Apache Spark In-Depth (Spark with Scala) Udemy Free Download
What you'll learn:
- Frame big data analysis problems as Apache Spark scripts
- Develop distributed code using the Scala programming language
- Optimize Spark jobs through partitioning, caching, and other techniques
- Build, deploy, and run Spark scripts on Hadoop clusters
- Process continual streams of data with Spark Streaming
- Transform structured data using SparkSQL and DataFrames
- Traverse and analyze graph structures using GraphX
Requirements::
- Some prior programming or scripting experience is required. A crash course in Scala is included, but you need to know the fundamentals of programming in order to pick it up.
- You will need a desktop PC and an Internet connection. The course is created with Windows in mind, but users comfortable with MacOS or Linux can use the same tools.
- The software needed for this course is freely available, and I’ll walk you through downloading and installing it.
Description:
Learn Apache Spark From Scratch To In-Depth
From the instructor of successful Data Engineering courses on "Big Data Hadoop and Spark with Scala" and "Scala Programming In-Depth"
From Simple program on word count to Batch Processing to Spark Structure Streaming.
From Developing and Deploying Spark application to debugging.
From Performance tuning, Optimization to Troubleshooting
Contents all you need for in-depth study of Apache Spark and to clear Spark interviews.
Taught in very simple English language so any one can follow the course very easily.
No Prerequisites, Good to know basics about Hadoop and Scala
Perfect place to start learning Apache Spark
Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Speed
Run workloads 100x faster.
Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine.
Ease of Use
Write applications quickly in Java, Scala, Python, R, and SQL.
Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells.
Generality
Combine SQL, streaming, and complex analytics.
Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.
Runs Everywhere
Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources.
Who this course is for:
- People looking to advance their career in Data Engineering, Big Data, Hadoop, Spark
- Already working on Big Data Hadoop/ Spark and want to clear the concepts
Course Details:
- 40.5 hours on-demand video
- 34 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion