Fast Data Processing Systems with SMACK Stack

Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles!
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Fast Data Processing Systems with SMACK Stack

Raúl Estrada Aparicio

Combine the incredible powers of Spark, Mesos, Akka, Cassandra, and Kafka to build data processing platforms that can take on even the hardest of your data troubles!
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Book Details

ISBN 139781786467201
Paperback376 pages

Book Description

SMACK is an open source full stack for big data architecture. It is a combination of Spark, Mesos, Akka, Cassandra, and Kafka. This stack is the newest technique developers have begun to use to tackle critical real-time analytics for big data. This highly practical guide will teach you how to integrate these technologies to create a highly efficient data analysis system for fast data processing.

We’ll start off with an introduction to SMACK and show you when to use it. First you’ll get to grips with functional thinking and problem solving using Scala. Next you’ll come to understand the Akka architecture. Then you’ll get to know how to improve the data structure architecture and optimize resources using Apache Spark.

Moving forward, you’ll learn how to perform linear scalability in databases with Apache Cassandra. You’ll grasp the high throughput distributed messaging systems using Apache Kafka. We’ll show you how to build a cheap but effective cluster infrastructure with Apache Mesos. Finally, you will deep dive into the different aspect of SMACK using a few case studies.

By the end of the book, you will be able to integrate all the components of the SMACK stack and use them together to achieve highly effective and fast data processing.

Table of Contents

Chapter 1: An Introduction to SMACK
Modern data-processing challenges
The data-processing pipeline architecture
SMACK technologies
Changing the data center operations
Data expert profiles
Is SMACK for me?
Summary
Chapter 2: The Model - Scala and Akka
The language - Scala
The model - Akka
Summary
Chapter 3: The Engine - Apache Spark
Spark in single mode
Spark core concepts
Resilient distributed datasets
Spark in cluster mode
Spark Streaming
Summary
Chapter 4: The Storage - Apache Cassandra
A bit of history
NoSQL
Apache Cassandra installation
Authentication and authorization (roles)
Backup
Recovery
Spark-Cassandra connector
Summary
Chapter 5: The Broker - Apache Kafka
Introducing Kafka
Installation
Cluster
Architecture
Producers
Consumers
Integration
Administration
Summary
Chapter 6: The Manager - Apache Mesos
The Apache Mesos architecture
Resource allocation
Running a Mesos cluster on AWS
Running a Mesos cluster on a private data center
Scheduling and management frameworks
Apache Aurora
Singularity
Apache Spark on Apache Mesos
Apache Cassandra on Apache Mesos
Apache Kafka on Apache Mesos
Summary
Chapter 7: Study Case 1 - Spark and Cassandra
Spark Cassandra connector
Study case: The Calliope project
Summary
Chapter 8: Study Case 2 - Connectors
Akka and Cassandra
Akka and Spark
Kafka and Akka
Kafka and Cassandra
Summary
Chapter 9: Study Case 3 - Mesos and Docker
Mesos frameworks API
Spark Mesos run modes
Apache Mesos API
Mesos containerizers
Docker containerizers
Summary

What You Will Learn

  • Design and implement a fast data Pipeline architecture
  • Think and solve programming challenges in a functional way with Scala
  • Learn to use Akka, the actors model implementation for the JVM
  • Make on memory processing and data analysis with Spark to solve modern business demands
  • Build a powerful and effective cluster infrastructure with Mesos and Docker
  • Manage and consume unstructured and No-SQL data sources with Cassandra
  • Consume and produce messages in a massive way with Kafka

Authors

Table of Contents

Chapter 1: An Introduction to SMACK
Modern data-processing challenges
The data-processing pipeline architecture
SMACK technologies
Changing the data center operations
Data expert profiles
Is SMACK for me?
Summary
Chapter 2: The Model - Scala and Akka
The language - Scala
The model - Akka
Summary
Chapter 3: The Engine - Apache Spark
Spark in single mode
Spark core concepts
Resilient distributed datasets
Spark in cluster mode
Spark Streaming
Summary
Chapter 4: The Storage - Apache Cassandra
A bit of history
NoSQL
Apache Cassandra installation
Authentication and authorization (roles)
Backup
Recovery
Spark-Cassandra connector
Summary
Chapter 5: The Broker - Apache Kafka
Introducing Kafka
Installation
Cluster
Architecture
Producers
Consumers
Integration
Administration
Summary
Chapter 6: The Manager - Apache Mesos
The Apache Mesos architecture
Resource allocation
Running a Mesos cluster on AWS
Running a Mesos cluster on a private data center
Scheduling and management frameworks
Apache Aurora
Singularity
Apache Spark on Apache Mesos
Apache Cassandra on Apache Mesos
Apache Kafka on Apache Mesos
Summary
Chapter 7: Study Case 1 - Spark and Cassandra
Spark Cassandra connector
Study case: The Calliope project
Summary
Chapter 8: Study Case 2 - Connectors
Akka and Cassandra
Akka and Spark
Kafka and Akka
Kafka and Cassandra
Summary
Chapter 9: Study Case 3 - Mesos and Docker
Mesos frameworks API
Spark Mesos run modes
Apache Mesos API
Mesos containerizers
Docker containerizers
Summary

Book Details

ISBN 139781786467201
Paperback376 pages
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