Hadoop is an Apache Software Foundation project and open source software platform for scalable, distributed computing. Hadoop can provide fast and reliable analysis of both structured data and unstructured data. In this course you will learn about the design principles, the cluster architecture, considerations for servers and operating systems, and how to plan for a deployment. This learning path can be used as part of the preparation for the Cloudera Certified Administrator for Apache Hadoop (CCA-500) exam. | Apache Spark Fundamentals course introduces to the various components of the spark framework to efficiently process, visualize and analyze data. The course takes you through spark applications using Python, Scala and Java. You will also learn about the apache spark programming fundamentals like resilient distributed datasets and check which operations to be used to do a transformation operation on the RDD. This will also show you how to save and load data from different data sources like different type of files, RDBMS databases and NO-SQL. At the end of the course, you will explore effective spark application and execute it on Hadoop cluster to make informed business decisions.
Designed by industry experts to offer in-depth learning on Big data and Hadoop, this training program comes with real life projects and case studies| It renders you with in-depth knowledge and understanding of Hadoop framework encompassing Map Reduce, HDFS and yearn| The other topics included in this course are introduction to HBase Architecture, Hadoop Administration and maintenance and Hadoop Cluster setup| It further encompasses Hadoop testing, Hadoop administration, Hadoop analyst and Hadoop developer training | Candidates will also gain in-depth knowledge of pig and its components |Apart from this, one will get to learn spark SQL, transforming, querying and creating data frames