Customized Onsite Training

3
Days
  • Customized Content
  • For Groups of 5+
  • Online or On-location
  • Expert Instructors
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Overview

This training class meant for developers and data analysts will introduce Apache Spark. The students will learn how Spark fits into the Big Data ecosystem, and how to use Spark for data analysis. The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX.

Outline
  1. Scala primer
    1. A Quick Introduction to Scala
  2. Spark Basics
    1. Background and History
    2. Spark and Hadoop
    3. Spark Concepts and Architecture
    4. Spark eco System (core, spark sql, mlib, streaming)
  3. RDDs
    1. Running Spark in Local Mode
    2. Spark Web UI
    3. Spark Shell
    4. Analyzing Dataset - part 1
    5. Inspecting RDDs
  4. RDDs In Depth
    1. Partitions
    2. RDD Operations / Transformations
    3. RDD Types
    4. Key-Value Pair RDDs
    5. MapReduce on RDD
    6. Caching and Persistence
  5. Spark and Hadoop
    1. Hadoop Intro (HDFS / YARN)
    2. Hadoop + Spark Architecture
    3. Running Spark on Hadoop YARN
    4. Processing HDFS Files Using Spark
  6. Spark API programming
    1. Introduction to Spark API / RDD API
    2. Submitting the First Program to Spark
    3. Debugging / Logging
    4. Configuration Properties
  7. Spark SQL
    1. SQL Context
    2. Defining Tables and Importing Datasets
    3. Querying
  8. Spark Streaming
    1. Streaming Overview
    2. Streaming Operations
    3. Sliding Window Operations
    4. Writing Spark Streaming Applications
  9. Spark Mlib
    1. mlib Intro
    2. mlib Algorithms
    3. Writing mlib Applications
  10. Spark GraphX
    1. GraphX Library Overview
    2. GraphX APIs
    3. Processing Graph Data Using Spark
  11. Spark Performance and Tuning
    1. Broadcast Variables
    2. Accumulators
    3. Memory Management
  12. Bonus Lab: Running Spark in Cluster Mode
    1. Inspecting Master / Workers in UIs
    2. Configurations
    3. Distributed Processing of Large Data Sets
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this Spark class:

  • Familiarity with either Java / Scala / Python language (labs are in Scala and Python).
  • Basic understanding of Linux development environment (command line navigation / editing files using VI or nano).
Prerequisite Courses

Courses that can help you meet these prerequisites:

Preparing for Class

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Contact Us or call 1-877-932-8228