Enterprise Scala and Spark

Enterprise Data Science is a wide-ranging field built on many core technologies and paradigms that combine to provide a robust solution. Some of these technologies and/or practices include ETL, Data Engineering, Machine Learning, Network/Grid/Cloud engineering, and Business Rules.

Retail Price: $2,795.00

Next Date: Request Date

Course Days: 5


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WHAT YOU'LL LEARN

Join an engaging hands-on learning environment, where you’ll learn:

  • Essential Scala programming, leveraging your existing OO development experience
  • How to write essential Spark programs and perform exploratory data analysis in Scala and the Spark shell
  • Work with Spark Core
  • Work with NoSQL
  • How to write programs for Spark Streaming in Scala

 

WHO SHOULD ATTEND?

Data Scientists and Developers.

 

PREREQUISITES

Before attending this course, you should have:

  • Experience in Java development, object-oriented enterprise applications at a basic level
  • Familiarity with Eclipse
  • Be comfortable with the Linux/Unix command line, including editing text files
  • Java 8 Programming and Object Oriented Essentials for Developers New to OO

COURSE OUTLINE

Functional Programming in Scala

  • Functional Programming
  • Scala Overview
  • Scala vs. Python vs. Java vs. R
  • REPL in Scala
  • Installing Scala
  • Hello, Scala

Introduction to Scala

  • Classes and Objects
  • Traits
  • Mixins
  • High-Order Functions
  • Types and Inference
  • Lists
  • Annotations
  • Collections
  • Pattern Matching
    Using Java in Scala
  • Futures, Promises, and Parallel Collections (Concurrency)
  • Functional Programming Overview

Spark Core

  • Hadoop and Spark Overview
  • File I/O with HDFS
  • Data Frames and Resilient Distributed Datasets
  • Spark SQL
  • In-memory lookups
  • Essential AI with MLLib
  • Using Web Notebooks (Optional)

Working with NoSQL

  • Not Only SQL
  • Relational Data
  • Sqoop
  • Columnar Databases
  • Cassandra
  • Document Databases
  • Key/Value Databases
  • Graph Databases
  • Neo4J
  • GraphX
  • Hive in Spark

Spark Streaming

  • Spark Streaming Model
  • Streaming with Kafka

ML Lib

  • Machine Learning Essentials
  • Spark ML/MLLib
  • MLLib and Streaming
  • MLlib, Streaming, and Kafka

Enterprise Integration

  • Enterprise Service and Message Busses
  • Lambda Architecture


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