Apache Spark is an open-source, unified analytics engine renowned for its speed and versatility in processing large-scale data. It offers a robust framework for big data processing, integrating seamlessly with Hadoop's HDFS, AWS S3, and a variety of other storage systems. Spark's in-memory computing capabilities significantly boost processing speeds, making it ideal for iterative algorithms and interactive data analytics. Its comprehensive suite of libraries, including Spark SQL for structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for real-time data streams, enables developers to perform a wide range of data tasks within a single cohesive environment. With its ease of use, scalability, and performance, Apache Spark is a powerful tool for data engineers and scientists looking to harness the potential of big data.

Aarush IT offers specialized online training in Apache Spark, designed to equip professionals with the skills needed to leverage this powerful big data analytics engine. The training program covers core aspects of Spark, including its architecture, in-memory processing capabilities, and integration with various data storage systems. Participants will gain hands-on experience with Spark's comprehensive libraries such as Spark SQL for querying structured data, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for real-time data analysis. The course is structured to accommodate learners of all levels, providing a blend of theoretical knowledge and practical applications through interactive modules and real-world projects. With expert instructors and flexible learning schedules, Aarush IT's Apache Spark online training ensures that individuals can effectively harness Spark’s capabilities to drive data-driven decision-making and innovation in their organizations.

Apache Spark Online Training Course Content

Apache Spark

• Introduction to Apache Spark
• Why Spark
• Batch Vs. Real Time Big Data Analytics
• Batch Analytics – Hadoop Ecosystem Overview
• Real Time Analytics Options
• Streaming Data – Storm
• In Memory Data – Spark, What is Spark?
• Spark benefits to Professionals
• Limitations of MR in Hadoop
• Components of Spark
• Spark Execution Architecture
• Benefits of Apache Spark
• Hadoop vs Spark

Introduction to Scala

• Features of Scala
• Basic Data Types of Scala
• Val vs Var
• Type Inference
• REPL
• Objects & Classes in Scala
• Functions as Objects in Scala
• Anonymous Functions in Scala
• Higher Order Functions
• Lists in Scala
• Maps
• Pattern Matching
• Traits in Scala
• Collections in Scala

Spark Core Architecture

• Spark & Distributed Systems
• Spark for Scalable Systems
• Spark Execution Context
• What is RDD
• RDD Deep Dive
• RDD Dependencies
• RDD Lineage
• Spark Application In Depth
• Spark Deployment
• Parallelism in Spark
• Caching in Spark

Spark Internals

• Spark Transformations
• Spark Actions
• Spark Cluster
• Spark SQL Introduction
• Spark Data Frames
• Spark SQL with CSV
• Spark SQL with JSON
• Spark SQL with Database

Spark Streaming

• Features of Spark Streaming
• Micro Batch
• Dstreams
• Transformations on Dstreams
• Spark Streaming Use Case 1
• Spark Streaming Use Case 2
• Spark Streaming Use Case 3

Spark GraphX Programming

• Introduction to Graph Parallel Systems
• Introduction to GraphX
• Features of GraphX
• GraphX Deep Dive
• Graph Builder

Introducing Mllib

• Using Mllib for Movie Recommendations
• Analyzing Recommendation Results using Spark