时至今日,MongoDB已走过了5个年头,MongoDB 2.6的发布,MongoDB CTO Eliot说这是有史以来(Our Biggest Release Ever)最意义重大的版本。 主要变化: 聚合增强Aggregation Enhancements db.collection.aggregate() 支持返回游标,这意味着可以返回任意记录数
时至今日,MongoDB已走过了5个年头,MongoDB 2.6的发布,MongoDB CTO Eliot说这是有史以来(Our Biggest Release Ever)最意义重大的版本。
主要变化:
聚合增强Aggregation Enhancements
db.collection.aggregate() 支持返回游标,这意味着可以返回任意记录数;支持查询计划explain()
;排序及其他改进,略。
集成全文搜索Text Search Integration
默认支持文本搜索,新的操作符$text.
{ $text: { $search: <string>, $language: <string> } }</string></string>
插入和更新的改进Insert and Update Improvements
_id
字段现在总数在文档第一个字段(你知道以前更新过文档有多乱吗,_id
不知道跑哪去了);
重命名字段的更新可能会导致字段的重新排序;
其他一些新的或者增量的操作符,略。
新的写操作协议
协议上的变化,把写操作和写确认(writeconcerns)集成在一起了,不需要单独调用
getLastError了;
支持批量操作。
安全方面改进
improved SSL support, x.509-based authentication
认证方面的改进,支持集合粒度的角色(可以按照集合去授权或者配置角色了)
查询引擎及索引的改进
这个才是重要的。查询中可以使用多个索引了;
后台索引在从库上也支持了;
创建索引时dropDups 选项删除了;
分片及复制方面增强
改进太少,都不好意思提。新增了一个mergeChunks 命令用来合并两个连续范围的chunks,要求至少一个chunk是空的。
存储方面
默认使用usePowerOf2Sizes,我只能说,好一点,没啥根本性的改进。
其他改进
去除了最大连接数20,000的限制;
工具的一些小改进,包括mongoexport,mongodump,mongostat;
总结及点评
依我看,都是些小的改进,不少是早就应该解决的一些细节问题,改进远没有吹的那么大。
Eliot在博客里吹嘘"From the very beginning, MongoDB has offered developers a simple and elegant way to manage their data.",依我看还远未达到。另外他还顺便推销了他们的MMS服务,什么支持按时间点恢复啦,我只想说,太不方便了,需要用的还是试试本社区的mongobackup吧。
原文地址:解读MongoDB 2.6 发布, 感谢原作者分享。

MySQL is an open source relational database management system, mainly used to store and retrieve data quickly and reliably. Its working principle includes client requests, query resolution, execution of queries and return results. Examples of usage include creating tables, inserting and querying data, and advanced features such as JOIN operations. Common errors involve SQL syntax, data types, and permissions, and optimization suggestions include the use of indexes, optimized queries, and partitioning of tables.

MySQL is an open source relational database management system suitable for data storage, management, query and security. 1. It supports a variety of operating systems and is widely used in Web applications and other fields. 2. Through the client-server architecture and different storage engines, MySQL processes data efficiently. 3. Basic usage includes creating databases and tables, inserting, querying and updating data. 4. Advanced usage involves complex queries and stored procedures. 5. Common errors can be debugged through the EXPLAIN statement. 6. Performance optimization includes the rational use of indexes and optimized query statements.

MySQL is chosen for its performance, reliability, ease of use, and community support. 1.MySQL provides efficient data storage and retrieval functions, supporting multiple data types and advanced query operations. 2. Adopt client-server architecture and multiple storage engines to support transaction and query optimization. 3. Easy to use, supports a variety of operating systems and programming languages. 4. Have strong community support and provide rich resources and solutions.

InnoDB's lock mechanisms include shared locks, exclusive locks, intention locks, record locks, gap locks and next key locks. 1. Shared lock allows transactions to read data without preventing other transactions from reading. 2. Exclusive lock prevents other transactions from reading and modifying data. 3. Intention lock optimizes lock efficiency. 4. Record lock lock index record. 5. Gap lock locks index recording gap. 6. The next key lock is a combination of record lock and gap lock to ensure data consistency.

The main reasons for poor MySQL query performance include not using indexes, wrong execution plan selection by the query optimizer, unreasonable table design, excessive data volume and lock competition. 1. No index causes slow querying, and adding indexes can significantly improve performance. 2. Use the EXPLAIN command to analyze the query plan and find out the optimizer error. 3. Reconstructing the table structure and optimizing JOIN conditions can improve table design problems. 4. When the data volume is large, partitioning and table division strategies are adopted. 5. In a high concurrency environment, optimizing transactions and locking strategies can reduce lock competition.

In database optimization, indexing strategies should be selected according to query requirements: 1. When the query involves multiple columns and the order of conditions is fixed, use composite indexes; 2. When the query involves multiple columns but the order of conditions is not fixed, use multiple single-column indexes. Composite indexes are suitable for optimizing multi-column queries, while single-column indexes are suitable for single-column queries.

To optimize MySQL slow query, slowquerylog and performance_schema need to be used: 1. Enable slowquerylog and set thresholds to record slow query; 2. Use performance_schema to analyze query execution details, find out performance bottlenecks and optimize.

MySQL and SQL are essential skills for developers. 1.MySQL is an open source relational database management system, and SQL is the standard language used to manage and operate databases. 2.MySQL supports multiple storage engines through efficient data storage and retrieval functions, and SQL completes complex data operations through simple statements. 3. Examples of usage include basic queries and advanced queries, such as filtering and sorting by condition. 4. Common errors include syntax errors and performance issues, which can be optimized by checking SQL statements and using EXPLAIN commands. 5. Performance optimization techniques include using indexes, avoiding full table scanning, optimizing JOIN operations and improving code readability.


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