Advanced Features of the Hadoop Ecosystem

In a world where organizations rely on fast, informed decision-making, big data analytics exists to extract meaningful insights from huge amounts of information. It plays an important role in every field from health and economics to banking, as well as in government; new opportunities and challenges continue to emerge to deal with massive amounts of data. The Apache Hadoop Ecosystem, with its open source components, is designed to answer these needs: to store, process, evaluate, analyze and mine data. Unlike traditional systems, Hadoop handles multiple types of workloads consisting of different types of data, with massive parallel processing using industry-standard hardware.

Hadoop stores data in the Hadoop distributed file system (HDFS), which is designed to run on standard hardware. HDFS is very fault-tolerant, provides high throughput access to application data and is suitable for applications that have large data sets. This course illustrates how different types of data can be stored on HDFS and how to process it using the various components of the Hadoop ecosystem. Cluster computing frameworks like MapReduce have been widely adopted for large-scale data analytics. Resilient distributed datasets (RDDs) enable efficient data reuse in a broad range of applications. RDDs are fault-tolerant, parallel data structures that let users explicitly persist intermediate results in memory, control their partitioning to optimize data placement, and manipulate them using a rich set of operators.

Are you interested in big data? Would you like to further your understanding of Hadoop software? This course is for database and dataware house developers, big data developers and architects, data scientists, analysts and any technical personnel who are interested in learning and exploring the features of big data and its tools. With comprehensive lessons guiding you step-by-step and theory to back it up, the course follows with hands-on sessions to get practical experience in Sqoop, Hive, Spark, Flume, Apache Pig and Cloudera. So if you are looking to increase your knowledge of the advanced features of the Hadoop ecosystem, start this free online course today!