The Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop developer. In the course, an in-depth knowledge of concepts such as will be covered Hadoop Distributed File SystemThe Hadoop Distributed File System (HDFS) is a critical part of the Hadoop ecosystem, Designed to store large volumes of data in a distributed manner. HDFS enables scalable storage and efficient data management, splitting files into blocks that are replicated across different nodes. This ensures availability and resilience to failures, facilitating the processing of big data in big data environments...., Hadoop Cluster, Map – Reduce, HbaseHBase is a NoSQL database designed to handle large volumes of data distributed in clusters. Based on the column model, Enables fast, scalable access to information. HBase easily integrates with Hadoop, making it a popular choice for applications that require massive data storage and processing. Its flexibility and ability to grow make it ideal for big data projects.... Zookeeper"Zookeeper" is a simulation video game released in 2001, where players take on the role of a zookeeper. The main mission is to manage and care for various species of animals, ensuring your well-being and the satisfaction of visitors. Throughout the game, Users can design and customize their zoo, facing challenges including food, the habitat and health of animals...., etc.
After completing the Big Data and Hadoop course at Edureka, I should be able to:
- Master the concepts of Distributed File SystemA distributed file system (DFS) Allows storage and access to data on multiple servers, facilitating the management of large volumes of information. This type of system improves availability and redundancy, as files are replicated to different locations, reducing the risk of data loss. What's more, Allows users to access files from different platforms and devices, promoting collaboration and... Hadoop and the framework MapReduceMapReduce is a programming model designed to efficiently process and generate large data sets. Powered by Google, This approach breaks down work into smaller tasks, which are distributed among multiple nodes in a cluster. Each node processes its part and then the results are combined. This method allows you to scale applications and handle massive volumes of information, being fundamental in the world of Big Data....
- Set up a clusterA cluster is a set of interconnected companies and organizations that operate in the same sector or geographical area, and that collaborate to improve their competitiveness. These groupings allow for the sharing of resources, Knowledge and technologies, fostering innovation and economic growth. Clusters can span a variety of industries, from technology to agriculture, and are fundamental for regional development and job creation.... the Hadoop
- Understand data loading techniques using SqoopSqoop es una herramienta de código abierto diseñada para facilitar la transferencia de datos entre bases de datos relacionales y el ecosistema Hadoop. Permite la importación de datos desde sistemas como MySQL, PostgreSQL y Oracle a HDFS, así como la exportación de datos desde Hadoop a estas bases de datos. Sqoop optimiza el proceso mediante la paralelización de las operaciones, lo que lo convierte en una solución eficiente para el... Y FlumeFlume is an open-source software designed for data collection and transport. Use a flow-based approach, allowing data to be moved from various sources to storage systems such as Hadoop. Its modular and scalable architecture makes it easy to integrate with multiple data sources, which makes it a valuable tool for the processing and analysis of large volumes of information in real time....
- Program in MapReduce (both MRv1 and MRv2)
- Learn to write complex MapReduce programs
- Program in YARNYARN is a package manager for JavaScript that allows the efficient installation and management of dependencies in development projects. Powered by Facebook, It is characterized by its speed and security compared to other managers. YARN uses a cache system to optimize installations and provides a lock file to ensure consistency of dependency versions across different development environments.... (MRv2)
- Perform data analysis with PigThe Pig, a domesticated mammal of the Suidae family, It is known for its versatility in agriculture and food production. Native to Asia, Its breeding has spread all over the world. Pigs are omnivores and have a high capacity to adapt to various habitats. What's more, play an important role in the economy, Providing meat, leather and other derived products. Their intelligence and social behavior are also ... Y HiveHive is a decentralized social media platform that allows its users to share content and connect with others without the intervention of a central authority. Uses blockchain technology to ensure data security and ownership. Unlike other social networks, Hive allows users to monetize their content through crypto rewards, which encourages the creation and active exchange of information....
- Putting HBase into practice, MapReduce integration, advanced usage and advanced indexing
- Have a good knowledge of the Zookeeper service.
- New features in Hadoop 2.0 – YARN, Hadfs Federation, NameNodeThe NameNode is a fundamental component of the Hadoop distributed file system (HDFS). Its main function is to manage and store the metadata of the files, such as its location in the cluster and size. What's more, coordinates data access and ensures system integrity. Without the NameNode, HDFS operation would be severely affected, as it acts as the master in distributed storage architecture.... High Availability
- Apply best practices for Hadoop development and debugging
- Implement a Hadoop project
- Work on a real-life project on Big Data Analytics and get hands-on project experience
Who should attend this course?
This course is designed for professionals aspiring to a career in Big Data Analytics using the Hadoop Framework. Software professionals, analytics professionals, ETL developers, project managers, Testing professionals are the primary beneficiaries of this course. Other professionals who wish to obtain a solid foundation in Hadoop Architecture can also opt for this course.
Prerequisites:
Some of the prerequisites for learning Hadoop include practical experience in Core Java and good analytical skills to understand and apply the concepts in Hadoop.. Edureka will provide a complementary course “Java Essentials for Hadoop” to all members who sign up for Hadoop training. This course helps you improve your Java skills essential for writing Map Reduce programs.
Lessons:
- Classes are held on weekends. Depending on your batch, your live classes will be on Saturdays or Sundays.
- Towards the end of the program 8 weeks, will undergo a training project and 2 hours on your online exam at the end of the course.
Halftime, full time:
Part time
Duration:
Online classes: 30 hrs, there will be 10 instructors led by interactive online classes throughout the course. Each class will last approximately 3 hours and will take place at the scheduled time of the batch you choose.
Lab hours: 40 hours, each class will be followed by practical assignments that can be completed before the next class. Edureka will help you to configure a virtual machine on your system to carry out the practices.
Project: 20 hours, towards the end of the course, you will be working on a project where you are expected to perform Big Data Analytics using Map Reduce, PIG, Hive y HBase.
Next lots:
Start date: 2 July 2016
