Apache Spark is a lightning fast cluster computing designed for fast computation. Spark executes in memory data processing and runs much faster than Hadoop Map Reduce. Learners will get trained in-depth spark concepts with Scala programming and its components such as Spark Streaming, Spark SQL, Spark RDD, Spark MLlib and Spark Graphx.
- After completing the Apache Spark training, you will be able to:
- Understand Scala and its implementation
- Install Spark and implement Spark operations on Spark Shell
- Understand the role of Spark RDD
- Implement Spark applications on YARN (Hadoop)
- Learn Spark Streaming API
- Implement machine learning algorithms in Spark MLlib API
- Analyse Hive and Spark SQL architecture
- Understand Spark Graphx API and implement graph algorithms
- Professionals aspiring to work on Big Data Analytics.
- Spark Developers
- Data Scientist
Basic knowledge of big data, HDFS, any programming language like java, python, etc. but it is not mandatory.
- Introduction to Spark Getting started
- Resilient Distributed Dataset and Data Frames
- Spark application programming
- Introduction to Spark Eco System (Spark SQL)
- Spark Streaming
- Spark Mlib
- Spark Graphx
|Introduction to Spark Getting started|
|Resilient Distributed Dataset and Data Frames|
|Spark application programming|
|Introduction to Spark Eco System (Spark SQL)|
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