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This course is about the learning process of apache spark which is an open-source and distributed processing system used for big-data loads. It is helpful for large scale data processing.
Unlimited Duration
January 27, 2021
Apache Spark is a computing technology which is designed for fast computation. Apache spark is a data processing framework that can quickly perform processing tasks on very huge data sets and can also distribute data processing tasks across multiple computers. Spark is the fast and general engine for large-scale data processing. It is helpful to cover a wide range of workloads.
Every year we have a big amount of data that we need to store and analyze. It is a computer service used to process and store vast amount of data. In the present era apache spark is being adopted by major sites like yahoo, ebay etc. It widely helps you to run programs faster.
Course Curriculum
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- What is Spark? 00:00:00
- Why Spark? 00:00:00
- Where Spark is used 00:00:00
- An overview of BigData 00:00:00
- A brief background of Spark 00:00:00
- Hadoop and Spark 00:00:00
- Spark Ecosystem 00:00:00
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- Modes of Spark Deployment 00:00:00
- Spark supported languages 00:00:00
- Installing Spark in various modes 00:00:00
- Testing Spark Installation 00:00:00
- Labs 00:00:00
- Intro to Spark Shell 00:00:00
- Performing basics using Spark Shell 00:00:00
- Labs 00:00:00
- Object Oriented Programming with classes 00:00:00
- Immutable Collections 00:00:00
- Mutable Collections 00:00:00
- Futures 00:00:00
- Labs 00:00:00
- What is a Spark Context 00:00:00
- Spark context using Scala 00:00:00
- Spark context using Java 00:00:00
- Spark context using Python 00:00:00
- Labs 00:00:00
- RDD operations using Scala 00:00:00
- RDD operations using Java 00:00:00
- RDD operations using Python 00:00:00
- Pairing RDDs 00:00:00
- Labs 00:00:00
- Intro to Spark DataFrames 00:00:00
- DataFrame Transformations 00:00:00
- Labs 00:00:00
- Intro to Spark GraphX 00:00:00
- Graph properties 00:00:00
- Graph Operators 00:00:00
- Graph Builders 00:00:00
- Vertex and Edge RDDs 00:00:00
- Labs 00:00:00
- Spark properties 00:00:00
- Environment properties 00:00:00
- Logging 00:00:00
- Labs 00:00:00
- Scheduling jobs across applications 00:00:00
- Scheduling jobs within applications 00:00:00
- Labs 00:00:00
- Testing in Java 00:00:00
- Testing in Scala 00:00:00
- Testing in Python 00:00:00
- Labs 00:00:00
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