Wheat Academy explains redis in simple terms video material sharing

Redis is a storage system. It supports storing relatively more value types, including string (string), list (linked list), set (set), zset (sorted set - ordered set) and hash (hash type). "Maizi Academy's in-depth redis video tutorial" takes you from shallow to deep understanding of this system.

Redis is a key-value storage system. Similar to Memcached, it supports relatively more stored value types, including string (string), list (linked list), set (set), zset (sorted set - ordered set) and hash (hash type). These data types all support push/pop, add/remove, intersection, union, difference, and richer operations, and these operations are all atomic. On this basis, redis supports various different ways of sorting. Like memcached, data is cached in memory to ensure efficiency. The difference is that redis will periodically write updated data to disk or write modification operations to additional record files, and on this basis, master-slave (master-slave) synchronization is achieved.

Redis is a high-performance key-value database. The emergence of redis has largely compensated for the shortcomings of key/value storage such as memcached, and can play a very good supplementary role to relational databases in some situations. It provides Java, C/C++, C#, PHP, JavaScript, Perl, Object-C, Python, Ruby, Erlang and other clients, which is very convenient to use.

Redis supports master-slave synchronization. Data can be synchronized from the master server to any number of slave servers, and the slave server can be a master server associated with other slave servers. This allows Redis to perform single-level tree replication. Saving can write data intentionally or unintentionally. Since the publish/subscribe mechanism is fully implemented, when the slave database synchronizes the tree anywhere, it can subscribe to a channel and receive the complete message release record of the master server. Synchronization is helpful for scalability and data redundancy of read operations.

Video playback address: http://www.php.cn/course/566.html

Difficulties in learning:

Use nosql:

High performance, demand for DB high concurrency rw (web2.0 websites need to generate dynamic pages and provide dynamic information in real time based on user personalized information, so it is difficult to use dynamic pages Static technology, so the concurrency and load requirements of DB are very high, often reaching tens of thousands of rw times per second. Relational DB including distributed clusters can barely withstand tens of thousands of queries (r), but if it can cope with Tens of thousands of SQL write operations, the physical hard disk IO can no longer bear it. For ordinary large BBS websites, there is a need for high concurrency);

huge storage, high-efficiency storage and access requirements for massive data (for large SNS , users generate massive amounts of dynamic data every day. For example, Friendfeed has 250 million user updates a month. For relational DB, it is extremely inefficient to perform SQL queries in a table with 250 million records; user logins of large web sites Systems, such as tencent, shengda, etc., have hundreds of millions of accounts, which are difficult for relational DB to cope with);

high scalability & high availability, high scalability and high availability requirements (in the Internet website architecture, DB is the most It is difficult to expand horizontally. When the number of users and visits to the application system is increasing day by day, it is difficult for DB to expand performance and load capacity simply by adding hardware nodes like web server and app server. For many websites that need to provide 24-hour uninterrupted business It is very painful to upgrade and expand DB, which often requires downtime maintenance and data migration);

nosql removes the following features of relational DB:

Relationship Type DB data transaction consistency requirements (traditional relational DB must maintain DB transaction consistency requirements, so it cannot meet the needs of high concurrency rw);

DB's r real-time and w real-time requirements (for relational DB Query immediately after inserting a piece of data into the DB and it can be found out, but for many web applications, such high real-time performance is not required);

For complex SQL queries, especially multi-table related query requirements ( Any web system with a large amount of data, especially SNS, is very taboo about correlation queries of multiple large tables and complex data analysis type SQL queries. From the perspective of demand and product design, to avoid this situation, it is often more of a single query. For primary key query of a table and simple conditional paging query of a single table, the function of SQL is greatly weakened);

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