Cassandra: the definitive guide: [distributed data at web scale]

369 Pages·2015·7.629 MB·English

by  Hewitt, Eben

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C assandra
The Definitive Guide
DISTRIBUTED DATA AT WEB SCALE
Jeff Carpenter & Eben Hewitt

SECOND EDITION
Cassandra: The Definitive Guide
Jeff Carpenter and Eben Hewitt
BBeeiijjiinngg BBoossttoonn FFaarrnnhhaamm SSeebbaassttooppooll TTookkyyoo
Cassandra: The Definitive Guide
by Jeff Carpenter and Eben Hewitt
Copyright © 2016 Jeff Carpenter, Eben Hewitt. All rights reserved.
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June 2016: Second Edition
Revision History for the Second Edition
2010-11-12: First Release
2016-06-27: Second Release
2017-04-07: Third Release
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978-1-491-93366-4
[LSI]
This book is dedicated to my sweetheart, Alison Brown.
I can hear the sound of violins, long before it begins.
—E.H.
For Stephanie, my inspiration, unfailing support,
and the love of my life.
—J.C.

Table of Contents
Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii
1. Beyond Relational Databases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
What’s Wrong with Relational Databases? 1
A Quick Review of Relational Databases 5
RDBMSs: The Awesome and the Not-So-Much 5
Web Scale 12
The Rise of NoSQL 13
Summary 15
2. Introducing Cassandra. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
The Cassandra Elevator Pitch 17
Cassandra in 50 Words or Less 17
Distributed and Decentralized 18
Elastic Scalability 19
High Availability and Fault Tolerance 19
Tuneable Consistency 20
Brewer’s CAP Theorem 23
Row-Oriented 26
High Performance 28
Where Did Cassandra Come From? 28
Release History 30
Is Cassandra a Good Fit for My Project? 35
Large Deployments 35
v
Lots of Writes, Statistics, and Analysis 36
Geographical Distribution 36
Evolving Applications 36
Getting Involved 36
Summary 38
3. Installing Cassandra. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Installing the Apache Distribution 39
Extracting the Download 39
What’s In There? 40
Building from Source 41
Additional Build Targets 43
Running Cassandra 43
On Windows 44
On Linux 45
Starting the Server 45
Stopping Cassandra 47
Other Cassandra Distributions 48
Running the CQL Shell 49
Basic cqlsh Commands 50
cqlsh Help 50
Describing the Environment in cqlsh 51
Creating a Keyspace and Table in cqlsh 52
Writing and Reading Data in cqlsh 55
Summary 56
4. The Cassandra Query Language. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
The Relational Data Model 57
Cassandra’s Data Model 58
Clusters 61
Keyspaces 61
Tables 61
Columns 63
CQL Types 65
Numeric Data Types 66
Textual Data Types 67
Time and Identity Data Types 67
Other Simple Data Types 69
Collections 70
User-Defined Types 73
Secondary Indexes 76
Summary 78
vi | Table of Contents
5. Data Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Conceptual Data Modeling 79
RDBMS Design 80
Design Differences Between RDBMS and Cassandra 81
Defining Application Queries 84
Logical Data Modeling 85
Hotel Logical Data Model 87
Reservation Logical Data Model 89
Physical Data Modeling 91
Hotel Physical Data Model 92
Reservation Physical Data Model 93
Materialized Views 94
Evaluating and Refining 96
Calculating Partition Size 96
Calculating Size on Disk 97
Breaking Up Large Partitions 99
Defining Database Schema 100
DataStax DevCenter 102
Summary 103
6. The Cassandra Architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Data Centers and Racks 105
Gossip and Failure Detection 106
Snitches 108
Rings and Tokens 109
Virtual Nodes 110
Partitioners 111
Replication Strategies 112
Consistency Levels 113
Queries and Coordinator Nodes 114
Memtables, SSTables, and Commit Logs 115
Caching 117
Hinted Handoff 117
Lightweight Transactions and Paxos 118
Tombstones 120
Bloom Filters 120
Compaction 121
Anti-Entropy, Repair, and Merkle Trees 122
Staged Event-Driven Architecture (SEDA) 124
Managers and Services 125
Cassandra Daemon 125
Storage Engine 126
Table of Contents | vii
Storage Service 126
Storage Proxy 126
Messaging Service 127
Stream Manager 127
CQL Native Transport Server 127
System Keyspaces 128
Summary 130
7. Configuring Cassandra. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Cassandra Cluster Manager 131
Creating a Cluster 132
Seed Nodes 135
Partitioners 136
Murmur3 Partitioner 136
Random Partitioner 137
Order-Preserving Partitioner 137
ByteOrderedPartitioner 137
Snitches 138
Simple Snitch 138
Property File Snitch 138
Gossiping Property File Snitch 139
Rack Inferring Snitch 139
Cloud Snitches 140
Dynamic Snitch 140
Node Configuration 140
Tokens and Virtual Nodes 141
Network Interfaces 142
Data Storage 143
Startup and JVM Settings 144
Adding Nodes to a Cluster 144
Dynamic Ring Participation 146
Replication Strategies 147
SimpleStrategy 147
NetworkTopologyStrategy 148
Changing the Replication Factor 150
Summary 150
8. Clients. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Hector, Astyanax, and Other Legacy Clients 151
DataStax Java Driver 152
Development Environment Configuration 152
Clusters and Contact Points 153
viii | Table of Contents