra created? All of the required components for basic operation are built in. Since Cassandra also operates in a peer-to-peer fashion, this means that there is no master-slave or sharding setup and that all nodes in the ring are equal.
Additionally, there is only one machine type that an administrator needs to worry about. Since it is masterless, there is no single point of failure. There is also the potential for zero downtime rolling upgrades. This is because Cassandra can support the temporary loss of multiple nodes depending on cluster size with negligible impact to the overall performance of the cluster.
The safety net Cassandra offers extends outside of your data center as well. Cassandra allows you to replicate your data to other data centers and keep multiple copies in multiple locations. This helps satisfy many regulatory requirements in addition to being a part of an strong disaster recovery and business continuity plan. Banks and other financial institutions are storing large quantities of financial data in Cassandra.
Analytics companies are using Cassandra to store web analytics data. Medical companies are using Cassandra to store sensor data and other time series inputs.
There are also many companies making use of Cassandra for storing internet of things IoT data. With Cassandra being a masterless system, all nodes in the ring are the same—a homogenous system. You can set it up to operate in a way that is consistent with your workload. For example, if you write lots of log data and read infrequently, then there are configuration tweaks to be made for write-heavy systems.
If you write heavily to one data center and then do all your reading from another data center, then you can adjust the settings on a data center-by-data center basis.
Changes can even be made by the drivers at connection time to aid in the performance of your system. For instance, the full text search engine Apache Solr has been packaged to work with Cassandra to provide full featured search capabilities to an existing Cassandra database. Apache Spark, a big data analytics engine, also has been plugged in to work on an existing database. There are entire suites of tools that can be integrated or bolted on to increase its capabilities. These include Apache Mahout, Kafka and Zipkin, to name a few.
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You also have the ability to gain more insight about your data without having to build and maintain the application systems that were previously required. You can then tack on your own additions of other metrics that are important to you. This is made possible by Cassandra taking advantage of Java MBeans and exposing them to the client. You can use these to get at much of the internal information Cassandra uses to make its own decisions and decide on its own health. Datastax also offers its own monitoring and control application called Opscenter.Building a Java application.
Additional components of Cassandra. Write programs more efficiently using Cassandra's features more efficiently Exploit the given infrastructure, improve performance, and tweak the Java Virtual Machine JVM Use CQL3 in your application in order to simplify working with Cassandra Configure Cassandra and fine-tune its parameters depending on your needs Set up a cluster and learn how to scale it Monitor a Cassandra cluster in different ways Use Apache Spark and other big data processing tools.
That is all a set a competencies that your organization no longer needs to own and can use what the greater community has already created. Active Everywhere. Cloud Security. You want to make each customer interaction a defining moment.
Application Security. There are entire suites of tools that can be integrated or bolted on to increase its capabilities.
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