Spark for Developers Training Course

Course

In City Of London

Price on request

Description

  • Type

    Course

  • Location

    City of london

OBJECTIVE:
This course 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.
AUDIENCE :
Developers / Data Analysts

Facilities

Location

Start date

City Of London (London)
See map
Token House, 11-12 Tokenhouse Yard, EC2R 7AS

Start date

On request

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Reviews

Subjects

  • Monitoring
  • Apache
  • SQL
  • Data analysis
  • Algorithms
  • Web
  • Project
  • Writing
  • Programming
  • Broadcast
  • Production

Course programme

  1. Scala primer
    • A quick introduction to Scala
    • Labs : Getting know Scala
  2. Spark Basics
    • Background and history
    • Spark and Hadoop
    • Spark concepts and architecture
    • Spark eco system (core, spark sql, mlib, streaming)
    • Labs : Installing and running Spark
  3. First Look at Spark
    • Running Spark in local mode
    • Spark web UI
    • Spark shell
    • Analyzing dataset – part 1
    • Inspecting RDDs
    • Labs: Spark shell exploration
  4. RDDs
    • RDDs concepts
    • Partitions
    • RDD Operations / transformations
    • RDD types
    • Key-Value pair RDDs
    • MapReduce on RDD
    • Caching and persistence
    • Labs : creating & inspecting RDDs; Caching RDDs
  5. Spark API programming
    • Introduction to Spark API / RDD API
    • Submitting the first program to Spark
    • Debugging / logging
    • Configuration properties
    • Labs : Programming in Spark API, Submitting jobs
  6. Spark SQL
    • SQL support in Spark
    • Dataframes
    • Defining tables and importing datasets
    • Querying data frames using SQL
    • Storage formats : JSON / Parquet
    • Labs : Creating and querying data frames; evaluating data formats
  7. MLlib
    • MLlib intro
    • MLlib algorithms
    • Labs : Writing MLib applications
  8. GraphX
    • GraphX library overview
    • GraphX APIs
    • Labs : Processing graph data using Spark
  9. Spark Streaming
    • Streaming overview
    • Evaluating Streaming platforms
    • Streaming operations
    • Sliding window operations
    • Labs : Writing spark streaming applications
  10. Spark and Hadoop
    • Hadoop Intro (HDFS / YARN)
    • Hadoop + Spark architecture
    • Running Spark on Hadoop YARN
    • Processing HDFS files using Spark
  11. Spark Performance and Tuning
    • Broadcast variables
    • Accumulators
    • Memory management & caching
  12. Spark Operations
    • Deploying Spark in production
    • Sample deployment templates
    • Configurations
    • Monitoring
    • Troubleshooting

Spark for Developers Training Course

Price on request