Big Data and Hadoop

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Hadoop is an open source programming framework based on Java. It has been developed primarily for storing & processing extremely large unstructured data in a distributed computing environment. With Hadoop, applications can be run on thousands of distributed commodities hardware called as nodes and can handle thousands of terabytes. Its distributed file system facilitates very fast data transfer rates among nodes over network. The inbuild redundancy allows to recover from node failures. 

Hadoop has emerged as the foundation of big data and its processing such as analytics, handling humongous amount of data generated from internet of things (IoT) sensors.

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DESCRIPTION

Hadoop is an open source programming framework based on Java. It has been developed primarily for storing & processing extremely large unstructured data in a distributed computing environment. With Hadoop, applications can be run on thousands of distributed commodities hardware called as nodes and can handle thousands of terabytes. Its distributed file system facilitates very fast data transfer rates among nodes over network. The inbuild redundancy allows to recover from node failures.

Hadoop has emerged as the foundation of big data and its processing such as analytics, handling humongous amount of data generated from internet of things (IoT) sensors.

  • Master fundamentals of Hadoop 2.7 and YARN and write applications using them
  • Setting up Pseudo node and Multi node cluster on Amazon EC2
  • Master HDFS, MapReduce, Hive, Pig, Oozie, Sqoop, Flume, Zookeeper, HBase
  • Learn Spark, Spark RDD, Graphx, MLlib writing Spark applications
  • Master Hadoop administration activities like cluster managing,monitoring,administration and troubleshooting
  • Configuring ETL tools like Pentaho/Talend to work with MapReduce, Hive, Pig, etc
  • Detailed understanding of Big Data analytics
  • Hadoop testing applications using MR Unit and other automation tools.
  • Work with Avro data formats
  • Practice real-life projects using Hadoop and Apache Spark
  • Be equipped to clear Big Data Hadoop Certification.

Hadoop

        + Hadoop Distributed File System (HDFS) – storing data across thousands of commodity servers with high data transfer rate supported. 

        + Hadoop's Yet Another Resource Negotiator (YARN) – resource management & scheduling for user applications.

        + MapReduce – programming interface to handle large distributed data processing – mapping data and reducing it to result.

HBase – An open source, nonrelational, distributed database.

Apache Flume – Collect, aggregate, and move huge volume of streaming data into HDFS.

Apache Hive – A data warehouse data provides data summarization, query, and analysis. 

Apache Pig – A high level open source platform for creating parallel programs that run-on Hadoop.

Apache Sqoop – A tool to transfer bulk data between Hadoop and structured data stores (RDBMS) 

Apache oozie – Workflow scheduler for managing Hadoop jobs. 

Apache Spark – A fast engine for big data processing capable of streaming and supporting SQL, Machine Learning, and graph processing. 

Apache Zookeper – An open source configuration, synchronization, and naming registry service for large distributed systems. 

NoSQL – “Not only” or “Non-relational” SQL for storage and retrieval of data which is modelled unlike tabular relations as in relational databases. 

        + Cassandra or MongoDB

We will share the reading material before the lectures
  • Java
  • Basics of Linux

FREQUENTLY ASKED QUESTIONS

What is Big data?

Big Data is defined as a large volume of both structured and unstructured raw data that inundates an enterprise on a day-to-day basis. By using Big Data you can take data from any source and examine it to find answers like cost reductions, new product development, time reductions and smart decision making.

What are the best certifications for Hadoop?

There are several top-grade big data vendors like Cloudera, Hortonworks, IBM, and MapReduce offering Hadoop Developer Certification and Hadoop Administrator Certification at different levels.

Do I have to be certified in Big Data and Hadoop?

Whether youre job hunting, waiting for a promotion, third-party proof of your skills is a great option. Certifications measure your skills and knowledge against industry to unlock great career opportunities as a Hadoop developer and to become an expert in Big Data Hadoop.

Is Java covered as part of this Big Data Hadoop course?

The total part of the Java is not covered in Big Data Hadoop course, the concepts which are required for understanding Big Data Hadoop course topics are covered.

What is MapReduce?

MapReduce is the heart of Hadoop. The MapReduce concept is simple to understand for those who are close with clustered out data processing solutions. It is the programming pattern that allows across hundreds or thousands of servers in a Hadoop cluster.

What is Cloud Lab?

Cloud Lab is a meta-cloud used in building cloud computing applications. This feature also allows users to store variables in the cloud. Cloud variables determine regular variables that have the characters in front of them.

What is HDFS?

The Hadoop Distributed File System (HDFS) is one of the most crucial topics of Apache Hadoop. It is the primary storage system used by Hadoop applications. HDFS is known as a Java-based file system that provides reliable data storage and high-performance access to data across Hadoop clusters.

What is Apache Flume?

Apache Flume is a reliable, distributed, and available service for aggregating, efficiently collecting and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS).

What is Apache Hive?

Hive is a component of Hortonworks Data Platform (HDP). Apache Hive provides an SQL-like interface to store data in HDP. A command line tool and JDBC driver are used to connect users to Hive.

What is Sqoop

Sqoop is a tool designed to carry bulk data between Hadoop and database servers. It is also used to import data from databases such as Oracle to Hadoop HDFS, MySQL to Hadoop file system.

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