About The Apache Spark Scala Training Course:

If you are looking for course to learn the concepts of Scala, RDD, OOPS, Traits, Spark SQL and MLib enroll yourself at PrwaTech for the Best Apache Spark Scala Training course. This training course will help the participants to learn various concepts of large-scale data processing. This online course is a part of Developer’s learning path.

Apache Spark is quickly gaining momentum not only in the headlines but also in real world adoption. Today, it has grown to the extent that, customers from all the industries are using it to improve their businesses with the HDP.

Learning Objectives: At the end of Spark Training course at PrwaTech, you will be able to:

Learn Storm Architecture and basic distributed concepts.
Learn Big Data features
Understand Legacy architecture of real time systems
Understand Logic Dynamics and Components in Storm
Learn the difference between Hadoop and Apache Spark
Learn Scala and the programming implementation in Scala
Build Spark Applications using Java, Python and Scala
Implement Spark on cluster
Gain insight into functioning of Scala
Develop Real-life Storm Projects

Pre-Requisites:

Basic knowledge of Java basics is required.
Prior knowledge of Hadoop is not mandatory.

About the Trainer

5 Avg Rating

1 Reviews

2 Students

9 Courses

Prwatech P

M Tech

Work Experience:
Software professional, worked on enterprise, web, JAVA, J2EE,mobile applications.. Now focusing on Hadoop, BigData.5+ Year Experience in Corporate Training.
Freelance Consulting on BIGDATA & HADOOP DEVELOPER / ADMIN,Spark.

Given talks at various meetup.Very proactive in learning and leveraging emerging technologies. Mentored engineers; believe in leading by doing.
Hadoop / BigData :
Consulting on Hadoop ecosystem : Hadoop, MapReduce, Pig,Hive, Sqoop, Flume
Managed Hadoop clusters : setup, install, monitor, maintain; Distributions : Cloudera CDH
Hadoop tutorials &howtos :
Teach Hadoop courses for individuals and corporate groups .

Responsibilities :
Written MapReduce code to process all the sequence files to extract the useful
Information from log files (like Host name, platform, operating system etc.).
Writing serdes and used complex data type in Hive.
Extensively involved in query optimization in Hive query language.
Extensively used pig script, complex type, grouping, flattening etc.
Maintained Hadoop clusters for dev/production.

Created the customized Map Reduce Input/output formatter and used extensively.
Highly involved in designed the next generation data architecture for the unstructured data.
Performance tuning of Hadoop clusters routines against very large data sets.
Assisted with the addition of Hadoop processing to the IT infrastructure.
Depending on this information the HBase rules will be applied on the log files, to get the required information in a structural manner (MapReduce output) used hive for storing the MapReduce output into tables.
Used Sqoop and Flume for importing the data into the HDFS.
Reviewed the HDFS usage and system design for future scalability.
Developed applications on MapReduce programming Model of Hadoop in java.