Introduction to Spark with Python

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Course Benefits

  • Understand the need for Spark in data processing
  • Understand the Spark architecture and how it distributes computations to cluster nodes
  • Be familiar with basic installation / setup / layout of Spark
  • Use the Spark shell for interactive and ad-hoc operations
  • Understand RDDs (Resilient Distributed Datasets), and data partitioning, pipelining, and computations
  • Understand/use RDD ops such as map(), filter() and others.
  • Understand and use Spark SQL and the DataFrame API.
  • Understand the DataFrame capabilities, including the Catalyst query optimizer and Tungsten memory/cpu optimizations.
  • Be familiar with performance issues, and use DataFrames and Spark SQL for efficient computations
  • Understand Spark‚Äôs data caching and use it for efficient data transfer
  • Write/run standalone Spark programs with the Spark API
  • Use Spark Structured Streaming to process streaming (real-time) data
  • Ingest streaming data from Kafka, and process via Spark Structured Streaming
  • Understand performance implications and optimizations when using Spark
Available Delivery Methods
Public Class
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private Class
Private classes are delivered for groups at your offices or a location of your choice.

Course Outline

  1. Introduction to Spark
    1. Overview, Motivations, Spark Systems
    2. Spark Ecosystem
    3. Spark vs. Hadoop
    4. Acquiring and Installing Spark
    5. The Spark Shell, SparkContext
  2. RDDs and Spark Architecture
    1. RDD Concepts, Lifecycle, Lazy Evaluation
    2. RDD Partitioning and Transformations
    3. Working with RDDs - Creating and Transforming (map, filter, etc.)
  3. Spark SQL, DataFrames, and DataSets
    1. Overview
    2. SparkSession, Loading/Saving Data, Data Formats (JSON, CSV, Parquet, text ...)
    3. Introducing DataFrames (Creation and Schema Inference)
    4. Supported Data Formats (JSON, Text, CSV, Parquet)
    5. Working with the DataFrame (untyped) Query DSL (Column, Filtering, Grouping, Aggregation)
    6. SQL-based Queries
    7. Mapping and Splitting (flatMap(), explode(), and split())
    8. DataFrames vs. RDDs
  4. Shuffling Transformations and Performance
    1. Grouping, Reducing, Joining
    2. Shuffling, Narrow vs. Wide Dependencies, and Performance Implications
    3. Exploring the Catalyst Query Optimizer (explain(), Query Plans, Issues with lambdas)
    4. The Tungsten Optimizer (Binary Format, Cache Awareness, Whole-Stage Code Gen)
  5. Performance Tuning
    1. Caching - Concepts, Storage Type, Guidelines
    2. Minimizing Shuffling for Increased Performance
    3. Using Broadcast Variables and Accumulators
    4. General Performance Guidelines
  6. Creating Standalone Applications
    1. Core API, SparkSession.Builder
    2. Configuring and Creating a SparkSession
    3. Building and Running Applications - sbt/build.sbt and spark-submit
    4. Application Lifecycle (Driver, Executors, and Tasks)
    5. Cluster Managers (Standalone, YARN, Mesos)
    6. Logging and Debugging
  7. Spark Streaming
    1. Introduction and Streaming Basics
    2. Streaming Introduction
    3. Structured Streaming (Spark 2+)
    4. Continuous Applications
    5. Table Paradigm, Result Table
    6. Steps for Structured Streaming
    7. Sources and Sinks
    8. Consuming Kafka Data
    9. Kafka Overview
    10. Structured Streaming - "kafka" format
    11. Processing the Stream

Class Materials

Each student will receive 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:

  • Working knowledge of some programming language. No Python experience necessary.
Since its founding in 1995, InterSource has been providing high quality and highly customized training solutions to clients worldwide. With over 500 course titles constantly updated and numerous course customization and creation possibilities, we have the capability to meet your I.T. training needs.
Instructor-led courses are offered via a live Web connection, at client sites throughout Europe, and at our Geneva Training Center.