Seven weeks and seven databases

Author: (US) Eric Redmond Translator: Wang Haipeng Tian siyuan Wang Chen Press: People's post and telecommunications Press ISBN: 9787115312242 Release Date: June 2013: 16 open pages: 256 versions: Classification of 1-1: Computer> database> more about "," seven weeks and seven databases, the data we need to face and use is becoming increasingly large and complex. If data is new oil. Then the database is the oil field, refinery, drilling and oil pump. As a modern software developer, we need to understand the new fields of data management, including RDBMS and nosql. The seven weeks and seven databases follow the writing style and style of the seven weeks and seven languages, and lead you to learn and understand the most popular open source databases. After a brief introduction, this book introduces seven types of databases. These databases belong to five different database styles, but each database has its own way of saving data and viewing the world. They are PostgreSQL, Riak, Apache hbase, MongoDB, Apache couchdb, neo4j, and redis in sequence. This book will go deep into each type of database, introduce their advantages and disadvantages, and how to select a database that best meets your application needs. 7-week 7 database is suitable for database architects, database administrators, and programmers who want to learn about and learn about nosql database technologies. This book will help readers understand, select, and apply these databases to better utilize the increasing Big Data capabilities. Database 7 in seven weeks applies to database architects, programmers and database administrators who want to learn nosql database technologies. Table of Contents seven weeks and seven databases chapter 1st overview 11.1 starting from a problem 11.2 style 21.2.1 relational database 31.2.2 key-value database 31.2.3 column-type database 41.2.4 document-type database 51.2.5 graph database 51.2.6 mixed use a variety database 61.3 advances and increases 6 chapter 6 PostgreSQL 2nd this is post-GREs-Q-l 72.1 72.2 days: link, crud and join 82.2.1 start from SQL 102.2.2 use table 102.2.3 use join query 132.2.4 Outer Join 152.2.5 use index quick search 162.2.6 1st day summary 18.2.2.7 1st day job 182.3 2nd day: advanced query, code, and rule 192.3.1 aggregation function 192.3.2 grouping 202.3.3 Window Function 212.3.4 transaction 222.3.5 Stored Procedure 242.3.6 trigger 262.3.7 view 272.3.8 what is a rule 282.3.9 joined table analysis 302.3.10 2nd days summary 322.4 3rd days: full-text search and multi-dimensional query 322.4.1 fuzzy search 342.4.2 SQL standard string matching 342.4.3 string Similarity comparison algorithm levenshtein 352.4.4 three-connected words 362.4.5 full-text search 372.4.6 combination use string matching method 422.4.7 to express the movie style into multi-dimensional super summary of cube 422.4.8 3rd days summary 452.5 Summary of advantages of 462.5.1 PostgreSQL 462.5.2 disadvantages of postgresql 472.5.3 conclusion 47 chapter 3rd Riak 483.1 Riak like Web 483.2 1st days: crud, link, and mime 493.2.1 rest are the best (or when using curl) 513.2.2 place the value in the bucket 523.2.3 link 543.2.4 the MIME type of Riak 583.2.5 1st days summary 583.3 2nd days: mapreduce and server cluster 593.3.1 fill script 593.3.2 mapreduce introduction to mapreduce 633.3.4 in 603.3.3 Riak about consistency and persistence 693.3.5 2nd days summary 753.4 3rd days: resolving conflicts and extending Riak 763.4.1 solving conflicts with vector clock 763.4.2 expanding Riak 833.4.3 summary 3rd summary 873.5 summary 873.5.1 Riak advantages 883.5.2 disadvantages of Riak 883.5.3 Riak in Cap 883.5.4 Conclusion 89 Chapter 4th hbase 904.1 Introduction hbase 914.2 1st days: crud and table management 914.2.1 configure hbase 924.2.2 hbase shell 934.2.3 create table 934.2.4 insert, update and read data 954.2.5 Modify Table 964.2.6 add data 994.2.7 1st days summary 1004.3 2nd days: process Big Data 1014.3.1 import data, call the script 1014.3.2 streaming XML 1024.3.3 streaming Wikipedia 1034.3.4 compression and bloom filter 1054.3.5 to start scanning a table in Region 4.3.6 and monitoring disk usage in Region 4.3.7 4.3.7 to create another table 1114.3.9 build a scanner 1124.3.10 run script 1144.3.11 check output 1144.3.12 2nd days summary 1164.4 3rd days: add the hbase application 1174.4.2 whirr introduction 1214.4.3 to develop the thrift protocol on the cloud and set EC2 1214.4.4 to prepare whirr 1224.4.5 configure the cluster worker to start the cluster 1234.4.7 connect to the cluster worker and destroy the cluster worker 3rd day summary 1254.5 summary advantages 1264.5.2 disadvantages of hbase ipv4.5.3 hbase on CAP ipv4.5.4 conclusion 128 chapter 5th MongoDB 1295.1 extremely large 1295.2 days: crud and nested 1305.2.1 command line fun 1315.2.2 more interesting Mongo content 1345.2.3 in-depth mining 1365.2.4 update 1405.2.5 reference 1425.2.6 Delete 1435.2.7 read 1445.2.8 1st days summary 1455.3 2nd days: index, grouping, and mapreduce 1465.3.1 index: if it is not fast enough, 1465.3.2 Aggregate Query 1505.3.3 server-side command 1525.3.4 mapreduce (and finalize) 1555.3.5 2nd days summary 1595.4 3rd days: replica set, Shard, geospatial and gridfs 1595.4.1 replica set 1595.4.2 even number node issue 1625.4.3 shard geospatial query 1655.4.5 gridfs 1675.4.6 3rd day summary 1685.5 summary 1685.5.1 advantages of Mongo 1685.5.2 disadvantages of Mongo 1695.5.3 conclusion Chapter 4 couchdb 169 relax on the sofa for 6th days: crud, futon, and curl Redux 1716.2.1 enjoy futon 1716.2.2 use curl to perform the rest-based CRUD operation 1756.2.3 use get to read documents 1756.2.4 use post to create documents 1766.2.5 use put to update documents 1776.2.6 use Delete to remove documents 17 day summary 1786.3 2nd days: create/query view 1796.3.1 use the view access document 1796.3.2 compile your first view 1816.3.3 Save the view as "design document" 1836.3.4 search artists 1846.3.5 by name search albums 1846.3.6 query the custom artist use ruby With album view 1856.3.7 to import data to couchdb 1876.3.8 2nd days summary 1926.4 3rd days: advanced view, changes API, and replication data 1926.4.1 create an advanced view with the Statute 1936.4.2 detailed description of protocol calls 1956.4.3 monitor couchdb changes 1966.4.4 continuous monitoring changes 2016.4.5 copy data in couchdb 2046.4.6 3rd days summary 2086.5 summary 2096.5.1 advantages of couchdb 2096.5.2 disadvantages of couchdb 2096.5.3 conclusion 209 chapter 7th neo4j 2117.1 neo4j, whiteboard-friendly database 2117.2 1st days: figure, groovy and crud 2127.2.1 neo4j web interface 7.2.2 use gremlin to operate the power of neo4j 2157.2.3 pipe 2187.2.4 pipeline and vertex 2217.2.5 steps to introduce groovy into specific fields of social data 2217.2.6 stepping stone 2237.2.7 update, delete, and complete 2297.2.10 1st days summary 2307.3 2nd days: rest, index and algorithm 2307.3.1 introduce rest 2307.3.2 create a node with rest and link 2317.3.3 search path 232