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Apache Spark ve Scala Eğitimi

spark-logo-trademark      4-Minimal-Scala-Web-Frameworks-for-Web-Developers

Apache Spark ve Scala Eğitimi

With Apache Spark and Scala certification training you would advance your expertise in Big Data Hadoop Ecosystem.

With this Apache Spark certification you will master the essential skills such as Spark Streaming, Spark SQL, Machine Learning Programming, GraphX Programming, Shell Scripting Spark.

And with real life industry project coupled with 30 demos you would be ready to take up Hadoop developer job requiring Apache Spark expertise.

With Certification in Apache Spark and Scala training, you will be able to :

Get clear understanding of the limitations of MapReduce and role of Spark in overcoming these limitations
Understand fundamentals of Scala Programming Language and it’s features
Explain & master the process of installing Spark as a standalone cluster
Expertise in using RDD for creating applications in Spark
Mastering SQL queries using SparkSQL
Gain thorough understanding of Spark Streaming features
Master & describe the features of Spark ML Programming and GraphX Programming

Who should do this course?

Professionals aspiring for a career in field of real time Big data analytics
Analytics professionals
Research professionals
IT developers and testers
Data scientists
BI and reporting professionals
Students who wish to gain a thorough understanding of Apache Spark

What projects are included in this course?

US based university has collected datasets which represent reviews of movies from multiple reviewers as a part of Research Project. To gain in depth insights from research data collected you have to perform a series of tasks in Spark on the data set provided.

Apache Spark and Scala Certification Course Agenda

Lesson 1: Course Preview
 Course overview
 Objectives

Lesson 2: Introduction to Spark
 Limitations of MapReduce in Hadoop Objectives
 Batch vs. Real-time analytics
 Application of stream processing
 How to install Spark
 Spark vs. Hadoop Eco-system

Lesson 3: Introduction to Programming in Scala
 Features of Scala
 Basic data types and literals used
 List the operators and methods used in Scala
 Concepts of Scala

Lesson 4: Using RDD for Creating Applications in Spark
 Features of RDDs
 How to create RDDs
 RDD operations and methods
 How to run a Spark project with SBT
 Explain RDD functions and describe how to write different codes in Scala

Lesson 5: Running SQL queries Using SparkSQL
 Explain the importance and features of SparkSQL
 Describe methods to convert RDDs to DataFrames
 Explain concepts of SparkSQL
 Describe the concept of hive integration

Lesson 6: Spark Streaming
 Explain a concepts of Spark Streaming
 Describe basic and advanced sources
 Explain how stateful operations work
 Explain window and join operations

Lesson 7: Spark ML Programming
 Explain the use cases and techniques of Machine Learning (ML)
 Describe the key concepts of Spark ML
 Explain the concept of an ML Dataset, and ML algorithm, model selection via cross validation

Lesson 8: Spark GraphX Programming
 Explain the key concepts of Spark GraphX programming
 Limitations of the Graph Parallel system
 Describe the operations with a graph
 Graph system optimizations

OFFICIAL SPARK SCALA RESOURCES

Programming Guides:

API Docs:

Deployment Guides:

Other Documents:

External Resources:

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