Designing 1 applications doesn't seem to be difficult, but it's not easy to achieve the optimal performance of the system. There are many choices in development tools, database design, application structure, query design, interface selection, and so on, depending on the specific application requirements and the skills of the development team. This article takes SQL Server as an example, discusses the application performance optimization techniques from the perspective of the background database, and gives some useful suggestions. 1 database design to achieve optimal performance in a good SQL Server scenario, the key is to have 1 ...
We want to do not only write SQL, but also to do a good performance of the SQL, the following for the author to learn, extract, and summarized part of the information to share with you! (1) Select the most efficient table name order (valid only in the Rule-based optimizer): The ORACLE parser processes the table names in the FROM clause in Right-to-left order, and the last table in the FROM clause (the underlying table driving tables) is processed first, In the case where multiple tables are included in the FROM clause, you must select the table with the least number of records as the underlying table. If...
To select the data that matches the specified criteria, add the WHERE clause to the SELECT statement. WHERE clause To select the data that match the specified criteria, add a WHERE clause to the SELECT statement. Syntax SELECT column FROM table WHERE column operator value The following operators can be used with the WHERE clause: Operator Description = Equal! = Not equal> Greater than <...
MySQL database sql statement commonly used optimization methods 1. Query optimization, should try to avoid full table scan, should first consider where and order by the columns involved in the establishment of the index. 2. Should be avoided in the where clause on the field null value judgment, otherwise it will cause the engine to abandon the use of indexes and full table scan, such as: select id from t where num is null You can set the default value of num 0, to ensure that Num column table does not null value ...
SQL statement for querying and deleting duplicate records (i) For example, there is a field "name" in Table A, and the "name" value may be the same between different records, and now you need to query between the records in the table, the "name" value has duplicates, and select name, Count (*) from-a group by name has count (*) > 1 as ...
A few suggestions to improve SQL execution efficiency: Try not to include subqueries in where; queries about time, try not to write: where To_char (dif_date, ' yyyy ') =to_char (' 2007-07-01 ', ' yyyy '); In the filter condition, the condition in which the maximum number of records can be filtered must be placed at the end of the WHERE clause, and the last table (underlying table, driving table) in the FROM clause will be first ...
This article describes the SQL name for filtering duplicate records using a having group by and various select in federated queries to implement a variety of different methods. -1, find redundant records in the table, duplicate records are based on a single field (Peopleid) to determine the code as follows select * from arranges where Peopleid in (select Peopleid from&n ...
Hive in the official document of the query language has a very detailed description, please refer to: http://wiki.apache.org/hadoop/Hive/LanguageManual, most of the content of this article is translated from this page, Some of the things that need to be noted during the use process are added. Create tablecreate [EXTERNAL] TABLE [IF not EXISTS] table_name [col_name data_t ...
1, use the index to traverse the table faster. The index created by default is a non-clustered index, but sometimes it is not optimal. Under non-clustered indexes, the data is physically stored on the data page. Reasonable index design should be based on the analysis and prediction of various inquiries. In general: a. There are a large number of duplicate values, and often range query (>, <,> =, <=) and order by, group by occurred columns, consider the establishment of cluster index; Column, and each column contains duplicate values can be ...
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