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Practical Cassandra: A Developer's Approach [Pehme köide]

  • Formaat: Paperback / softback, 208 pages, kõrgus x laius x paksus: 231x178x11 mm, kaal: 336 g
  • Ilmumisaeg: 31-Dec-2013
  • Kirjastus: Addison-Wesley Educational Publishers Inc
  • ISBN-10: 032193394X
  • ISBN-13: 9780321933942
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  • Formaat: Paperback / softback, 208 pages, kõrgus x laius x paksus: 231x178x11 mm, kaal: 336 g
  • Ilmumisaeg: 31-Dec-2013
  • Kirjastus: Addison-Wesley Educational Publishers Inc
  • ISBN-10: 032193394X
  • ISBN-13: 9780321933942
Teised raamatud teemal:
Eric and Russell were early adopters of Cassandra at SimpleReach. In Practical Cassandra, you benefit from their experience in the trenches administering Cassandra, developing against it, and building one of the first CQL drivers. If you are deploying Cassandra soon, or you inherited a Cassandra cluster to tend, spend some time with the deployment, performance tuning, and maintenance chapters If you are new to Cassandra, I highly recommend the chapters on data modeling and CQL.

From the Foreword by Jonathon Ellis, Apache Cassandra Chair

 

Build and Deploy Massively Scalable, Super-fast Data Management Applications with Apache Cassandra

 

Practical Cassandra is the first hands-on developers guide to building Cassandra systems and applications that deliver breakthrough speed, scalability, reliability, and performance. Fully up to date, it reflects the latest versions of Cassandraincluding Cassandra Query Language (CQL), which dramatically lowers the learning curve for Cassandra developers.

 

Pioneering Cassandra developers and Datastax MVPs Russell Bradberry and Eric Lubow walk you through every step of building a real production application that can store enormous amounts of structured, semi-structured, and unstructured data. Drawing on their exceptional expertise, Bradberry and Lubow share practical insights into issues ranging from querying to deployment, management, maintenance, monitoring, and troubleshooting.

 

The authors cover key issues, from architecture to migration, and guide you through crucial decisions about configuration and data modeling. They provide tested sample code, detailed explanations of how Cassandra works under the covers, and new case studies from three cutting-edge users: Ooyala, Hailo, and eBay.

 

Coverage includes

 





Understanding Cassandras approach, architecture, key concepts, and primary use cases and why its so blazingly fast Getting Cassandra up and running on single nodes and large clusters Applying the new design patterns, philosophies, and features that make Cassandra such a powerful data store Leveraging CQL to simplify your transition from SQL-based RDBMSes Deploying and provisioning through the cloud or on bare-metal hardware Choosing the right configuration options for each type of workload Tweaking Cassandra to get maximum performance from your hardware, OS, and JVM Mastering Cassandras essential tools for maintenance and monitoring Efficiently solving the most common problems with Cassandra deployment, operation, and application development

 
Foreword xiii
Jonathon Ellis
Foreword xv
Paul Dix
Preface xvii
Acknowledgments xxi
About the Authors xxiii
1 Introduction to Cassandra
1(10)
A Greek Story
1(1)
What Is NoSQL?
2(1)
There's No Such Thing as "Web Scale"
2(1)
ACID, CAP, and BASE
2(3)
ACID
3(1)
CAP
3(1)
BASE
4(1)
Where Cassandra Fits In
5(1)
What Is Cassandra?
5(3)
History of Cassandra
6(1)
Schema-less (If You Want)
7(1)
Who Uses Cassandra?
7(1)
Is Cassandra Right for Me?
7(1)
Cassandra Terminology
8(1)
Cluster
8(1)
Homogeneous Environment
8(1)
Node
8(1)
Replication Factor
8(1)
Tunable Consistency
8(1)
Our Hope
9(2)
2 Installation
11(6)
Prerequisites
11(1)
Installation
11(2)
Debian
12(1)
RedHat/CentOS/Oracle
12(1)
From Binaries
12(1)
Configuration
13(2)
Cluster Setup
15(1)
Summary
16(1)
3 Data Modeling
17(10)
The Cassandra Data Model
17(2)
Model Queries---Not Data
19(3)
Collections
22(3)
Sets
22(1)
Lists
23(1)
Maps
24(1)
Summary
25(2)
4 CQL
27(14)
A Familiar Way of Doing Things
27(12)
CQL 1
27(1)
CQL 2
28(1)
CQL 3
28(1)
Data Types
28(2)
Commands
30(7)
Example Schemas
37(2)
Summary
39(2)
5 Deployment and Provisioning
41(10)
Keyspace Creation
41(1)
Replication Factor
41(1)
Replication Strategies
42(1)
SimpleStrategy
42(1)
NetworkTopologyStrategy
42(1)
Snitches
43(3)
Simple
43(1)
Dynamic
43(1)
Rack Inferring
44(1)
EC2
44(1)
Ec2MultiRegion
45(1)
Property File
45(1)
PropertyFileSnitch Configuration
46(1)
Partitioners
46(2)
Byte Ordered
47(1)
Random Partitioners
47(1)
Node Layout
48(1)
Virtual Nodes
48(1)
Balanced Clusters
49(1)
Firewalls
49(1)
Platforms
49(1)
Amazon Web Services
50(1)
Other Platforms
50(1)
Summary
50(1)
6 Performance Tuning
51(18)
Methodology
51(1)
Testing in Production
52(1)
Tuning
52(10)
Timeouts
52(1)
CommitLog
53(1)
MemTables
54(1)
Concurrency
55(1)
Durability and Consistency
55(1)
Compression
56(2)
SnappyCompressor
58(1)
DeflateCompressor
58(1)
File System
58(1)
Caching
59(1)
How Cassandra Caching Works
59(1)
General Caching Tips
59(1)
Global Cache Tuning
60(1)
ColumnFamily Cache Tuning
61(1)
Bloom Filters
61(1)
System Tuning
62(2)
Testing I/O Concurrency
62(1)
Virtual Memory and Swap
63(1)
sysctl Network Settings
64(1)
File Limit Settings
64(1)
Solid-State Drives
64(1)
JVM Tuning
65(2)
Multiple JVM Options
65(1)
Maximum Heap Size
65(1)
Garbage Collection
66(1)
Summary
67(2)
7 Maintenance
69(14)
Understanding nodetool
69(3)
General Usage
71(1)
Node Information
72(1)
Ring Information
72(1)
ColumnFamily Statistics
73(1)
Thread Pool Statistics
74(2)
Flushing and Draining
75(1)
Cleaning
75(1)
upgradesstables and scrub
76(1)
Compactions
76(3)
What, Where, Why, and How
76(1)
Compaction Strategies
77(1)
Impact
77(2)
Backup and Restore
79(2)
Are Backups Necessary?
79(1)
Snapshots
79(2)
CommitLog Archiving
81(1)
archive_command
81(1)
restore_command
81(1)
restore_directories
81(1)
restore_point_in_time
82(1)
CommitLog Archiving Notes
82(1)
Summary
82(1)
8 Monitoring
83(16)
Logging
83(2)
Changing Log Levels
84(1)
Example Error
84(1)
JMX and MBeans
85(6)
JConsole
86(5)
Health Checks
91(5)
Nagios
91(3)
Cassandra-Specific Health Checks
94(2)
Cassandra Interactions
96(1)
Summary
96(3)
9 Drivers and Sample Code
99(20)
Java
100(4)
C#
104(4)
Python
108(4)
Ruby
112(5)
Summary
117(2)
10 Troubleshooting
119(8)
Toolkit
119(2)
iostat
119(1)
dstat
120(1)
nodetool
121(1)
Common Problems
121(5)
Slow Reads, Fast Writes
122(1)
Freezing Nodes
123(1)
Tracking Down OOM Errors
124(1)
Ring View Differs between Nodes
124(1)
Insufficient User Resources
124(2)
Summary
126(1)
11 Architecture
127(8)
Meta Keyspaces
127(2)
System Keyspace
127(1)
Authentication
128(1)
Gossip Protocol
129(1)
Failure Detection
130(1)
CommitLogs and MemTables
130(1)
SSTables
130(1)
HintedHandoffs
131(1)
Bloom Filters
131(3)
Compaction Types
132(1)
Tombstones
132(1)
Staged Event-Driven Architecture
133(1)
Summary
134(1)
12 Case Studies
135(14)
Ooyala
135(2)
Hailo
137(4)
Taking the Leap
138(1)
Proof Is in the Pudding
139(1)
Lessons Learned
140(1)
Summary
141(1)
eBay
141(6)
eBay's Transactional Data Platform
141(1)
Why Cassandra?
142(1)
Cassandra Growth
143(1)
Many Use Cases
143(3)
Cassandra Deployment
146(1)
Challenges Faced and Lessons Learned
147(1)
Summary
147(2)
A Getting Help
149(2)
Preparing Information
149(1)
IRC
149(1)
Mailing Lists
149(2)
B Enterprise Cassandra
151(6)
DataStax
151(1)
Acunu
152(1)
Titan by Aurelius
153(1)
Pentaho
154(1)
Instaclustr
154(3)
Index 157
Russell Bradberry (Twitter: @devdazed) is the principal architect at SimpleReach, where he is responsible for designing and building out highly scalable, high-volume, distributed data solutions. He has brought to market a wide range of products, including a real-time bidding ad server, a rich media ad management tool, a content recommendation system, and, most recently, a real-time social intelligence platform. He is a U.S. Navy veteran, a DataStax MVP for Apache Cassandra, and the author of the NodeJS Cassandra driver Helenus.







Eric Lubow (Twitter: @elubow) is currently chief technology officer of SimpleReach, where he builds highly scalable, distributed systems for processing social data. He began his career building secure Linux systems. Since then he has worked on building and administering various types of ad systems, maintaining and deploying large-scale Web applications, and building email delivery and analytics systems. He is also a U.S. Army combat veteran and a DataStax MVP for Apache Cassandra.







Eric and Russ are regular speakers about Cassandra and distributed systems, and both live in New York City.