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E-raamat: Complete Guide to Open Source Big Data Stack

  • Formaat: EPUB+DRM
  • Ilmumisaeg: 18-Jan-2018
  • Kirjastus: APress
  • Keel: eng
  • ISBN-13: 9781484221495
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Complete Guide to Open Source Big Data StackSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 18-Jan-2018
  • Kirjastus: APress
  • Keel: eng
  • ISBN-13: 9781484221495
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See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together.



In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stacksharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more.



What Youll Learn









Install a private cloud onto the local cluster using Apache cloud stack

Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin

See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud

Install and use DCOS for big data processing Use Apache Spark for big data stack data processing





Who This Book Is For

Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.
About the Author xiii
About the Technical Reviewer xv
Acknowledgments xvii
Introduction xix
Chapter 1 The Big Data Stack Overview
1(16)
What Is Big Data?
2(2)
Limitations of Approach
4(1)
Why a Stack?
5(1)
NoSQL Overview
6(1)
Development Stacks
7(1)
LAMP Stack
7(1)
MEAN Stack
7(1)
SMACK Stack
7(1)
MARQS Stack
7(1)
Book Approach
8(9)
Chapter 2 Cloud Storage
9(1)
Chapter 3 Release Management - Brooklyn
9(1)
Chapter 4 Resource Management
10(1)
Chapter 5 Storage
10(1)
Chapter 6 Processing
10(1)
Chapter 7 Streaming
11(1)
Chapter 8 Frameworks
11(1)
Chapter 9 Data Visualisation
11(1)
Chapter 10 The Big Data Stack
11(1)
The Full Stack
11(2)
Cloud or Cluster
13(2)
The Future
15(2)
Chapter 2 Cloud Storage
17(42)
CloudStack Overview
18(2)
Server Preparation
20(8)
Minimum System Requirements
20(2)
Check CentOS Install
22(1)
Secure Shell (SSH) Access
22(1)
Configure Network
23(1)
Check Hostname FQDN
23(1)
Configure SELinux
24(1)
Configure NTP
24(1)
Configure CloudStack Package Repository
25(1)
Configure NFS (Network File System)
25(3)
CloudStack Server Install
28(3)
MySQL Server Install
28(1)
MySQL Connector Installation
29(1)
Management Server Installation
30(1)
System Template Setup
30(1)
KVM Setup and Installation
31(4)
Prerequisites
31(1)
Create Repository File
32(1)
KVM Installation
32(1)
KVM QEMU (Quick Emulator) Configuration
32(1)
Libvirt Configuration
33(1)
Check KVM Running
33(1)
Host Naming
34(1)
CloudStack Cluster Configuration
35(16)
Adding Hosts to the Cloud
40(4)
Adding an Instance to the Cloud
44(1)
Registering an ISO with CloudStack
44(2)
Creating an Instance from an ISO
46(5)
Advanced Zone Creation
51(7)
Problem-Solving
55(1)
CloudStack Log Files
56(1)
CloudStack Storage
56(1)
CloudStack System VMs
57(1)
CloudStack Firewall Issues
57(1)
Conclusion
58(1)
Chapter 3 Apache Brooklyn
59(38)
Brooklyn Install
59(10)
Brooklyn Overview
69(5)
Blueprints
70(1)
REST API
71(1)
Policy Management
72(1)
Monitoring
73(1)
Operations
73(1)
Modelling With Blueprints
74(1)
Application Installs
74(21)
Server-Based Install
75(10)
Cloud-Based Install
85(10)
Conclusion
95(2)
Chapter 4 Apache Mesos
97(42)
Mesos Architecture
98(1)
Mesos Install
99(16)
Overview
99(1)
Building Mesos
100(8)
Starting Mesos
108(1)
Mesos User Interface
109(5)
Build Errors
114(1)
Mesosphere DCOS
115(20)
Overview
115(1)
SSH configuration
115(2)
Install Prerequisites
117(4)
Install Server
121(3)
Master Server
124(2)
Agent Server
126(1)
User Interfaces
127(4)
Logging and Problem Investigation
131(1)
Build Errors
132(3)
Project Myriad
135(2)
Myriad Architecture
135(2)
Conclusion
137(2)
Chapter 5 Stack Storage Options
139(38)
HDFS Mesos Framework
141(10)
Source Software
141(1)
Start Scheduler
142(2)
Create and Start HDFS Nodes
144(4)
Use HDFS Mesos Framework
148(3)
Riak Mesos Framework
151(13)
VirtualBox Install
152(2)
Vagrant Install
154(1)
Install Framework
154(6)
Use Framework
160(4)
Cassandra Mesos Framework
164(11)
Install Prerequisites
165(1)
Install X Windows
165(1)
Install VirtualBox and Vagrant
166(1)
Install Vagrant-Based DCOS
167(5)
Install Cassandra
172(3)
Conclusion
175(2)
Chapter 6 Processing
177(42)
Stack Architecture
178(1)
Server Preparation
179(2)
Mesos and Spark
181(17)
Build Mesos Part 1
181(1)
Build Mesos Part 2
182(1)
Build Mesos Part 3
183(1)
Building the Mesos Source
184(2)
Starting Mesos
186(1)
Installing the HDFS Framework
187(5)
Running Spark
192(6)
DCOS and Spark
198(19)
DCOS Build Part 1
198(1)
DCOS Build Part 2
199(1)
DCOS Build Part 3---Install Server
200(3)
DCOS Master Server Install
203(1)
DCOS Agent Server Install
203(1)
User Interfaces
204(1)
DCOS CLI Command Install
205(4)
Running a Spark Application
209(4)
Problem Tracking
213(4)
Conclusion
217(2)
Chapter 7 Streaming
219(40)
DCOS Issues
221(4)
Port Conflict Issues
221(1)
Firewall Issues
222(1)
Network Time Synchronisation
223(1)
ZooKeeper Issues
224(1)
The Kafka System
225(2)
Installing Kafka
227(9)
DCOS Ul Kafka Install
227(5)
DCOS CLI Kafka Install
232(4)
Kafka Management Using the CLI
236(10)
Kafka Management Using Spark
246(11)
Conclusion
257(2)
Chapter 8 Frameworks
259(36)
Akka
261(16)
OOP Overview
261(1)
Distributed Systems Issues
262(2)
Akka Architecture
264(3)
Actors
267(3)
Networking
270(3)
Streams
273(3)
Other Modules
276(1)
Enterprise Offerings
277(1)
Netty
277(5)
Spring
282(11)
RabbitMQ Overview
283(1)
Kafka or RabbitMQ?
284(1)
Messaging Protocols
284(1)
Languages
285(1)
Clustering
286(1)
Enterprise Support
287(1)
Routing
288(2)
Plug-ins
290(1)
Administration
291(2)
Conclusion
293(2)
Chapter 9 Visualisation
295(44)
Apache Zeppelin
296(20)
Interpreters
297(2)
Worked Example
299(5)
Graph Options
304(3)
Notebook Import
307(1)
Dynamic Forms
308(2)
Scheduling Notebook
310(1)
Sharing Session Output
311(1)
Helium
312(4)
Multi-user Support
316(1)
Possible Extensions
316(1)
Grafana
316(8)
Datadog
324(12)
Conclusion
336(3)
Chapter 10 The Big Data Stack
339(18)
Hardware Architecture
340(2)
Chapter Topics
342(6)
Chapter 2 Cloud
343(1)
Chapter 3 Brooklyn
343(1)
Chapter 4 Resource Management
344(1)
Chapter 5 Storage
345(1)
Chapter 6 Processing
345(1)
Chapter 7 Queueing
346(1)
Chapter 8 Frameworks
347(1)
Chapter 9 Visualisation
347(1)
Application Architecture
348(1)
Application Submission
348(1)
Brooklyn and DCOS
349(3)
Stack Monitoring
352(2)
Visualisation
354(1)
Cloud or Cluster
354(1)
Conclusion
355(2)
Index 357
Mike Frampton has been in the IT industry since 1990, working in many roles (tester, developer, support, QA), and in many sectors (telecoms, banking, energy, insurance). He has also worked for major corporations and banks as a contractor and a permanent member of staff, including Agilent, BT, IBM, HP, Reuters, and JP Morgan Chase. The owner of Semtech Solutions, an IT/Big Data consultancy, Mike currently lives by the beach in Paraparaumu, New Zealand, with his wife and son. Mike has a keen interest in new IT-based technologies and the way that technologies integrate. Being married to a Thai national, Mike divides his time between Paraparaumu or Wellington in New Zealand and their house in Roi Et, Thailand.
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