If large scale data processing is a critical business need for you, you just found what you wanted. Apache Spark is a fast and general engine built for iterating over large chunks of data. It offers a great API and allows you to rapidly process data through machine learning or other techniques that require cyclic data flow or in-memory computing.
Apache Spark fits neatly into the open-source community of Hadoop by building on top of the Hadoop Distributed File System. When integrated with Hadoop, the engine can run on Hadoop 2’s YARN cluster manager and read existing data on Hadoop. Even if you don’t have Hadoop 2 Cluster, you can run Spark standalone on EC2 or Mesos. Spark can read data from Cassandra, HBase, HDFS and other Hadoop sources as well.
Apart from the great speed due to its DAG execution engine, Spark is an extremely user friendly technology. Applications can be written quickly in Java, Python or Scala. Moreover, it offers great tools such as MLib for machine learning, Spark SQL, Spark Streaming and GraphX (native graph processing library) which can all be combined to build high-performance applications. Apache Spark is extremely suitable for machine learning algorithms.
Organizations across the world are benefiting from employing Spark. In conjunction with Hadoop, the engine is used to gather business intelligence via visual, real-time predictive analytics. Apart from exploration of large datasets, Spark also provides an effective data center solution and a Big Data platform. Companies that use Spark include big names such as eBay Inc, Yahoo!, Baidu, Amazon, Alibaba among others.
e-Zest provides Apache Spark implementation services. We highly recommend Spark to enterprises worldwide. The framework offers great performance benefits and versatility. Enterprises are faced with a high volume and velocity of data coming from web and mobile apps. To stay ahead of the curve, it is critical that the speed of data processing and analysis should support the Big Data apps. Spark gives your business that advantage. It also offers multiple analytics options such as machine learning, streaming analytics and graph analytics.
Get in touch with us today at firstname.lastname@example.org to get started on this framework.