SQL. UPDATE command syntax. SQL(DML) Help: UPDATE and DELETE Statements DML: Join Operation

This SQL tutorial explains how to use the SQL UPDATE statement with syntax, examples and practice exercises.

Syntax

The syntax for the UPDATE statement when updating a table in SQL is:

UPDATE table SET column1 = expression1, column2 = expression2, ... ;

The syntax for the SQL UPDATE statement when updating a table with data from another table is:

UPDATE table1 SET column1 = (SELECT expression1 FROM table2 WHERE conditions) ;

The syntax for the SQL UPDATE statement when updating multiple tables (not permitted in Oracle) is:

UPDATE table1, table2, ... SET column1 = expression1, column2 = expression2, ... WHERE table1.column = table2.column ;

Parameters or Arguments

, and so on.

WHERE conditions Optional. The conditions that must be met for the update to execute. If no conditions are provided, then all records in the table will be updated.

DDL/DML for Examples

If you want to follow along with this tutorial, get the DDL to create the tables and the DML to populate the data. Then try the examples in your own database!

Example - Update single column Let's look at an example showing how to use the SQL UPDATE statement to update a single column in a table.

Johnson Example - Update single column

Example - Update single column Now let"s demonstrate how the UPDATE statement works by updating one column in the

Try It UPDATE customers SET first_name = "Judy" WHERE customer_id = 8000;

SELECT * FROM customers; customer_id Judy Example - Update single column In this UPDATE example, the customers field is set to "Judy" in the

table where the

is equal to 8000.

Example - Update multiple columns Let's look at an UPDATE example that shows how to update more than one column in a table.

TIP: When you update multiple columns in an UPDATE statement, you need to comma separate the column/value pairs in the SET clause. Let's look at an example showing how to use the SQL UPDATE statement to update a single column in a table.

Now let"s demonstrate how to use the UPDATE statement to update more than one column value at once. Enter the following UPDATE statement:

There will be 1 record updated. Select the data from the When you update multiple columns in an UPDATE statement, you need to comma separate the column/value pairs in the SET clause. Now let"s demonstrate how the UPDATE statement works by updating one column in the

SELECT * FROM suppliers;

These are the results that you should see:

This UPDATE example would update the In this UPDATE example, we have a table called to 150, the suppliers to "Apple" and supplier_id to "Cupertino" where the suppliers is "Google".

Example - Update table with data from another table

Let's look at an UPDATE example that shows how to update a table with data from another table.

TIP: products Let's look at an example showing how to use the SQL UPDATE statement to update a single column in a table.

And a table called summary_data Let's look at an example showing how to use the SQL UPDATE statement to update a single column in a table.

Now let's update the summary_data table with values ​​from the products table. Enter the following UPDATE statement:

UPDATE summary_data SET current_category = (SELECT category_id FROM products WHERE products.product_id = summary_data.product_id) WHERE EXISTS (SELECT category_id FROM products WHERE products.product_id = summary_data.product_id);

There will be 5 records update. Select the data from the summary_data Now let"s demonstrate how the UPDATE statement works by updating one column in the

SELECT * FROM summary_data;

These are the results that you should see:

This example would update the current_category field in the summary_data table with the category_id from the products In this UPDATE example, the product_id values ​​match. The first 5 records in the summary_data table has been updated.

Example - Update multiple columns Notice that our UPDATE statement included an EXISTS condition in the WHERE clause to make sure that there was a matching product_id in both the products and summary_data table before updating the record.

If we hadn't included the EXISTS condition, the UPDATE query would have updated the current_category field to NULL in the 6th row of the summary_data table (because the products table does not have a record where product_id=8).

Practice Exercises

If you want to test your skills using the SQL UPDATE statement, try some of our practice exercises.

These exercises allow you to try out your skills with the UPDATE statement. You will be given questions that you need to solve. After each exercise, we provide the solution so you can check your answer. Give it a try!

UPDATE command— makes changes to an existing record or multiple records in a table SQL. Modifies existing values ​​in a table or the view's main table.

UPDATE Command Command Syntax

UPDATE Command Syntax

UPDATE command. Basic keywords and parameters of the UPDATE command

• schema - a permission identifier, usually the same as some username
• table view - table name SQL, in which the data is changed; if a view is defined, the data is modified in the main table SQL representation
• subquery_1 - subquery, which the server treats in the same way as a view
• Witholumn - table column SQL or submissions SQL, whose value changes; if the table column is from a sentence SET is omitted, the column value remains unchanged
• expr - ; this expression may contain main variables and optional indicator variables
• subquery_2 - new value assigned to the corresponding column
• subquery_3 - new value assigned to the corresponding column

WHERE- defines the range of rows to be modified by those for which a certain condition is TRUE; if this phrase is omitted, all rows in the table or view are modified.
When an approval is issued, any UPDATE trigger, defined on the table.
Subqueries. If the offer SET contains subquery, it returns exactly one row for each row modified. Each value in the subquery result is assigned to the corresponding list columns in parentheses. If the subquery does not return any rows, the column is assigned Anderson. Subqueries can select data from the modified table. Offer SET can combine expressions and subqueries.

UPDATE Command Example 1
Changing the rating for all buyers to a value equal to 200:

Customers SET rating = 200;

UPDATE Command Example 2
Replacing a column value across all rows of a table is generally rarely used. Therefore in the team, as in the team DELETE, you can use a predicate. To perform the specified replacement of the values ​​of the rating column, for all customers who are served by the seller Giovanni (snum = 1003), you should enter:

Customers SET rating = 200 WHERE snum = 1001;

SQL UPDATE Command Example 3
In a sentence SET You can specify any number of values ​​for the columns, separated by commas:

Emp SET job = 'MANAGER', sal = sal + 1000, deptno = 20 WHERE ename = 'JONES';

UPDATE Command Example 4
In a sentence SET you can specify a NULL value without using any special syntax (such as IS NULL). Thus, if you want to set all customer ratings from London (city = 'London') to NULL, you would enter:

Customers SET rating = NULL WHERE city = 'London';

UPDATE Command Example 5
Explains the use of the following command syntax:

• Both sentence forms SET together in one statement.
• Subquery.
• A WHERE clause that limits the range of rows that can be modified.

Emp a SET deptno =
(SELECT deptno FROM dept WHERE loc = 'BOSTON'), (sal, comm) = ( SELECT 1.1*AVG(sal), 1.5*AVG(comm) FROM emp b WHERE a.deptno = b.deptno) WHERE deptno IN ( SELECT deptno FROM dept WHERE loc = 'DALLAS' OR loc = 'DETROIT');

The above statement does the following:

• Modifies only those employees who work in Dallas or Detroit
• Sets the value of the deptno column for employees from Boston
• Sets the salary of each employee at 1.1 times the average salary of the entire department
• Sets each employee's commission at 1.5 times the average commission for the entire department

UPDATE command— makes changes to an existing record or multiple records in a table SQL. Modifies existing values ​​in a table or the view's main table.

UPDATE Command Command Syntax

UPDATE Command Syntax

UPDATE command. Basic keywords and parameters of the UPDATE command

• schema - a permission identifier, usually the same as some username
• table view - table name SQL, in which the data is changed; if a view is defined, the data is modified in the main table SQL representation
• subquery_1 - subquery, which the server treats in the same way as a view
• Witholumn - table column SQL or submissions SQL, whose value changes; if the table column is from a sentence SET is omitted, the column value remains unchanged
• expr - ; this expression may contain main variables and optional indicator variables
• subquery_2 - new value assigned to the corresponding column
• subquery_3 - new value assigned to the corresponding column

WHERE- defines the range of rows to be modified by those for which a certain condition is TRUE; if this phrase is omitted, all rows in the table or view are modified.
When issuing approval UPDATE any one turns on UPDATE trigger, defined on the table.
Subqueries. If the offer SET contains subquery, it returns exactly one row for each row modified. Each value in the subquery result is assigned to the corresponding list columns in parentheses. If the subquery does not return any rows, the column is assigned Anderson. Subqueries can select data from the modified table. Offer SET can combine expressions and subqueries.

UPDATE Command Example 1
Changing the rating for all buyers to a value equal to 200:

UPDATE Customers SET rating = 200;

UPDATE Command Example 2
Replacing a column value across all rows of a table is generally rarely used. Therefore on the team UPDATE, as in the team DELETE, you can use a predicate. To perform the specified replacement of the values ​​of the rating column, for all customers who are served by the seller Giovanni (snum = 1003), you should enter:

UPDATE Customers SET rating = 200 WHERE snum = 1001;

SQL UPDATE Command Example 3
In a sentence SET You can specify any number of values ​​for the columns, separated by commas:

UPDATE emp SET job = 'MANAGER', sal = sal + 1000, deptno = 20 WHERE ename = 'JONES';

UPDATE Command Example 4
In a sentence SET you can specify a NULL value without using any special syntax (such as IS NULL). Thus, if you want to set all customer ratings from London (city = 'London') to NULL, you would enter:

UPDATE Customers SET rating = NULL WHERE city = 'London';

UPDATE Command Example 5
Explains the use of the following command syntax UPDATE:

• Both sentence forms SET together in one statement.
• Subquery.
• A WHERE clause that limits the range of rows that can be modified.

UPDATE emp a SET deptno =
(SELECT deptno FROM dept WHERE loc = 'BOSTON'), (sal, comm) = ( SELECT 1.1*AVG(sal), 1.5*AVG(comm) FROM emp b WHERE a.deptno = b.deptno) WHERE deptno IN ( SELECT deptno FROM dept WHERE loc = 'DALLAS' OR loc = 'DETROIT');

The above statement UPDATE performs the following operations:

• Modifies only those employees who work in Dallas or Detroit
• Sets the value of the deptno column for employees from Boston
• Sets the salary of each employee at 1.1 times the average salary of the entire department
• Sets each employee's commission at 1.5 times the average commission for the entire department

Data manipulation operators (DML language).

DML statements operate on the database and are used to modify data and retrieve required information.

SELECT – selecting rows that satisfy given conditions. The operator implements, in particular, such operations of relational algebra as “selection” and “projection”.

UPDATE – changing the values ​​of certain fields in table rows that meet specified conditions.

INSERT – inserts new rows into the table.

DELETE – deleting table rows that meet specified conditions. The example of this operator takes into account integrity principles, so it may not always be executed correctly.

12.2 Interactive mode of working with SQL (interactive SQL)

The corresponding mode provides for direct user work with the database according to the following algorithm: using an application program (client application) or a standard utility included in the DBMS, the user:

· establishes a connection to the database (confirming the availability of access rights);

· enters the appropriate SQL statement, if necessary, enters additional information in dialog mode;

· initiates command execution.

The request text is sent to the DBMS, which:

· parses the request (checks whether the request is correct);

· checks whether the user has the right to perform such a request (for example, a user who has read-only rights is trying to delete something);

· chooses how to execute the request – the request execution plan;

· executes the request;

· the execution result is sent to the user.

Scheme of interaction between the user and the DBMS using interactive SQL

is shown in Fig. 12.1.

Rice. 12.1. How interactive SQL works

12.3. Using SQL to select information from a table

Data is retrieved using the SELECT statement, which is the most commonly used statement in the SQL language. The syntax of the SELECT statement is as follows:

SELECT<список атрибутов>/*

FROM<список таблиц>

Square brackets indicate elements that may not be present in the request.

The ALL keyword means that the result will be all rows that satisfy the query condition, including identical rows.

DISTINCT means that no duplicate rows are included in the result set. Next is a list of attributes of the source table that will be included in the result table. The * symbol means that the resulting table includes all the attributes of the source table.

The required keyword is FROM, followed by the names of the tables being queried.

The clause with the WHERE keyword specifies the conditions for selecting table rows. The result table includes only those rows for which the condition specified in the WHERE clause evaluates to true.

The ORDER BY keyword specifies the operation of ordering the rows of the result table according to the specified list of attributes.

The GROUP BY keyword clause specifies a list of grouping attributes (this and the following keyword will be explained a little later).

The HAVING clause specifies the conditions to be applied to each group.

Separately, we note that the keywords FROM, WHERE ORDER BY are used in a similar way in other SQL data manipulation operators.

Let's look at the implementation of queries for the specific example presented in Lecture 8 (see Fig.

SQL - UPDATE Query

List all students.

SELECT id_st, surname

Note that if you add the ORDER BY surname clause to this query, the list will be ordered by surname. By default, sorting is assumed to be in ascending order. If descending ordering is desired, the word DESC is added after the attribute name.

Display a list of grades that the student received with code “1”.

SELECT id_st, mark

Provide a list of codes for students who received at least one D or C in the exams.

In the WHERE clause, you can write an expression using arithmetic operators comparisons (<, >, etc.) and logical operators (AND, OR, NOT) as in conventional programming languages.

SELECT id_st, mark

WHERE (MARK >= 2) AND (MARK<= 3)

Along with comparison operators and logical operators for creating conditions in the SQL language (due to the specific scope of application), there are a number of special operators that, as a rule, have no analogues in other languages. These are the operators:

IN – entry into a certain set of values;

BETWEEN – entry into a certain range of values;

LIKE – pattern matching test;

IS NULL – check for an undefined value.

The IN operator is used to check whether a value is included in a set. Yes, request

SELECT id_st, mark

WHERE mark IN (2,3)

gives the same result as the above query (it will display the identifiers of all applicants who received at least one D or C in the exams).

The same result can be achieved using the BETWEEN operator:

SELECT id_st, mark

WHERE mark BETWEEN 2 AND 3

Print a list of all students whose last names begin with the letter A.

In this case, it is convenient to use the LIKE operator.

The LIKE operator applies exclusively to character fields and allows you to determine whether a field's value matches a pattern. The pattern may contain special characters:

_ (underscore) – replaces any single character;

% (percent sign) – replaces a sequence of any number of characters.

SELECT id_st, surname

WHERE surname LIKE ‘A%’

Very often there is a need to calculate the minimum, maximum or average values ​​in columns. For example, you may need to calculate your GPA. To perform such calculations, SQL provides special aggregate functions:

MIN – minimum value in the column;

MAX – maximum value in the column;

SUM – the sum of the values ​​in the column;

AVG – average value in the column;

COUNT – the number of non-NULL values ​​in the column.

The following query calculates the average of all scores obtained by students in exams.

SELECT AVG(mark)

Naturally, you can use aggregate functions in conjunction with a WHERE clause:

SELECT AVG(mark)

WHERE id_st = 100

This query will calculate the average score of a student with a code of 100 based on the results of all exams he has taken.

SELECT AVG(mark)

WHERE id_ex = 10

This query will calculate the average score of students based on the results of passing the exam with code 10.

In addition to the mechanisms discussed above, the SQL language provides a powerful apparatus for calculating aggregate functions not for the entire table of query results, but for different values ​​by group. For this purpose, SQL has a special GROUP BY construct, designed to indicate the column whose values ​​will be used for grouping. So, for example, we can calculate the average score across all exams for each student. To do this, just run the following query:

SELECT id_st, AVG(mark)

All of this, as usual, can be combined with a WHERE clause. At the same time, without going into the intricacies of query execution inside the DBMS, we can assume that first those rows of the table that satisfy the conditions from the WHERE clause are selected, and then grouping and aggregation are performed.

Here is a query that calculates the average score based on grades obtained in an exam coded 100 for each student.

SELECT id_st, AVG(mark)

WHERE id_ex = 100

Note that grouping can be done by more than one field.

For queries containing a GROUP BY clause, there is an important limitation: such queries can include as results the columns by which the grouping is performed, and the columns that contain the actual aggregation results.

There are various SQL capabilities to format the output. For example, it is acceptable to include text in a request. Let's look at an example of how this is done:

SELECT ‘Average score=’, AVG(mark)

WHERE id_ex = 10

As a result of this request, the user will see not just a certain number, but a number accompanied by explanatory text.

12.4. Using SQL to Select Information from Multiple Tables

So far we've looked at selecting information from a single table. You can query information from several tables by implementing the relational operations described in the corresponding section of the textbook. It is worth mentioning that a full discussion of the topic is beyond the scope of this textbook. This issue can be studied in detail using, for example, . Let's look at some examples of how this is done.

As a rule, in cases where there is a need to select information from different tables, they are related to each other in one way or another, for example, by a one-to-many or one-to-one relationship for a certain field.

Let's return once again to the example from lecture 8. Consider the corresponding ER diagram (Fig. 12.2.).

Rice. 12.2. Example of linked tables

This example also contains related tables. Let's look at the tables student, mark_st and exam_st.

The mark_st table is linked to the exam_st table by the id_ex field.

The mark_st table is linked to the student table by the id_st field.

Let's say you want to print a list of students with the grades they received in exams. To do this you need to run the following query:

SELECT student.surname, mark_st.id_ex, mark_st.mark

FROM student, mark_st

WHERE student.id_st = mark_st.id_st

Note the following changes compared to queries against a single table.

1. The FROM section contains two tables.

2. Since there was more than one table, there was some ambiguity when mentioning fields. So, in many cases it is not known which table from the FROM list to take a field from. To eliminate ambiguity, field names are specified with a prefix - the table name. The table name is separated from the field name by a dot.

3. The WHERE clause specifies the condition for joining the tables.

It is easy to see that the use of table name prefixes greatly clutters the query. To avoid such clutter, pseudonyms are used. So, you can rewrite the previous query as follows:

SELECT E.surname, M.id_ex, M.mark

FROM student E, mark_st M

WHERE E.id_st = M.id_st

12.5. Using SQL to insert, edit, and delete data
in tables

To add data to a table, the SQL standard provides the INSERT command.

Let's look at a number of example queries.

INSERT INTO mark_st

VALUES (1, 2, 5)

This query inserts a row into the mark_st table containing the values ​​listed in the VALUES list. If you do not need to specify the value of a field, you can assign it NULL:

INSERT INTO mark

VALUES (1, 2, NULL)

If you need to use default values ​​for some fields, SQL allows you to explicitly specify which fields need to be filled with specific data and which with default values:

INSERT INTO mark_st (id_st, id_ex)

To delete data from a table, there is the DELETE command:

This query deletes all data from the student table.

You can limit the range of information deleted as follows:

WHERE surname > ‘AND’

The UPDATE command is used to update data.

SET mark = '5'

WHERE id_st = 100 AND id_ex = 10

Using this request, the student’s grade with code 100 on the exam with code 10 will change to “5”.

12.5. SQL language and relational algebra operations

The SQL language is a means of expressing the powerful mathematics of set theory and relational algebra. This section examines the relationship between SQL statements and the operations of relational algebra and set theory.

Union operation

Using the SQL language, a join operation is represented as follows:

Difference operation

Using the SQL language, the difference operation is represented as follows:

Projection operation

SELECT Field i1, …, Field in

Selection operation

WHERE ( )

Intersection operation

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4.6.5.DML: Data modification commands.

This group includes operators for adding, changing and deleting records. INSERT INTO<имя_таблицы> [ (<имя_столбца>,<имя_столбца>,…) ] VALUES (<значение>,<значение>,..) The list of columns in this command is not a required parameter. In this case, the values ​​for all table fields must be specified in the order that the columns were listed in the command, for example: Example specifying a list of columns: UPDATE<имя_таблицы>SET<имя_столбца>=<значение>,… If a keyword and condition are specified, the command is applied only to those records for which it is executed. If the condition is not specified, it applies to all records. Example: Logical expressions over constants and fields are used as conditions. The conditions allow:

• comparison operations: . In SQL, these operations can be applied not only to numeric values, but also to strings (meaning earlier and later in alphabetical order) and dates (earlier and later in chronological order).
• operations for checking a field for a value:
• operations of checking for inclusion in a range: and.
• list checking operations: and
• operations of checking for the occurrence of a substring: and
• individual operations are connected by links and grouped using parentheses.

All these keywords will be described and illustrated in detail in the paragraph dedicated to the operator. Here we will limit ourselves to giving a simple example: This command finds in the table publishers all undefined column values url and replaces them with the line “url not defined”. DELETE FROM<имя_таблицы>[WHERE<условие> ] All records that meet the specified condition are deleted. If the keyword and condition are missing, all records are removed from the table. Example: This command deletes the Super Computer Publishing record.

4.6.6.DML: Data sampling.

To retrieve records from tables, SQL defines the operator SELECT. Using this command, not only the relational algebra operation “selection” (horizontal subset) is performed, but also a preliminary join of two or more tables. This is the most sophisticated and powerful SQL tool, full statement syntax SELECT has the form: SELECT<список_выбора>FROM<имя_таблицы>, …[ WHERE<условие>] [ GROUP BY<имя_столбца>,…] [HAVING<условие> ] ,… ] Order of clauses in a statement SELECT must be strictly followed (e.g. must always be preceded) otherwise it will introduce errors.

We will start reviewing SELECT from its simplest forms. All of the examples below regarding the publications database can be performed independently by going to this page, so the results of the queries are not shown here.

This statement always begins with a keyword. The construct specifies the column or columns to be included in the result. It can consist of the names of one or more columns, or a single character (asterisk) that identifies all columns. List elements are separated by commas.

get a list of all table fields authors: In the case when we are not interested in all records, but only those that satisfy a certain condition, this condition can be specified after the keyword.

For example, let's find all books published after 1996: Let's now say that we need to find all publications for the interval 1995 - 1997. This condition can be written as: Another version of this command can be obtained using logical operation checks for inclusion in the interval: When using the construct, all lines that are not included in the specified range are found.

Another version of this command can be constructed using the logical operation of checking for inclusion in a list:

Here we have explicitly specified a list of values ​​that interest us. The construction allows you to find lines that do not satisfy the conditions listed in the list.

The benefits of a keyword are most evident in nested queries, also called subqueries. Let's say we need to find all publications published by Oracle Press. The names of publishing companies are contained in the table publishers, book titles in the table titles. The keyword allows you to join both tables (without obtaining a common relation) and extract the necessary information:

When executing this command, the DBMS first processes a nested query on the table publishers, and then its result is passed to the input of the main query on the table titles.

Some problems cannot be solved using comparison operators alone. For example, we want to find the website of the Wiley publishing house, but we don’t know its exact name. A keyword is intended to solve this problem; its syntax is:

The pattern is enclosed in quotation marks and must contain the substring pattern to be searched. Typically two characters are used in patterns:

• % (percent sign) - replaces any number of characters
• _ (underscore) - replaces a single character.

Let's try to find the desired website: In accordance with the template, the DBMS will find all lines that include the substring “Wiley”. Another example: find all books whose titles begin with the word “SQL”: In the case when you need to find a value that itself contains one of the pattern characters, use the keyword and<ключевой_символ>. The literal following the key character in the pattern is treated as a regular character; all subsequent characters have a regular meaning. For example, we need to find a link to a web page that is known to contain the substring “my_works” in its url: In conclusion, note that when the operator is executed, the resulting relation can have several records with the same values ​​for all fields. To exclude duplicate records from the selection, a keyword is used. The keyword specifies that all rows should be included in the result.

4.6.7.DML: Selecting from multiple tables.

Very often a situation arises when data must be sampled from a relation that is the result of a join of two other relations. For example, we need to get from the database publications information about all printed publications in the form of the following table: For this, the DBMS must first merge the tables titles And publishers, and only then make a sample from the resulting relationship.

To perform an operation of this kind, the operator after the keyword specifies a list of tables through which the data will be searched. After the keyword, the condition under which the merge is performed is indicated. In order to fulfill this request, you need to give the command:

And here is an example where the conditions for both merging and selection are specified simultaneously (the result of the previous query is limited to publications after 1996): Please note that when different tables contain fields of the same name, then to eliminate ambiguity, the table name is indicated before the field name and sign "." (dot). (A good rule of thumb is to always include the table name!)

Naturally, it is possible to merge more than two tables. For example, to supplement the selection described above with the names of book authors, you need to create an operator of the following form:

4.6.8.DML: Calculations inside SELECT.

allows you to perform various arithmetic operations on the columns of the resulting relation. In design<список_выбора>You can use constants, functions and their combinations with arithmetic operations and parentheses. For example, to find out how many years have passed since 1992 (the year the SQL-92 standard was adopted) until the publication of a particular book, you can run the command: In arithmetic equations, the operations allowed are addition (+), subtraction (-), division (/), multiplication ( *), and various functions(COS, SIN, ABS - absolute value, etc.).

You can also add a string constant to the query: The so-called aggregate functions are also defined, which perform actions on a set of identical fields in a group of records. Among them:

• AVG(<имя поля>) — average over all values ​​of this field
• COUNT(<имя поля>) or COUNT (*)— number of records
• MAX(<имя поля>) — the maximum of all values ​​of this field
• MIN(<имя поля>) — the minimum of all values ​​of this field
• SUM(<имя поля>) — the sum of all values ​​of this field

Please note that each aggregation function returns the only thing meaning. Examples: determine the publication date of the oldest book in our database; count the number of books in our database: The scope of these functions can be limited using a logical condition. For example, the number of books with the word “SQL” in the title:

4.6.9.DML: Data grouping.

Grouping of data in a statement is carried out using a keyword and a keyword, which is used to set the conditions for dividing records into groups.

is inextricably linked with aggregation functions; without them it is practically not used. divides the table into groups, and the aggregation function calculates the total value for each of them. For example, let’s determine the number of books from each publisher in our database:

The keyword works as follows: first it splits rows into groups, then conditions are imposed on the resulting sets. For example, let's exclude from the previous query those publishing houses that have only one book: Another use case is to include in the result only those publishing houses whose name ends with the substring "Press": What is the difference between these two use cases? In the second option, we could place the condition for selecting records in the keyword section; in the first option, this would not be possible, since it does not allow the use of aggregation functions.

4.6.10.DML: Data sorting.

To sort the data obtained using the operator, a keyword is used. It allows you to sort results by any column or expression specified in<списке_выбора>. Data can be sorted in either ascending or descending order. Example: sort a list of authors alphabetically: A more complex example: get a list of authors sorted alphabetically and a list of their publications, and for each author the list of books is sorted by publication time in reverse order (i.e., more recent books first, then more and more “ancient”): The keyword here specifies the reverse sorting order by field yearpub, keyword (it can be omitted) - direct sort order by field author.

4.6.11.DML: Merge operation.

SQL provides the ability to perform the relational algebra operation UNION on relations that are the results of a SELECT statement. Naturally, these relationships must be defined according to the same scheme. Example: get all Internet links stored in the database publications. These links are stored in tables publishers And wwwsites. In order to get them in one table, we must build the following query:

4.6.12.Using views.

So far we have talked about tables that really are stored in the database. These are the so-called base tables. There is another type of table called “views” (sometimes called “viewable tables”).

When the contents of the underlying tables change, the DBMS automatically re-executes the queries that create the view, resulting in corresponding changes in the views.

The view is defined using the command

CREATE VIEW<имя_представления> [<имя_столбца>,…] AS<запрос> The following restrictions must be observed:

• the view must be based on a single query (not allowed)
• the output of the query that generates the view must be unordered (not allowed)

Let's create a view that stores information about authors, their books and publishers of these books: Now any user whose access rights to this submission enough, can sample data from books. For example: (User access rights to views are also assigned using commands.)

From the above example, the meaning of using views is quite clear. If queries like “select all books by a given author, indicating publishers” are performed quite often, then creating the presented table books will significantly reduce the overhead of joining four base tables authors, titles, publishers And titleauthors. In addition, the view can present information that is not explicitly stored in any of the underlying tables. For example, one of the view columns could be calculated:

Another, previously undescribed, feature is used here - assigning new names to the view columns.

In the example given, the number of publications produced by each publisher would be stored in a column named books_count. Note that if we want to assign new names to the view columns, we need to specify names for everyone columns. The data type of a view column and its null status always depend on how it was defined in the underlying table(s).

A query to select data for a view looks exactly the same as a query for any other table. However, there are restrictions on changing the data in the view. Briefly about them we can say the following:

• If a view is based on a single table, changes to the data in it are allowed. This changes the data in the associated table.
• If a view is based on more than one table, then changes to the data in it are not allowed, because In most cases, the DBMS cannot correctly reconstruct the schema of the base tables from the presentation schema.

Removing a view is done using the operator:

DROP VIEW<имя_представления>

4.6.13.Other SQL features.

The capabilities described below have not yet been standardized, but are presented to one degree or another in almost all modern DBMSs.

• Stored procedures. Practical experience in creating data processing applications shows that it is advisable to move a number of operations on data that implement logic common to all users and are not related to the user interface to the server. However, to write procedures that implement these operations, standard capabilities are not enough, since operators for processing branches, loops, etc. are needed here. Therefore, many DBMS vendors offer their own procedural extensions (PL/SQL from Oracle, etc.). These extensions contain logical operators (IF ... THEN ... ELSE), conditional transition operators (SWITCH ... CASE ...), loop operators (FOR, WHILE, UNTIL) and operators transferring control to procedures (CALL, RETURN). Using these tools, functional modules are created that are stored on the server along with the database. Usually such modules are called stored procedures. They can be called with parameters passed by any user who has the appropriate rights. In some systems, stored procedures can also be implemented as modules external to the DBMS in general-purpose languages, such as C or Pascal.

  SQL - UPDATE query

  Example for PostgreSQL DBMS: CREATE FUNCTION<имя_функции> ([<тип_параметра1>,…<тип_параметра2>]) RETURNS <return types> AS [ | <имя_объектного_модуля>] LANGUAGE 'SQL' | 'C' | 'internal' The created function is called from the SELECT statement (in the same way as aggregation functions are called). For more information about stored procedures, see the article by E. Eisenberg New standard stored procedures in the SQL language, DBMS N 5-6, 1996

• Triggers. For each table, a stored procedure without parameters can be assigned, which is called when a modification statement for this table is executed (INSERT, UPDATE, DELETE). Such stored procedures are called triggers. Triggers are executed automatically, regardless of whether the data modification is caused by the actions of a human operator or an application program. The “average” syntax of the trigger creation operator is: CREATE TRIGGER<имя_триггера>ON<имя_таблицы>FOR (INSERT | UPDATE | DELETE ) [, INSERT | UPDATE | DELETE ]… AS The keyword specifies the name of the table for which the trigger is defined, the keyword specifies which data modification command(s) activates the trigger. The statements after the keyword describe the actions that the trigger performs and the conditions for executing these actions. Any number of statements, stored procedure calls, etc. can be listed here. The use of triggers is very convenient for performing integrity constraint checking operations (see chapter 4.3).
• Event monitors. A number of DBMSs allow the creation of stored procedures that continuously scan one or more tables to detect certain events (for example, the average value of a column reaches a specified limit). If an event occurs, the launch of a trigger, stored procedure, external module and so on. Example: Let our database be part of an automated process control system. The readings of the temperature sensor installed on the cutter are entered in the field of one of the tables. lathe. When this value exceeds a specified limit, an external program is launched that changes the operating parameters of the machine.

The question is old, but I felt that a better answer had not yet been given.

Is there an UPDATE syntax... without specifying column names ?

General solution with dynamic SQL

You don't need to know the column names, except for some unique columns to join (in the example). Works well for every possible corner case I can think of.

This is specific to PostgreSQL. I'm creating dynamic code based on schema_info, specifically a table that is defined in ANSI SQL and supported by most modern DBMSs (beyond except for Oracle). But the statement with PL/pgSQL code doing dynamic SQL is completely non-standard PostgreSQL syntax.

SQL UPDATE

Assuming the corresponding column in for everyone column in, but not vice versa.

may have additional columns.

is optional to update only the selected row.

SQL Fiddle.

Similar answers with more explanations:

Partial solutions with simple SQL

With a list of shared columns

You still need to know the list of column names that both tables share. With a syntax shortcut to update multiple columns - shorter than other answers offered so far anyway.

SQL Fiddle.

This syntax was introduced with Postgres 8.2 in December 2006, long before the question was asked.
More details are provided in the manual and the corresponding answer on dba.SE:

With a list of columns in

If all columns are defined (but not required),
And You you know column names (but not required).

appends to the row from where all columns with the same name have the same value. We don't need to update in this case (nothing changes) and can remove these lines at the beginning of process().
We still need to find the matching string, so in the outer query.

SQL Fiddle.

This is standard SQL, except for the clause.
It works regardless of which column is actually present in, but the query cannot distinguish between actual NULL values ​​and missing columns in, so it is only reliable if all columns in are defined.

There are several possible options, depending on what you you know about both tables.

I have two tables:

will always be a subset (meaning all columns are also in).

I want to update a record with a specific in with their data from for all columns This exists in both in and in

Is there a syntax or any other way to do this without specifying the column names, just saying "set all columns A" ?

I'm using PostgreSQL, so the specific non-standard command is also accepted (not recommended, however).

These concepts relate to databases.

DDL - Data Definition Language. Using this language, data is defined by specifying the data type and presentation structures. Actually, it's part of the language. SQL. But only one. These are the operators that are associated with creation commands, for example CREATE TABLE. The result of these operations is entered into the system directory, which stores information about the tables.

DML - Data Manipulation Language. It is a data management language that can be used to retrieve and modify data. There are two varieties of these languages.

Procedural procedural Non Procedural non-procedural

The difference between them is not as it seems at first glance. For a programmer, it’s like there are procedures, there are no procedures. In reality, procedural languages ​​process data sequentially. That is, record by record, and non-procedural ones operate on entire sets at once. And the difference is clear from here: in procedural languages ​​it is indicated how to obtain data, and in non-procedural languages, what we want to receive. The process in a non-procedural language does not concern us and it is hidden from the developer. The most common non-procedural language is SQL. And here it should become clear what it means when we indicate not the path, but the result. Operator SQL type SELECT * FROM TABLE talks about the result we want. And in this case, we want to get all the records and columns from the table.

UPDATE OPERATOR

There is another non-procedural language QBE. Let's look at it from the outside SQL. So, SQL this is two parts, the first part is for creating objects in the database DDL, and the second part is for manipulating the data in these objects DML. Why such a division? Designing a database is not a simple task and requires serious work. There are special programs that help build a data structure, check connections, and eliminate contradictions at the design stage. As a result of the operation of these programs, a set of commands is formed DDL(in the form of operators SQL) which are launched on the database server and all structures are ready for work. Then the filling begins, I’m already using DML, and then work, again using DML(in the form of operators SQL).

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Author Kaev Artem.

Operator UPDATE changes existing data in the table. The command has the following syntax:

UPDATE SET ( = ( | NULL | DEFAULT),...) [ (WHERE )];

A single statement can be used to set values ​​for any number of columns. However, you can only make changes to each column of a specified table once in the same UPDATE statement. If there is no WHERE clause, all rows in the table will be updated.

If a column is NULLable, you can specify it explicitly. You can also replace the existing value with the default value (DEFAULT) for a given column.

SQL UPDATE Statement Examples

I have the following Planets table:

Example 1: Use the SQL UPDATE statement to change the name of the planet Neptune on Pluto:

UPDATE Planets SET PlanetName = "Pluton" WHERE ID = 3;

In this example, the SQL WHERE clause condition is required because without it, all of the PlanetName column fields in the entire table would change to Pluton. In this case, the ID column comes to our aid, because it is the Primary key that allows a record to be uniquely identified.

Example 2. We will increase the salaries of all teachers by 2 times, and the bonus by 10 times.

Updating data in a database means changing values ​​in existing table records. In this case, it is possible to both change the values ​​of fields in a group of rows (even all rows of the table), and edit the value of a field in an individual row.

In SQL, you can change a record in a database table using the UPDATE command. In its most minimal form, the data update command looks like this:

UPDATE table SET field = value

Here, UPDATE– a command indicating that the request is to update data;

table– the name of the table in which changes will be made;

SET– a command followed by comma-separated fields with assigned values;

field– table field to which the change will be made;

meaning– a new value that will be entered into the field.

For example, if you need to set a field in all rows of a table to zero, you can run the following query:

UPDATE goods SET price = 0

In this case, the price field in absolutely all available rows of the table will take the value 0.

Changing one value

Changing the values ​​of all fields in a table is extremely rare. Most often it is necessary to change the value of a specific entry. To do this, at the end of the line with the UPDATE command, a WHERE directive will be added, which specifies a condition that determines which line the update operation should be performed on.

There is a table:

For example, we need to update the cost of a product with its value known to us num. To do this, run the following query:

UPDATE goods SET price = 150 WHERE num = 2

Now, before the operation of changing fields, a row will be selected that satisfies the condition num = 2. There is only one such row in the table. In this stock the price will be changed to the value 150. As a result, we will get a table with the changed price of the product.

Making changes to multiple lines with a selection condition

If you remember all the variety of conditions in the query, you can imagine how diverse the samples can be. Therefore, update queries can be executed either with one row, or with a group of rows, or with all rows of the table. It all depends on the task you are facing, as well as on which table rows you need to perform update operations on.

For example, we want to halve the price of all goods that currently cost 100 or more. Request:

UPDATE goods SET price = price / 2 WHERE price >= 100

Condition WHERE here contains a rule according to which only products with a price equal to or more than 100 will be selected, and those products with a price below 100 will not be affected by the request.

price = price / 2– the formula by which the new price of goods will be calculated. The new price will be written equal to the old price divided by two.

As a result of executing such a query, we will obtain a table with changed records:

Updating values ​​in multiple row fields

If it is necessary to update several fields at once, all fields with their values ​​are indicated after the SET directive, separated by commas. For example, you need to change the name and price of a product with code 2 to “iron”, costing 300:

UPDATE goods SET title = "iron" , price = 300 WHERE num = 2 !}

This query will assign each matching field in a row its value. And the condition will indicate in which line the changes will be made.

The following are the main types of update operations. Based on them, queries are generated to solve most data modification problems in development using SQL.