Cassandra authoritative guide

Cassandra authoritative guide

 

Basic Information

Author:

(US) Eben Hewitt [Translator's introduction]

Translator: Wang Xu

Series name: Turing programming Series

Press: People's post and telecommunications Press

ISBN: 9787115251121

Mounting time: 2011-7-4

Publication date:August 2011

Http://product.china-pub.com/198403

Online reading of Cassandra's authoritative guide to e-books

Introduction

If you can store infinite data on a large scale, what will you do with them? In this practical guide, you will learn how Apache Cassandra saves hundreds of TB of data in multiple data centers and provides highly available services. These features make Facebook, Twitter, and other companies with massive data exciting. Cassandra's authoritative guide describes the technical details of Cassandra and outstanding examples of using Cassandra in production systems.
The author of this book, Eben Hewitt, describes the advantages of Cassandra's non-relational design and focuses on its data model. This book shows Cassandra's speed and flexibility to developers, DBAs, application architects, and managers looking for database scalability solutions.

 
Directory

Cassandra authoritative guide
Chapter 1 Cassandra Overview 1
1.1 What is the problem with relational databases? 1
1.2 brief review of relational databases 5
1.2.1 RDBMS: outstanding performance and average performance
1.2.2 Internet scale 12
1.3 Cassandra's elevator room speech 13
1.3.1 50 characters introduction Cassandra 13
1.3.2 distributed and decentralized 13
1.3.3 elastic scalability 14
1.3.4 high availability and fault tolerance 15
1.3.5 adjustable consistency 15
1.3.6 Brewer cap theory 18
1.3.7 line 21
1.3.8 no schema 22
1.3.9 High Performance 22
1.4 where does Cassandra come from 22
1.5 Cassandra Application Scenario 23
1.5.1 large-scale deployment 23
1.5.2 write intensive, statistical, and analytical work 24

. 1.5.3 regional distribution 24
1.5.4 changed Applications 24
1.6 who is using Cassandra 24
1.7 Summary 26
Chapter 2 install Cassandra 27
2.1 install Binary Package 27
2.1.1 decompress 27
2.1.2 What is in 27
2.2 compile from source code 28
2.2.1 Other compilation targets 30
2.2.2 use Maven to compile 30
2.3 run Cassandra 30
2.3.1 run Cassandra 31 on Windows
2.3.2 run Cassandra 31 in Linux
2.3.3 start server 32
2.4 client using the command line interface 33
2.5 basic command line command 34
2.5.1 help 34
2.5.2 connect to server 35
2.5.3 Environment Description 35
2.5.4 create keyspace and column family 36
2.5.5 read and write data 37
2.6 summary 38
Chapter 3 Cassandra Data Model 39
3.1 Relational Data Model 39
3.2 Overview 40
3.3 cluster 43
3.4 keyspaces 43
3.5 columnfamily 44
3.6 columns 46
3.6.1 wide and narrow rows 48
3.6.2 column sorting 49
3.7 super column 50
3.8 design differences between Cassandra and RDBMS 53
3.8.1 no Query Language 53
3.8.2 no reference integrity 53
3.8.3 second index 53
3.8.4 sorting becomes a design decision 54
3.8.5 anti-paradigm 54
3.9 design mode 55
3.9.1 materialized view 56
3.9.2 no value column 56
3.9.3 aggregation key 56
3.10 several things to remember 57
3.11 summary 57
Chapter 5 Application Example 59
4.1 Data Model Design 59
4.2 Relational Database Design for hotel applications 60
4.3 Cassandra Design for hotel applications 61
4.4 hotel application code 62
4.4.1 create a database 63
4.4.2 Data Structure 64
4.4.3 connect 65
4.4.4 pre-installed database 66
4.4.5 search application 78
4.5 twissandra 82
4.6 Summary 82
Chapter 3 Cassandra architecture 83
5.1 system keyspace 83
5.2 peer-to-peer structure (P2P) 84
5.3 gossip and Fault Detection 84
5.4 inverse entropy and read restoration 86
5.5 memtables, sstable, and commit log 87
5.6 request for handover 89
5.7 compression 89
5.8 bloom filter 91's
5.9 tombstone 91
5.10 phased event-driven architecture 92
5.11 manager and service 93
5.11.1 Cassandra daemon 93
5.11.2 storage service 93
5.11.3 Message Service 93
5.11.4 prompt transfer manager 94
5.12 summary 94
Chapter 4 configure Cassandra 95
6.1 keyspace 95
6.1.1 create a columnfamily 98
6.1.2 migration from 0.6 to 0.7 99
6.2 copy 99
6.3 copy placement policy 100
6.3.1 policy 101
6.3.2 old network topology policy 102
6.3.3 network topology policy 103
6.4 copy factor 103
6.5 partition machine 105
6.5.1 random partition server 106
6.5.2 ordered partition server 106
6.5.3 configure the orderly partition server 107
6.5.4 bytecode splitter 107
6.6 snitch 107
6.6.1 simple snitch 107
6.6.2 propertyfilesnitch 107
6.7 create a cluster 108
6.7.1 modify cluster name 109
6.7.2 add node 109 to the Cluster
6.7.3 multi-seed node 111
6.8 dynamic join ring 113
6.9 Security 114
6.9.1 use simpleauthenticator 114
6.9.2 programming authentication 117
6.9.3 use MD5 encryption 118
6.9.4 provide your own authentication algorithm 118
6.10 miscellaneous settings 119
6.11 additional tool 120
6.11.1 view key value 120
6.11.2 import the configuration of the previous version 120
6.12 conclusion 122
Chapter 4 read and write data 7th
7.1 differences between Cassandra and RDBMS 123
7.1.1 no update query 123
7.1.2 record-level write atomicity 123
7.1.3 server transaction 123 not supported
7.1.4 no duplicate key value 124
7.2 basic attributes of write operations 124
7.3 consistency level 124
7.4 basic attributes of read Operations 126
7.5 API 126
7.6 set and insert data 128
7.7 use simple get 133
7.8 data preparation 135
7.9 slice predicates 135
7.9.1 Use get slice to read a specific column name 136
7.9.2 get a group of columns 137 through the slice interval
7.9.3 retrieve all columns in a row 138
7.10 get range slices 138
7.11 multiget slice 140
7.12 Delete 142
7.13 batch change 144
7.13.1 batch Delete 144
7.13.2 ghost film 145
7.14 programming definition keyspace and column family 145
7.15 conclusion 146
Chapter 4 client 8th
8.1 basic client API 148
8.2 thrift 148
8.2.1 thrift supports Java 151
8.2.2 151 exception
8.2.3 thrift summary 152
8.3 Avro 152
8.3.1 Avro ant target 154
8.3.2 Avro specification 155
8.3.3 Avro summary 156
8.4 git introduction 156
8.5 connect to client node 157
8.5.1 client list 157
8.5.2 cyclic DNS 157
8.5.3 Server Load balancer 157
8.6 Cassandra Web Console 157
8.7 Hector (Java) 161
8.7.1 feature 161
8.7.2 Hector API 162
8.8 hectorsharp (C #) 162
8.9 chirper 167
8.10 chiton (Python) 167
8.11 Pelops (Java) 168
8.12 Kundera (Java ORM) 169
8.13 fauna (Ruby) 169
8.14 Conclusion 170
Chapter 4 Monitoring 9th
9.1 log 171
9.1.1 Tracking View 173
9.1.2 general tips 174
9.2 JMX and mbean overview 175
9.2.1 mbean 177
9.2.2 integrate JMX 179
9.3 interaction with Cassandra through JMX 180
9.4 Cassandra mbean 181
9.4.1 org. Apache. Cassandra. Concurrent 185
9.4.2 org. Apache. Cassandra. db.185
9.4.3 org. Apache. Cassandra. GMS 186
9.4.4 org. Apache. Cassandra. Service 186
9.5 customize Cassandra mbean 188
9.6 runtime analysis tool 190
9.6.1 use JMX and jhat for heap analysis 191
9.6.2 thread problems discovered 194
9.7 health check 195
9.8 conclusion 196
Chapter 4 Maintenance 10th
10.1 obtain information about the ring 198
10.1.1 info 198
10.1.2 ring 198
10.2 obtain statistics 199
10.2.1 cfstats 199
10.2.2 tpstats 200
10.3 basic maintenance 201
10.3.1 repair 201
10.3.2 flushing 202
10.3.3 cleaning 203
10.4 snapshot 203
10.4.1 perform snapshot 203
10.4.2 clear snapshots 204
10.5 Load Balancing for clusters 205
10.6 server return node 208
10.7 update node 210
10.7.1 Delete token 210
10.7.2 compression threshold 210
10.7.3 change the columnfamily 210 in a working Cluster
10.8 conclusion 211
Chapter 2 Performance Tuning 11th
11.1 data storage 213
11.2 reply timeout 215
11.3 commit log 215
11.4 memtable 216
11.5 concurrency 216
11.6 cache 217
11.7 buffer size 218
11.8 use Python stress testing 218
11.8.1 generate Python thrift interface 218
11.8.2 run Python pressure test 220
11.9 start and JVM settings 222
11.10 conclusion 224
Chapter 2 integration with hadoop 12th
12.1 what is hadoop 225
12.2 use mapreduce 226
12.3 running word count example 227
12.3.1 output data to Cassandra 229
12.3.2 hadoop stream 229
12.4 mapreduce tools 229
12.4.1 pig 230
12.4.2 hive 231
12.5 cluster configuration 231
12.6 Case 233
12.6.1 raptr.com: Keith thornhill.233
12.6.2 imagini: Dave Gardner 233
12.7 conclusion 234
Appendix Non-relational database overview 235