The core of designing a database sharding strategy is "how to reasonably separate the data without affecting use". The key points include: 1. Select the right shard key, and fields such as user ID that are high-base, evenly distributed and commonly used as query conditions should be selected, such as user ID, to avoid using time or high-frequency query fields to prevent hot spots and cross-slicing problems; 2. Control the number of shards, set to 16 or 32 in the initial stage, and reasonably estimate the total data volume and node bearing capacity to avoid operation and maintenance or expansion problems caused by too much or too little; 3. Optimize query and transactions, reduce cross-slicing queries, use redundancy or intermediate layer aggregation to improve efficiency, pay attention to the limited transaction support in the shard environment, and it is necessary to cooperate with cache or secondary index to optimize query performance, report statistics and other operations, and it is recommended to process in parallel at the application layer to reduce database pressure.
The core of designing a database sharding strategy is " how to reasonably separate the data without affecting use ." The key points are: select the right shard key, control the number of shards, consider scalability and query performance.
The most important choice of shard key
The shard key determines how the data is distributed. Once the wrong choice is selected, the later adjustment will be very expensive. Ideally, a field with a high cardinality, uniform distribution, and often used for query conditions should be selected, such as user ID, order number, etc.
- Avoid hot issues : If time is used as the shard key, the new data will be concentrated on one shard, causing uneven load.
- Try to avoid cross-slice queries : If your business often checks users based on mobile phone numbers, then mobile phone numbers are not suitable for sharding keys, unless you have an additional mechanism to handle this situation.
- Common practices: E-commerce systems usually use the user ID as the shard key, so that users' orders, browsing records, etc. can be concentrated in the same shard.
For example:
Suppose you have a social platform where users interact frequently. At this time, using the user ID as the shard key can make most operations complete within the same shard, reducing cross-slice queries and transactions.
The number of shards should be planned in advance
The more shards, the better, nor the fewer the better. General suggestions:
- In the early stage, you can set a moderate number, such as 16 or 32 shards.
- Considering the data growth in the next few years, a certain amount of capacity space is reserved.
- Too many shards will increase the complexity of operation and maintenance, and too few may limit the ability to horizontally scale.
Some common misunderstandings:
- At the beginning, only 2 to 4 shards were used, but the data was stuck as soon as it expanded.
- Blindly setting up hundreds of shards leads to difficulties in connection management and waste of resources.
You can reverse the number of shards in combination with the estimated total data and the carrying capacity of a single node. For example, the total data volume is expected to be 1 billion, and a single node can last 200 million, so at least 5 shards are needed.
Pay special attention to inquiries and transactions
After sharding, it turns out that simple SQL may become complicated. The following points need to be noted:
- Try to avoid cross-sliced ??queries : This type of query is inefficient and complex to implement. It can be optimized by redundant data or by introducing intermediate layer aggregation.
- Transaction support is restricted : Most sharding schemes do not support cross-shash ACID transactions. If the business must be strongly consistent, other options may be considered, such as CQRS or event-driven architecture.
- Indexes and caches should also be coordinated with sharding logic : although some queries are not on the primary table shard key, they can be accelerated through caches or secondary indexes.
Let me give you a small detail:
For example, when you make a report, you need to count the activity of all users. At this time, it is best to initiate multiple parallel queries at the application layer and then merge the results, rather than letting the database help you scan the full table.
Basically that's it. The database sharding strategy does not seem difficult, but many details are easily overlooked when actually implemented, especially changes brought about by business development. As long as you plan well in the early stage, subsequent maintenance will not be too passive.
The above is the detailed content of How to design a database sharding strategy?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

The most direct way to connect to MySQL database is to use the command line client. First enter the mysql-u username -p and enter the password correctly to enter the interactive interface; if you connect to the remote database, you need to add the -h parameter to specify the host address. Secondly, you can directly switch to a specific database or execute SQL files when logging in, such as mysql-u username-p database name or mysql-u username-p database name

Character set and sorting rules issues are common when cross-platform migration or multi-person development, resulting in garbled code or inconsistent query. There are three core solutions: First, check and unify the character set of database, table, and fields to utf8mb4, view through SHOWCREATEDATABASE/TABLE, and modify it with ALTER statement; second, specify the utf8mb4 character set when the client connects, and set it in connection parameters or execute SETNAMES; third, select the sorting rules reasonably, and recommend using utf8mb4_unicode_ci to ensure the accuracy of comparison and sorting, and specify or modify it through ALTER when building the library and table.

MySQL supports transaction processing, and uses the InnoDB storage engine to ensure data consistency and integrity. 1. Transactions are a set of SQL operations, either all succeed or all fail to roll back; 2. ACID attributes include atomicity, consistency, isolation and persistence; 3. The statements that manually control transactions are STARTTRANSACTION, COMMIT and ROLLBACK; 4. The four isolation levels include read not committed, read submitted, repeatable read and serialization; 5. Use transactions correctly to avoid long-term operation, turn off automatic commits, and reasonably handle locks and exceptions. Through these mechanisms, MySQL can achieve high reliability and concurrent control.

The setting of character sets and collation rules in MySQL is crucial, affecting data storage, query efficiency and consistency. First, the character set determines the storable character range, such as utf8mb4 supports Chinese and emojis; the sorting rules control the character comparison method, such as utf8mb4_unicode_ci is case-sensitive, and utf8mb4_bin is binary comparison. Secondly, the character set can be set at multiple levels of server, database, table, and column. It is recommended to use utf8mb4 and utf8mb4_unicode_ci in a unified manner to avoid conflicts. Furthermore, the garbled code problem is often caused by inconsistent character sets of connections, storage or program terminals, and needs to be checked layer by layer and set uniformly. In addition, character sets should be specified when exporting and importing to prevent conversion errors

CTEs are a feature introduced by MySQL8.0 to improve the readability and maintenance of complex queries. 1. CTE is a temporary result set, which is only valid in the current query, has a clear structure, and supports duplicate references; 2. Compared with subqueries, CTE is more readable, reusable and supports recursion; 3. Recursive CTE can process hierarchical data, such as organizational structure, which needs to include initial query and recursion parts; 4. Use suggestions include avoiding abuse, naming specifications, paying attention to performance and debugging methods.

MySQL query performance optimization needs to start from the core points, including rational use of indexes, optimization of SQL statements, table structure design and partitioning strategies, and utilization of cache and monitoring tools. 1. Use indexes reasonably: Create indexes on commonly used query fields, avoid full table scanning, pay attention to the combined index order, do not add indexes in low selective fields, and avoid redundant indexes. 2. Optimize SQL queries: Avoid SELECT*, do not use functions in WHERE, reduce subquery nesting, and optimize paging query methods. 3. Table structure design and partitioning: select paradigm or anti-paradigm according to read and write scenarios, select appropriate field types, clean data regularly, and consider horizontal tables to divide tables or partition by time. 4. Utilize cache and monitoring: Use Redis cache to reduce database pressure and enable slow query

To design a reliable MySQL backup solution, 1. First, clarify RTO and RPO indicators, and determine the backup frequency and method based on the acceptable downtime and data loss range of the business; 2. Adopt a hybrid backup strategy, combining logical backup (such as mysqldump), physical backup (such as PerconaXtraBackup) and binary log (binlog), to achieve rapid recovery and minimum data loss; 3. Test the recovery process regularly to ensure the effectiveness of the backup and be familiar with the recovery operations; 4. Pay attention to storage security, including off-site storage, encryption protection, version retention policy and backup task monitoring.

TooptimizecomplexJOINoperationsinMySQL,followfourkeysteps:1)EnsureproperindexingonbothsidesofJOINcolumns,especiallyusingcompositeindexesformulti-columnjoinsandavoidinglargeVARCHARindexes;2)ReducedataearlybyfilteringwithWHEREclausesandlimitingselected
