In-depth nosql

Deep nosql
Basic Information
Original Title: Professional nosql
Author: (printed) Tiffany [Translator's introduction]
Translator: jucheng
Press: People's post and telecommunications Press
ISBN: 9787115296382
Mounting time:
Published on: February 1, November 2012
Start: 16
Page number: 1
Version: 1-1
Category: Computer> database> SQL language

For more information, see deep nosql.

Introduction
Books
Computer books
Deep nosql is a comprehensive guide to nosql practices. The book focuses on the basic concepts of nosql and practical solutions for using nosql databases. The book introduces mapreduce-based scalable processing, demonstration of hadoop cases, as well as high-level abstraction such as hive and pig. This book contains many use cases and discusses the Scalable Data Architecture of Google, Amazon, Facebook, Twitter, and LinkedIn.
Deep nosql is suitable for nosql database administrators and developers.
Directory
Deep nosql
Part 1 nosql getting started
Chapter 2 concept and applicability of nosql 2
1.1 Definition and Introduction 3
1.1.1 background and history 3
1.1.2 big data 5
1.1.3 scalability 7
1.1.4 mapreduce 8
1.2 column-oriented ordered storage 9
1.3 Key/value storage 11
1.4 document database 14
1.5 graph database 15
1.6 Summary 16
Chapter 1 nosql getting started experience 17
2.1 first impression-two simple examples 17
2.1.1 simple location preference dataset 17
2.1.2 store automobile brand and model data 22
2.2 use multiple languages 30
2.2.1 MongoDB driver 30
2.2.2 first knowledge thrift 33
2.3 Summary 34
Chapter 1 nosql interfaces and interaction 36
3.1 What else is SQL? 36
3.1.1 data storage and access 37
3.1.2 MongoDB data storage and access 37
3.1.3 MongoDB Data Query 41
3.1.4 redis data storage and access 43
3.1.5 redis Data Query 47
3.1.6 hbase data storage and access 50
3.1.7 hbase Data Query 52
3.1.8 Apache Cassandra data storage and access 54
3.1.9 Apache Cassandra Data Query 55
3.2 nosql data storage language binding 56
3.2.1 thrift 56
3.2.2 Java 56
3.2.3 Python 58
3.2.4 Ruby 59
3.2.5 PHP 59
3.3 conclusion 60
Part 2 nosql Basics
Chapter 2 Understanding Storage Architecture 62
4.1 Use column-oriented database 63
4.1.1 use relational database tables and columns 63
4.1.2 comparison between column databases and RDBMS 65
4.1.3 column database as a key/value pair nested ing Table 67
4.1.4 webtable layout 70
4.2 hbase Distributed Storage Architecture 71
4.3 internal mechanism of document storage 73
4.3.1 use memory ing files to store data 74
4.3.2 guide to MongoDB collection and indexing 75
4.3.3 MongoDB reliability and durability 75
4.3.4 horizontal scaling 76
4.4 key/value storage memcached and redis 78
4.4.1 internal structure of memcached 78
4.4.2 internal structure of redis 79
4.5 eventual consistency non-relational database 80
4.5.1 consistent hash 81
4.5.2 object version 82
4.5.3 gossip agreement and prompt transfer 83
4.6 Summary 83
Chapter 4 perform crud operations 84
5.1 create record 84
5.1.1 create a record in a document-centric database 85
5.1.2 create a column database 91
5.1.3 create a key/value ing table 93
5.2 access data 96
5.2.1 access document 96 with MongoDB
5.2.2 use hbase to access data 97
5.2.3 query redis 98
5.3 Update and delete data 98
5.3.1 update and modify data using MongoDB, hbase, and redis 98
5.3.2 limited atomicity and transaction integrity 99
5.4 Conclusion 100
Chapter 1 query nosql storage 6th
6.1 similarity between SQL and MongoDB query functions 101
6.1.1 load movielens data 103
6.1.2 mapreduce 108 in MongoDB
6.2 access data in column-oriented databases such as hbase 111
6.3 querying redis data storage 113
6.4 conclusion 116
Chapter 5 modifying data storage and management evolution 7th
7.1 modify document database 117
7.1.1 weak schema flexibility 120
7.1.2 MongoDB data import and export 121
7.2 evolution of data schema in column-oriented databases 124
7.3 hbase data import and export 125
7.4 data evolution in key/value storage 126
7.5 conclusion 126
Chapter 2 Data Indexing and sorting 8th
8.1 basic concepts of database indexes 127
8.2 MongoDB index and sorting 128
8.3 create and use indexes in MongoDB 131
8.3.1 composite and nested key 136
8.3.2 create unique and sparse indexes 138
8.3.3 keyword-based search and multi-key 139
8.4 couchdb index and sorting 140
8.5 Apache Cassandra index and sorting 141
8.6 conclusion 143
Chapter 4 Management of transaction and data integrity 9th
9.1 RDBMS and acid 144
9.2 distributed acid system 147
9.2.1 consistency 149
9.2.2 availability 149
9.2.3 partition adequacy 149
9.3 maintain Cap 151
9.3.1 compromise availability 153
9.3.2 compromise partition adequacy 153
9.3.3 compromise consistency 154
9.4 nosql product consistency 155
9.4.1 MongoDB distribution consistency 155
9.4.2 couchdb's final consistency is 155
9.4.3 ultimate consistency of Apache Cassandra 156
9.4.4 membase consistency 157
9.5 conclusion 157
Part 3 familiarity with nosql
Chapter 4 Use nosql 10th in the cloud
10.1 Google App Engine 161
10.1.1 Gae Python SDK: installation, setup, and startup 161
10.1.2 use python for basic Gae Data Modeling 165
10.1.3 query and index 168
10.1.4 filtering and result sorting 170
10.1.5 Java App Engine sdks 172
10.2 Amazon simpledb 175
10.2.1 getting started with simpledb 176
10.2.2 use rest API 178
10.2.3 access simpledb 181 using Java
10.2.4 use simpledb 182 through Ruby and Python
10.3 conclusion 183
Chapter 2 mapreduce Scalable Parallel Processing 11th
11.1 understand mapreduce 186
11.1.1 find the maximum price per share of 188
11.1.2 load historical NYSE market data to couchdb 189
11.2 mapreduce and hbase 192
11.3 mapreduce and Apache mahout 196
11.4 conclusion 197
Chapter 1 use hive to analyze big data 12th
12.1 hive basics 199
12.2 back to movie rating 203
12.3 friendly SQL 209
12.4 hiveql connection 211
12.4.1 interpretation of the Plan 213
12.4.2 Partition Table 215
12.5 conclusion 215
Chapter 2 overview of internal database 13th
13.1 MongoDB internal 217
13.1.1 MongoDB transfer protocol 218
13.1.2 insert document 219
13.1.3 query set 219
13.1.4 MongoDB database file 220
13.2 membase architecture 222
13.3 hypertable bottom layer 224
13.3.1 Regular Expressions support 224.
13.3.2 bloom filter 224
13.4 Apache Cassandra 225
13.4.1 point-to-point model 225
13.4.2 Based on gossip and antientropy 225
13.4.3 write 226 quickly
13.4.4 prompt for transfer 226
13.5 Berkeley dB 226
13.6 conclusion 228
Part 4 learn about nosql
Chapter 1 select nosql 14th
14.1 comparison of nosql products 230
14.1.1 scalability 230
14.1.2 transaction integrity and consistency 233
14.1.3 Data Model 233
14.1.4 query supports 235
14.1.5 interface availability 236
14.2 Performance Testing 237
14.2.1 50/50 read and update 237
14.2.2 95/5 read and update 237
14.2.3 scan 238
14.2.4 238 scalability Test
14.2.5 hypertable test 238
14.3 background comparison 239
14.4 conclusion 240
Chapter 2 coexistence 15th
15.1 use MySQL as nosql 241
15.2 static data storage 244
15.2.1 applications of diversified storage in Facebook 245
15.2.2 Data Warehouse and business intelligence 246
15.3 Web framework and nosql 247
15.3.1 rails and nosql 247
15.3.2 Django and nosql 248
15.3.3 use spring data 250.
15.4 migrate data from RDBMS to nosql 254
15.5 conclusion 254
Chapter 2 Performance Tuning 16th
16.1 goal of parallel algorithms: 256
16.1.1 definition of latency reduction 256
16.1.2 how to increase throughput by 257
16.1.3 linear expansion 257
16.2 formulas and models 257
16.2.1 Amdahl law 257
16.2.2 little law 258
16.2.3 message cost model 259
16.3 partition 259
16.4 planning heterogeneous environments 260
16.5 other mapreduce tuning 261
16.5.1 communication cost: 261
16.5.2 compression 261
16.5.3 file block size: 261
16.5.4 parallel replication 262
16.6 hbase coprocessor 262
16.7 bloom filter 262
16.8 conclusion 262
Chapter 4 tools and utilities 17th
17.1 rrdtool 263
17.2 Nagios 265
17.3 scribe 266
17.4 flume 267
17.5 chukwa 267
17.6 pig 268
17.6.1 pig 269
17.6.2 pig latin basics 269
17.7 nodetool 271
17.8 opentsdb 272
17.9 solandra 273
17.10 hummingbird and c5t 274
17.11 geocouch 275
17.12 alchemy database 276
17.13 webdis 276
17.14 conclusion 276
Appendix A installation and configuration 278

Source of this book: China Interactive publishing network