Introduction to Enterprise Scala in Spark

Enterprise Data Science is a very wide-ranging field built on many core technologies and paradigms that combine to provide a robust solution. Some of these key technologies and/or practices include ETL, Data Engineering, Machine Learning, Network/Grid/Cloud engineering, Business Rules and others. Introduction to Enterprise Scala in Spark is five-day, hands-on course that explores some of these areas at a higher level and provides experienced developers with a ‘big-picture’ understanding of how these technologies and skillsets fit together in a professional-grade enterprise Data Science environment, focusing on best practices and emerging trends.

Retail Price: $3,000.00

Next Date: Request Date

Course Days: 5


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Course Objectives

This course provides indoctrination in the practical use of the umbrella of technologies that are on the leading edge of data science development. 

Working in a hands-on learning environment led by our expert practitioner, attending students will lean:

  • 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

Course Prerequisites

Attending students are required to have a background in programming with basic OO development skills. Students should have the following incoming skills or knowledge:

  • Experience in developing object-oriented enterprise applications to at least a basic level
  • Familiarity with Eclipse
  • Be comfortable with the Linux/Unix command line, including editing text files

Course Agenda

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience needs and skill-level.

 

Session: Functional Programming in Scala

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

Session: 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

Session: 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)

Session: Working with NOSQL

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

Session: Spark Streaming

  • Spark Streaming Model
  • Streaming with Kafka

Session: ML Lib

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

Session: Enterprise Integration

  • Enterprise Service and Message Busses
  • Lambda Architecture


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