If records are inserted in a random order, the pages are from 1/2 to 15/16 full. If index records are inserted in a sequential order (ascending or descending), the resulting index pages are about 15/16 full. When new records are inserted into an InnoDB clustered index, InnoDB tries to leave 1/16 of the page free for future insertions and updates of the index records. Random primary keys can also lead to a page low filling factor. This operation is costly in terms of performance as it requires many disk I/O operations to read and write data. thus it needs to be divided into two or more smaller pages. A page split occurs when an InnoDB page becomes full and cannot accommodate the new data. But, when the primary key is random, it is unlikely for a page to become frequently accessed thus each insert will mostly require an extra disk I/O.Īdditionally, inserting rows with random primary keys can cause more page splits. This can result in performance gains in terms of latency and throughput. Normally when a page is frequently accessed and modified it becomes a hot page, and the buffer pool gives it a higher priority to stay in memory as long as possible. If the page is not in the buffer pool, InnoDB reads the page from the disk.Īt some point, the page will be flushed back to the disk. When a new row with a random UUID needs to be inserted, InnoDB needs to:Ĭhecks whether the page is already in the buffer pool In other words, when a table has a clustered index, the data is physically stored on disk in the same order as the index. InnoDB by default creates a b-tree for the table’s primary key and stores the rows data in the leaf nodes of the same b-tree which is called a clustered index. The negative impact of using UUID as the primary key comes from how MySQL’s default engine, InnoDB, stores the data. The 128-bit value of a UUID is usually represented as a string of 36 characters, consisting of 32 hexadecimal digits separated by hyphens in the form of 8-4-4-4-12. UUID consists of two parts: a time-based component and a random component, and there are officially 5 versions of UUID, each with a different algorithm for generating the random and time-based components. UUID stands for Universally Unique Identifier, which is a standard for generating unique identifiers that are widely used in computer systems and software applications. They can be generated by the application without a centralized authority.Īnd since they are pseudo-random, they can be sent safely to the client side.īut as with any tech or tool, some tradeoffs come with using a unique identifier. Unique identifiers have a low probability of collision even across tables and databases. But, using unique identifiers instead of auto-incremented integers can have some benefits: Using integers for tables’ primary key is the go-to approach when working with MySQL and other RDBMS. Unique identifiers are often implemented using a numerical or alphanumeric string that is assigned to an object when it is created and they have many types like UUID, ULID, Snowflake ID, GUID and more. They are commonly used to identify entities such as users, files, processes, network devices, and other objects. Unique identifiers are used to distinguish one object from another.
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