A more efficient solution for SQL Server paging: Keyset paging
In SQL Server, paging is usually implemented using OFFSET, but for large tables, Keyset paging is a more efficient method. Unlike rowset pagination, which requires reading all previous rows to reach the desired page, Keyset pagination jumps directly to the correct location in the index, significantly improving performance.
Implementing Keyset paging requires building a unique index on the required key. The key can contain additional columns required by the query. It should be noted that this method cannot directly jump to a specific page number. Instead, you need to locate a specific key first and then move on from there.
One advantage of Keyset paging is that it avoids the "lost row" problem caused by deleting rows in rowset paging. Since paging is based on keys, changes in the order of rows will not affect the paging logic.
The following is an example of using Keyset pagination in SQL Server:
SELECT TOP (@numRows) * FROM TableName ORDER BY Id DESC;
This query retrieves the first page of data in descending order by the Id column. To paginate further, you can use the last received Id value like this:
SELECT TOP (@numRows) * FROM TableName WHERE Id < @lastId ORDER BY Id DESC;
To support paging by non-unique columns, additional columns must be included in both the ORDER BY
and WHERE
clauses. Appropriate indexes need to be built on selected columns to ensure efficient execution.
Keyset paging provides a more efficient alternative to OFFSET paging for large data sets in SQL Server. It avoids unnecessary row reads and ensures consistent paginated results even when data is modified.
The above is the detailed content of Keyset Pagination vs. OFFSET in SQL Server: A More Efficient Approach?. For more information, please follow other related articles on the PHP Chinese website!

MySQL'sBLOBissuitableforstoringbinarydatawithinarelationaldatabase,whileNoSQLoptionslikeMongoDB,Redis,andCassandraofferflexible,scalablesolutionsforunstructureddata.BLOBissimplerbutcanslowdownperformancewithlargedata;NoSQLprovidesbetterscalabilityand

ToaddauserinMySQL,use:CREATEUSER'username'@'host'IDENTIFIEDBY'password';Here'showtodoitsecurely:1)Choosethehostcarefullytocontrolaccess.2)SetresourcelimitswithoptionslikeMAX_QUERIES_PER_HOUR.3)Usestrong,uniquepasswords.4)EnforceSSL/TLSconnectionswith

ToavoidcommonmistakeswithstringdatatypesinMySQL,understandstringtypenuances,choosetherighttype,andmanageencodingandcollationsettingseffectively.1)UseCHARforfixed-lengthstrings,VARCHARforvariable-length,andTEXT/BLOBforlargerdata.2)Setcorrectcharacters

MySQloffersechar, Varchar, text, Anddenumforstringdata.usecharforfixed-Lengthstrings, VarcharerForvariable-Length, text forlarger text, AndenumforenforcingdataAntegritywithaetofvalues.

Optimizing MySQLBLOB requests can be done through the following strategies: 1. Reduce the frequency of BLOB query, use independent requests or delay loading; 2. Select the appropriate BLOB type (such as TINYBLOB); 3. Separate the BLOB data into separate tables; 4. Compress the BLOB data at the application layer; 5. Index the BLOB metadata. These methods can effectively improve performance by combining monitoring, caching and data sharding in actual applications.

Mastering the method of adding MySQL users is crucial for database administrators and developers because it ensures the security and access control of the database. 1) Create a new user using the CREATEUSER command, 2) Assign permissions through the GRANT command, 3) Use FLUSHPRIVILEGES to ensure permissions take effect, 4) Regularly audit and clean user accounts to maintain performance and security.

ChooseCHARforfixed-lengthdata,VARCHARforvariable-lengthdata,andTEXTforlargetextfields.1)CHARisefficientforconsistent-lengthdatalikecodes.2)VARCHARsuitsvariable-lengthdatalikenames,balancingflexibilityandperformance.3)TEXTisidealforlargetextslikeartic

Best practices for handling string data types and indexes in MySQL include: 1) Selecting the appropriate string type, such as CHAR for fixed length, VARCHAR for variable length, and TEXT for large text; 2) Be cautious in indexing, avoid over-indexing, and create indexes for common queries; 3) Use prefix indexes and full-text indexes to optimize long string searches; 4) Regularly monitor and optimize indexes to keep indexes small and efficient. Through these methods, we can balance read and write performance and improve database efficiency.


Hot AI Tools

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

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

Undress AI Tool
Undress images for free

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

Dreamweaver Mac version
Visual web development tools

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

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.
