The LEAD() function is a MySQL window function, which is used to obtain a certain row of data after the current row, without self-connection. Its syntax is LEAD(expression [, offset] [, default]) OVER ([PARTITION BY partition_expression] ORDER BY sort_expression), where expression is the column to be retrieved, offset is the number of offset rows (default 1), and default is the default value when the boundary is exceeded (default NULL). Application scenarios include: 1. Comparison of data in adjacent time periods, such as monthly month-on-month; 2. Comparison within groups, such as viewing performance by grouping sales personnel. When using it, you need to pay attention to: there must be ORDER BY to ensure the sorting; it is recommended to set the default value clearly; and consider index optimization when large data volumes. Common errors include forgetting ORDER BY, unpartitioned resulting in cross-group acquisition, and unprocessed NULL values. The solutions are to add ORDER BY, use PARTITION BY, set default values, or use IFNULL() to handle.
MySQL's LEAD()
function is a type of window function, which is used to access a certain row of data after the current row. It is useful when dealing with time series, ranking analysis, or comparing adjacent records. If you have used Excel's "Next Line" function before, LEAD()
is a similar function in the SQL world.

What is the LEAD() function?
LEAD()
allows you to get data from one or more rows after the current row without using self-connection. Its basic syntax is as follows:
LEAD(expression [, offset] [, default]) OVER ( [PARTITION BY partition_expression] ORDER BY sort_expression )
-
expression
: The column or expression to be retrieved. -
offset
: The number of rows offset backwards, default is 1. -
default
: If the boundary is exceeded, the default value returned is NULL. -
OVER()
clause defines the sorting and grouping methods.
For example, suppose you have a sales record table and you want to know the comparison of each salesperson's sales this month and the next month, then you can use LEAD()
.

Practical application scenarios
1. Compare data from adjacent time periods (such as monthly month-on-month)
For example, if you have monthly sales records, you want to see if next month is more or less than this month:
SELECT sales_month, amount, LEAD(amount, 1) OVER (ORDER BY sales_month) AS next_month_amount, LEAD(amount, 1) OVER (ORDER BY sales_month) - amount AS diff FROM monthly_sales;
In this way, you can directly see the difference between each month and the next without writing complicated JOINs.

2. Comparison within groups (by personnel, products, etc.)
If you want to group sales people into comparisons of their monthly performance:
SELECT salesperson_id, sales_month, amount, LEAD(amount, 1) OVER (PARTITION BY salesperson_id ORDER BY sales_month) AS next_month_amount FROM sales_records;
PARTITION BY
is used here to ensure that only comparisons are made within the same salesperson and that there is no confusion among people.
Things to note when using
Although LEAD()
is convenient, there are several details that are easy to ignore:
- There must be ORDER BY : Otherwise, it is impossible to determine which line is "next line".
- The default value setting is clear : if not set, the last line will be NULL, which may affect subsequent calculations.
- Performance issues : Using window functions in big data tables may be slower, and it is best to optimize the sorting field with index.
For example, you can add the default value like this:
LEAD(amount, 1, 0) OVER (ORDER BY sales_month)
In this way, the last line will not be NULL, but 0, to avoid null errors.
Common errors and solutions
? Forgot
ORDER BY
, resulting in confusion in the results ? AddORDER BY
to explicit sorting logic? No partition causes cross-group values to be taken? If you need group comparison, remember to use
PARTITION BY
? Not handling NULL causes calculation errors? Set appropriate default values or wrap them with
IFNULL()
Basically that's it. LEAD() looks simple, but it is very useful in actual business. As long as you pay attention to sorting and grouping, you can use it very easily.
The above is the detailed content of mysql lead function. 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)

Hot Topics

GTID (Global Transaction Identifier) ??solves the complexity of replication and failover in MySQL databases by assigning a unique identity to each transaction. 1. It simplifies replication management, automatically handles log files and locations, allowing slave servers to request transactions based on the last executed GTID. 2. Ensure consistency across servers, ensure that each transaction is applied only once on each server, and avoid data inconsistency. 3. Improve troubleshooting efficiency. GTID includes server UUID and serial number, which is convenient for tracking transaction flow and accurately locate problems. These three core advantages make MySQL replication more robust and easy to manage, significantly improving system reliability and data integrity.

MySQL main library failover mainly includes four steps. 1. Fault detection: Regularly check the main library process, connection status and simple query to determine whether it is downtime, set up a retry mechanism to avoid misjudgment, and can use tools such as MHA, Orchestrator or Keepalived to assist in detection; 2. Select the new main library: select the most suitable slave library to replace it according to the data synchronization progress (Seconds_Behind_Master), binlog data integrity, network delay and load conditions, and perform data compensation or manual intervention if necessary; 3. Switch topology: Point other slave libraries to the new master library, execute RESETMASTER or enable GTID, update the VIP, DNS or proxy configuration to

The steps to connect to the MySQL database are as follows: 1. Use the basic command format mysql-u username-p-h host address to connect, enter the username and password to log in; 2. If you need to directly enter the specified database, you can add the database name after the command, such as mysql-uroot-pmyproject; 3. If the port is not the default 3306, you need to add the -P parameter to specify the port number, such as mysql-uroot-p-h192.168.1.100-P3307; In addition, if you encounter a password error, you can re-enter it. If the connection fails, check the network, firewall or permission settings. If the client is missing, you can install mysql-client on Linux through the package manager. Master these commands

InnoDB is MySQL's default storage engine because it outperforms other engines such as MyISAM in terms of reliability, concurrency performance and crash recovery. 1. It supports transaction processing, follows ACID principles, ensures data integrity, and is suitable for key data scenarios such as financial records or user accounts; 2. It adopts row-level locks instead of table-level locks to improve performance and throughput in high concurrent write environments; 3. It has a crash recovery mechanism and automatic repair function, and supports foreign key constraints to ensure data consistency and reference integrity, and prevent isolated records and data inconsistencies.

IndexesinMySQLimprovequeryspeedbyenablingfasterdataretrieval.1.Theyreducedatascanned,allowingMySQLtoquicklylocaterelevantrowsinWHEREorORDERBYclauses,especiallyimportantforlargeorfrequentlyqueriedtables.2.Theyspeedupjoinsandsorting,makingJOINoperation

MySQL's default transaction isolation level is RepeatableRead, which prevents dirty reads and non-repeatable reads through MVCC and gap locks, and avoids phantom reading in most cases; other major levels include read uncommitted (ReadUncommitted), allowing dirty reads but the fastest performance, 1. Read Committed (ReadCommitted) ensures that the submitted data is read but may encounter non-repeatable reads and phantom readings, 2. RepeatableRead default level ensures that multiple reads within the transaction are consistent, 3. Serialization (Serializable) the highest level, prevents other transactions from modifying data through locks, ensuring data integrity but sacrificing performance;

MySQL transactions follow ACID characteristics to ensure the reliability and consistency of database transactions. First, atomicity ensures that transactions are executed as an indivisible whole, either all succeed or all fail to roll back. For example, withdrawals and deposits must be completed or not occur at the same time in the transfer operation; second, consistency ensures that transactions transition the database from one valid state to another, and maintains the correct data logic through mechanisms such as constraints and triggers; third, isolation controls the visibility of multiple transactions when concurrent execution, prevents dirty reading, non-repeatable reading and fantasy reading. MySQL supports ReadUncommitted and ReadCommi.

To add MySQL's bin directory to the system PATH, it needs to be configured according to the different operating systems. 1. Windows system: Find the bin folder in the MySQL installation directory (the default path is usually C:\ProgramFiles\MySQL\MySQLServerX.X\bin), right-click "This Computer" → "Properties" → "Advanced System Settings" → "Environment Variables", select Path in "System Variables" and edit it, add the MySQLbin path, save it and restart the command prompt and enter mysql--version verification; 2.macOS and Linux systems: Bash users edit ~/.bashrc or ~/.bash_
