Learning Apache Spark Scala in Pune

Learning new languages can be full of hassles. If you want to learn Scala from scratch, you should opt for our Scala Training In Pune. Our training will help you in writing simple codes in Apache Spark with the use of Scala. You will have an in-depth knowledge of Scala as you go for this training. In addition to learning one language, you will be capable of adding more skills to the resume. With an ample amount of experience in the industry, we are recognized among the leading professional institutes offering career oriented and comprehensive Spark Online Training Pune.

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What will you learn from Spark online classes in Pune

As you opt for our Spark online classes in Pune, you will be introduced to Scala and Spark. Thus, you will be capable of learning these languages in details. You will master the algorithms of Spark. As you complete each module and move to the next one, you will be capable of understanding the difference between Hadoop Training and Spark. This training has provided to be useful to IT professionals for Spark Data aggregation and improvement of performance. By opting for the training courses, you will be successful in developing codes from Scala. You can write spark applications with the use of Scala, Python, and Java.

Who should participate in the Scala Training In Pune

Software developers who are willing to upgrade their skills in Big Data should opt for training in Apache Spark Scala Pune. ETL developers and data engineers can also consider accomplishing this training. This training is a great option for analytics professionals and data scientists.

Eligibility criteria to go for Spark online training in Pune

There are no specific eligibility criteria for opting this training. Basic knowledge of SQL, database and query language will be beneficial.

Why go for training of Apache Spark Scala Pune

Big data has an impact on the IT industry in Pune. The companies are in high competition for the production of instant outcomes with the processing of real time streaming data. Apache Spark happens to be one similar technology which accomplishes the above-mentioned requirement with the aid of smart features. Owing to this, its demands are enhancing in the city steadily.

As IT professionals opt for this training, they will have hands-on experience in Scala and Spark. The experienced industry professionals will be helpful in mastering the technologies via interactive teaching sessions, assignments and lab practices. As you enroll for these training courses, you will be able to score high in Hadoop Developer Certification and Cloudera Spark examination. At Prwatech, we have experienced professionals from leading multi national companies who will clear all your doubts related to Apache Spark Scala. There will be a boost in your career opportunities as you master this language.

Learning objectives – In this module, you will learn about the: basic concepts of UNIX, LINUX, Java, HDFS, Big Data, Hadoop, Hadoop data loading techniques, Solving big data problems using Hadoop, MapReduce, Hadoop cluster and role of Hadoop cluster.

Topics: Introduction to UNIX, Introduction to LINUX, Introduction to Java, Introduction to HDFS, DWH Concepts, Pig & Hive, Map reduce.

Learning Objectives – In this module you will learn about Multiple Hadoop Server roles, Understanding Pseudo cluster, Installation of Hadoop, Understanding Map-Reduce, files configuration and parameters.

Hadoop Installation, Hadoop Configuration, Understanding pseudo-distributed mode, deploying multi-node cluster, Role of Hadoop server, Rack knowledge, Write and Read Anatomy, Data Processing.

Learning Objectives – In this module you will be Understanding Hadoop Cluster setup, concepts of managing and planning Hadoop cluster, Troubleshooting Hadoop cluster, Monitoring Hdoop cluster, Executing MapReduce Jobs.

Topics: Concepts of Hadoop Cluster, Scheduling jobs, Monitoring cluster, Cluster Size, Knowledge about Hardware and Software portions, Schedulers in Hadoop, Troubleshooting cluster, Schedulers Configuring and run Map Reduce.

Learning Objectives – This module will help you to understand Clustering basics, Clustering administration tasks like adding or deleting data nodes, Node recovery, Configuring in Hadoop, Backup in Hadoop, Recovery in Hadoop, Troubleshooting node failures and Upgrade Hadoop.

Topics: Maintaining Hadoop Backup, data nodes white list and blacklist in a cluster, quota’s setup, upgrading Hadoop cluster, DISTCP, Diagnostics, Recovery, Cluster Troubleshooting, Rack Configuration.

Learning Objectives – In this module our main focus is to understand Hadoop 2.0 New Features, HDFS, YARN, Hadoop 2.0 setup, MRv2, Secondary NameNode setup, NameNode check pointing.

Topics: Configuring Secondary NameNode, , Deploying Hadoop 2.0 in pseudo-distributed mode, Hadoop 2.0, YARN, MRv2, Hadoop 2.0 Cluster setupdeploying a multi-node Hadoop 2.0 cluster.

HQL and Hive with Analytics

Learning Objectives- After completing with the basics, In this module you will strengthen concepts about Hadoop security, Managing Hadoop security, HDFS High Availability, HDFS setup and Log Management and Quorum Journal Manager

Topics: Hadoop Platform Security, Configuring Kerberos, Auditing and Alerts, Configuring HDFS, Monitoring, Log Management and Service Monitoring.

Learning Objectives – This module will assist you in learning Oozie Workflow Scheduler, deploying HBase, Hive Administration, effectively load data, read and write from HBase.

Topics: No SQL, H base, Zookeeper, HBase Architecture, Sqoop, Flume, HBase setup, Oozie, Yarn and Hue.

Learning Objectives – In this module you will work on a real-world case and learn about implementing, planning, designing and deploying Hadoop cluster. You will also learn about Hadoop eco-system components.

Topics: Implementing, planning, designing and deploying Hadoop cluster, Hadoop ecosystem components, troubleshooting cluster problems, AWS cluster.

This module in the Big Data Hadoop Course helps the learners in understanding Hadoop 2.0 features like MRv2, YARN and HDFS Federation.

The topics covered are New Features of Hadoop 2.0, High Availability of NameNode.

This module helps the readers in understanding how different Hadoop ecosystem elements work together towards Hadoop implementation for solving Big Data issues.

Rs. 14,000 + Tax

per 2 weeks

35 Hours
Practical 40 Hours
15 Seats
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