Spark is a unique framework for big data analytics which gives one unique integrated API by developers for the purpose of data scientists and analysts to perform separate tasks. It supports a wide range of popular languages like Python, R, SQL, Java and Scala. Apache Spark main aim is to provide hands-on experience to create real-time Data Stream Analysis and large-scale learning solutions for data scientists, data analysts and software developers. Spark is a cluster computer framework. It is an open source and lighting fast computer designer. It is used or extends the MapReduce model. It was introduced by Apache framework. It enables a computing solution which is scalable. Also, it is flexible and cost-effective. It is used for the speed up the Hadoop computational computing software process. Spark has its own cluster management, hence it uses the Hadoop for the storage purpose.
Apache Spark
By: Professor
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
- 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 & 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 Transformations
- Spark Actions
- Spark Cluster
- Spark SQL Introduction
- Spark Data Frames
- Spark SQL with CSV
- Spark SQL with JSON
- Spark SQL with Database
- 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
- Introduction to Graph Parallel Systems
- Introduction to GraphX
- Features of GraphX
- GraphX Deep Dive
- Graph Builder
- Using Mllib for Movie Recommendations
- Analyzing Recommendation Results using Spark
Register
Josh Innovations is a leading software training institute providing Software Training, Project Guidance, IT Consulting and Technology Workshops.