Big Data Hadoop Course by Simplilearn
The course provides a non-intimidating introduction to big data hadoop technologies. You will learn about the Hadoop Framework, Mapreduce and YARN for processing huge amounts of data in a distributed manner. You will also learn how to transfer data between relational databases and HDFS.
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Introduction to Big Data
Learn to use Apache Hadoop to process Big Data. This Big Data course by Simplilearn provides an introduction to the Hadoop framework and its components. This includes HDFS, MapReduce, Sqoop, Flume, Hive, Pig, Mahout (Machine Learning), R Connector, Ambari, Zookeeper, Oozie and No-SQL like HBase.
This course teaches you how to analyze and interpret Big Data with MapReduce, Hive, and Spark. It also explains the fundamental concepts of Hadoop and its ecosystem. You’ll discover the Five Vs of Big Data and how to apply them to business problems and questions.
MapReduce is a programming model for processing large data sets in parallel on a cluster of servers. Its relative simplicity and broad application make it a popular choice for data analysis and computing.
It takes input data and processes it into a set of intermediate results that are stored in HDFS. These intermediate results are then shuffled, sorted and reduced by a reducer program to produce the final output.
The framework is fault-tolerant because it will reschedule failed tasks a certain number of times before failing them altogether. It will also retry an incomplete task.
This course is perfect for anyone who wants to learn more about Big Data. It is one of the most popular courses on Udemy and has over 24,805 students enrolled. It provides a hands-on learning experience with Hadoop, including HDFS, MapReduce, and YARN.
It is designed for Software Engineers, Data Scientists, IT Professionals and System Administrators. The course will teach you how to handle large datasets using the Hadoop ecosystem, including YARN, HDFS, MapReduce, and Hive. It also covers how to integrate Hadoop with RDBMS using Sqoop. The course includes live instructor-led classes, and recorded sessions for future reference.
Hive is a data warehouse that provides ad hoc querying, summarization, and data analysis. It uses tables and databases to organize structured data that is stored in Hadoop Distributed File System (HDFS). Hive’s SQL-inspired language separates users from the complexity of Map Reduce programming.
It is optimized for the ORC and Parquet file formats and supports many SQL aggregate functions and analytical functions. It also offers fast and reliable performance for processing petabytes of data. It also enables users to integrate relational and non-relational data using technologies like Kafka, Pig, and Sqoop.
Pig is a scripting language for data processing on Hadoop. It combines SQL and MapReduce to perform complex data transformations. It is easy to program and supports both structured and unstructured data. It is also extensible and self-optimizing.
Unlike SQL, which is designed for the RDBMS environment with schemas and proper constraints, Pig was developed for the Hadoop data-processing environment, where the data might not have a defined schema. In addition, it can work on data as soon as it is copied to HDFS file system.
Moreover, Pig uses a fully-nestable data model that includes Tuples (or lists), Bags, and Maps. This feature helps reduce the amount of data that is scanned and improves performance.
The Big Data Hadoop course is an online training course that introduces you to the core components of the Apache Hadoop framework. It teaches you how to process large volumes of data with Hadoop Distributed File System (HDFS), MapReduce, Hive, and YARN. You will also learn to use high-speed messaging solutions like Kafka and Sqoop.
Using Sqoop, you can transfer data between relational database systems and Hadoop’s distributed storage system. The Sqoop import process works by splitting the data into multiple mappers and then converting each mapper into Java code. This code is compiled and then saved as a jar file.
This course will teach you how to develop and deploy big data applications with Hadoop. It will also give you a deep understanding of the core ideas and proficiency in managing Hadoop’s individual building blocks, including HDFS, MapReduce, and YARN.
In this specialization, you will learn about the complex architecture of Hadoop and its various components like MapReduce, YARN, Hive, and Sqoop. You will also learn to implement your own big data pipelines using frameworks like Apache Pig and Hive. You will also learn how to analyze relational databases with Hive.