SQL SELECT Statement Example

SQL select into

The SELECT INTO statement in SQL is used to create a new table and insert data from a SELECT statement into that table. The basic syntax of the SELECT INTO statement is as follows:

SELECT column1, column2, ...
INTO new_table_name
FROM existing_table_name;

You can also use clauses like WHERE, JOIN,GROUP BY , HAVING ,ORDER BY to filter and sort the data that will be inserted into the new table

For example:

SELECT column1, column2
INTO new_table
FROM existing_table
WHERE column3 = 'some value';

This statement would create a new table called "new_table" and insert the values in column1 and column2 from the "existing_table" where the value in column3 is 'some value'.

It's worth noting that if the new table already exists, the SELECT INTO statement will fail. Also, SELECT INTO statement is not supported by all SQL engines, for example, MySQL does not support it.

The DISTINCT keyword in SQL is used to retrieve only distinct (unique) values in the result set of a SELECT statement. The basic syntax of a SELECT DISTINCT statement is as follows:

SELECT DISTINCT column1, column2, ...
FROM table_name;

For example:

SELECT DISTINCT City
FROM Customers;

This statement would retrieve all distinct (unique) cities from the Customers table.

You can also use the DISTINCT keyword in combination with other clauses like WHERE, JOIN,GROUP BY , HAVING ,ORDER BY to filter and sort the data.

For example:

SELECT DISTINCT column1, column2
FROM table_name
WHERE column3 = 'some value'
ORDER BY column1;

This statement would retrieve the distinct values in column1 and column2 from the table where the value in column3 is 'some value' and sort the results by column1.

SELECT column1, column2, ...
FROM table_name;

You can select data from one table or multiple tables using joins.

For example, you can select all the columns from Customers table

SELECT *
FROM Customers;

You can also use WHERE clause to filter the data based on certain conditions

SELECT column1, column2
FROM table_name
WHERE column3 = 'some value';

or you can use JOIN clause to combine data from multiple tables based on a related column between them

SELECT column1, column2, column3
FROM table1
JOIN table2
ON table1.column = table2.column;

You can also use clauses like GROUP BY , HAVING ,ORDER BY to aggregate and sort the data.

SELECT column1, SUM(column2)
FROM table_name
GROUP BY column1
HAVING SUM(column2) > 100
ORDER BY column1;

This statement would retrieve the values in column1 and the sum of column2 from the table, group the results by column1, filter the group having sum of column2 greater than 100, and sort the result by column1.

SELECT DISTINCT column1, column2, ...
FROM table_name;

For example:

SELECT DISTINCT City
FROM Customers;

This statement would retrieve all unique cities from the Customers table.

You can also use the DISTINCT keyword in combination with other clauses like WHERE, JOIN,GROUP BY , HAVING ,ORDER BY to filter and sort the data.

For example:

SELECT DISTINCT column1, column2
FROM table_name
WHERE column3 = 'some value'
ORDER BY column1;

This statement would retrieve the unique values in column1 and column2 from the table where the value in column3 is 'some value' and sort the results by column1.

It's worth noting that the DISTINCT keyword and UNIQUE keyword have the same meaning and can be used interchangeably.

A subquery in SQL is a query that is nested inside another query, often used to filter or manipulate data based on the results of the outer query. The subquery is placed within the WHERE or HAVING clause of the outer query, and is enclosed in parentheses.

For example, the following query uses a subquery in the WHERE clause to find all customers who have placed an order with a total cost greater than the average cost of all orders:

SELECT customers.*
FROM customers
WHERE EXISTS (
  SELECT 1
  FROM orders
  WHERE orders.customer_id = customers.id
  AND orders.total > (SELECT AVG(total) FROM orders)
);

In this example, the subquery (SELECT AVG(total) FROM orders) is used to calculate the average cost of all orders, and the outer query filters the customer's table to only include customers who have placed an order with a total cost greater than that average.

In SQL, it is possible to use a subquery in the FROM clause to select data from a subquery result set. The subquery is treated as a virtual table and can be used in the same way as a regular table.

For example, the following query uses a subquery in the FROM clause to select the names and order totals for all orders placed by customers who have a credit limit greater than $5000:

SELECT customers.name, orders.total
FROM (SELECT * FROM customers WHERE credit_limit > 5000) as eligible_customers
JOIN orders ON eligible_customers.id = orders.customer_id;

In this example, the subquery (SELECT * FROM customers WHERE credit_limit > 5000) is used to create a virtual table of customers with a credit limit greater than $5000. The outer query then joins this virtual table with the orders table to select the names and order totals for all orders placed by these customers.

It's important to note that the subquery must return one or more columns and one or more rows to be used as a table.

In SQL, the IN operator can be used in conjunction with a subquery in the WHERE clause to filter a query based on the results of the subquery. The subquery returns a set of values, and the IN operator is used to check if a column value is present in that set of values.

For example, the following query uses a subquery in the WHERE clause with the IN operator to select all orders placed by customers who have a credit limit greater than $5000:

SELECT *
FROM orders
WHERE customer_id IN (SELECT id FROM customers WHERE credit_limit > 5000);

In this example, the subquery (SELECT id FROM customers WHERE credit_limit > 5000) returns a set of customer IDs for customers with a credit limit greater than $5000. The outer query then filters the orders table to only include orders placed by customers whose ID is present in that set of customer IDs.

Alternatively, you can also use the NOT IN operator to find the opposite, for example to select all orders placed by customers who have a credit limit less than or equal to $5000

SELECT *
FROM orders
WHERE customer_id NOT IN (SELECT id FROM customers WHERE credit_limit > 5000);

It's important to note that the subquery must return one or more columns and one or more rows to be used with the IN or NOT IN operator.

In SQL, it is possible to select data from multiple tables using a JOIN clause. The JOIN clause combines rows from two or more tables based on a related column between them.

For example, consider two tables: "customers" and "orders". The customers table has a column "id" and the orders table has a column "customer_id". These two columns are related as the "customer_id" in the orders table references the "id" in the customers table.

To select all orders along with the customer information, you can use a JOIN clause to combine the data from these two tables:

SELECT orders.*, customers.*
FROM orders
JOIN customers ON orders.customer_id = customers.id;

In this example, the JOIN clause combines rows from the orders and customers tables where the "customer_id" in the orders table matches the "id" in the customers table. The query then selects all columns from both tables (orders., customers.)

You can also use different types of JOINs like INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN, CROSS JOIN and SELF JOIN depending on the requirement of the query and the data in the tables.

It's important to note that when using JOINs, the query can return duplicate data if there are multiple rows in one table that match a single row in another table, in that case, you can use SELECT DISTINCT to avoid duplicate rows.

In SQL, the SELECT statement is used to query a database and retrieve specific data from one or more tables. The basic syntax of a SELECT query is as follows:

SELECT column1, column2, ...
FROM table_name
WHERE condition;

• The SELECT keyword is used to indicate that a query is being made.
• The column names that you want to retrieve are listed after SELECT keyword.
• The FROM keyword is used to specify the table from which data is being retrieved.
• The WHERE clause is used to filter the results based on a specific condition.

For example, the following query selects the "name" and "email" columns from a "customers" table where the "city" is 'New York':

SELECT name, email
FROM customers
WHERE city = 'New York';

You can also use various clauses like ORDER BY, GROUP BY, HAVING, and LIMIT to manipulate the data and retrieve the required information from the database.

It's important to note that, when retrieving data from a table, it's a best practice to only select the columns that are needed for the current task, as selecting unnecessary columns can slow down the query and consume more resources.

In SQL, the TOP keyword is used to specify the number of rows to be returned by a query. It is most commonly used with the SELECT statement to limit the number of rows returned from a query. The basic syntax for the TOP keyword is:

SELECT TOP (n) column1, column2, ...
FROM table_name
WHERE condition;

• The TOP keyword is followed by an integer value that specifies the number of rows to return.
• The column names that you want to retrieve are listed after SELECT keyword.
• The FROM keyword is used to specify the table from which data is being retrieved.
• The WHERE clause is used to filter the results based on a specific condition.

For example, the following query selects the top 5 names and emails from the "customers" table where the "city" is 'New York':

SELECT TOP (5) name, email
FROM customers
WHERE city = 'New York';

It's worth noting that the TOP keyword is specific to the Microsoft SQL Server, but similar functionality can be achieved in other databases using other keywords or methods such as LIMIT in MySQL and PostgreSQL, FETCH FIRST in IBM's DB2, ROWNUM in Oracle, and so on.

It's also important to note that, when using the TOP keyword, it's a best practice to also use an ORDER BY clause to specify the order in which the rows should be returned, otherwise the query may return arbitrary rows.

In SQL, the SELECT statement is used to query a database and retrieve specific data from one or more tables. To select all the columns from a table, you can use the * operator instead of listing all the columns. The basic syntax for selecting all columns from a table is as follows:

SELECT *
FROM table_name
WHERE condition;

• The SELECT keyword is used to indicate that a query is being made.
• The * operator is used to select all columns from the table.
• The FROM keyword is used to specify the table from which data is being retrieved.
• The WHERE clause is used to filter the results based on a specific condition.

For example, the following query selects all columns from the "customers" table where the "city" is 'New York':

SELECT *
FROM customers
WHERE city = 'New York';

It's important to note that when retrieving all columns from a table, it can be a best practice to only select the columns that are needed for the current task, as selecting unnecessary columns can slow down the query and consume more resources. This is especially true when working with large tables with many columns.

In SQL, the SELECT statement is used to query a database and retrieve specific data. The "AS" keyword is used to give a column or table a temporary or permanent alias. For example, you can use "AS" to give a column a more meaningful name in the result set, like this:

SELECT first_name AS "Full Name" FROM employees;

This query would retrieve the "first_name" column from the "employees" table and display it in the result set as "Full Name".

You can also use "AS" to give a table a temporary alias, like this:

SELECT e.first_name FROM employees AS e;

This query would retrieve the "first_name" column from the "employees" table, but instead of referring to it as "employees.first_name", you can refer to it as "e.first_name" in the query.

In SQL, the CASE statement is used to create conditional logic in a SELECT statement. The basic syntax for a CASE statement in a SELECT statement is as follows:

SELECT column1, column2,
CASE
    WHEN condition1 THEN result1
    WHEN condition2 THEN result2
    ELSE result3
END as column3
FROM table;

The CASE statement starts with the keyword "CASE" followed by one or more "WHEN" clauses, each with a corresponding "THEN" clause. The "ELSE" clause is optional and is used to provide a default result if none of the "WHEN" conditions are met. The "END" keyword is used to indicate the end of the CASE statement.

For example, the following query returns "Low", "Medium", or "High" based on the value of the "price" column:

SELECT product, price,
CASE
    WHEN price < 10 THEN 'Low'
    WHEN price >= 10 AND price < 20 THEN 'Medium'
    ELSE 'High'
END as price_range
FROM products;

It's also possible to include the case statement in the SELECT statement to change the value of the column being selected, for example:

SELECT product, 
CASE
    WHEN price < 10 THEN 'Low'
    WHEN price >= 10 AND price < 20 THEN 'Medium'
    ELSE 'High'
END as price_range,
price
FROM products;

In SQL, a JOIN is used to combine data from two or more tables based on a related column between them. The basic syntax for a JOIN in a SELECT statement is as follows:

SELECT column1, column2, column3
FROM table1
JOIN table2
ON table1.column = table2.column;

The JOIN keyword is used to specify the table to be joined, and the ON keyword is used to specify the column(s) that the tables are joined on.

You can also include a WHERE clause in a SELECT statement with JOIN to filter the results based on certain conditions. The basic syntax for including a WHERE clause in a SELECT statement with JOIN is as follows:

SELECT column1, column2, column3
FROM table1
JOIN table2
ON table1.column = table2.column
WHERE table1.column4 = 'some value';

For example, the following query returns all rows from the "orders" table and the corresponding "customers" table where the customer's city is "New York":

SELECT orders.id, customers.name, orders.total
FROM orders
JOIN customers
ON orders.customer_id = customers.id
WHERE customers.city = 'New York';

It's also possible to use multiple JOIN and WHERE clauses in a single SELECT statement to combine data from multiple tables and filter the results based on various conditions.

In SQL, there are a few ways to select duplicate rows from a table. One way is to use the GROUP BY clause with the HAVING clause to group the rows by one or more columns and return only the groups that have more than one row. The basic syntax for selecting duplicate rows using GROUP BY and HAVING is as follows:

SELECT column1, column2, ...
FROM table
GROUP BY column1, column2, ...
HAVING COUNT(*) > 1;

For example, the following query returns all duplicate rows from the "employees" table based on the "name" and "age" columns:

SELECT name, age
FROM employees
GROUP BY name, age
HAVING COUNT(*) > 1;

Another way to select duplicate rows is to use a self join, which joins a table to itself using a related column. The basic syntax for selecting duplicate rows using a self join is as follows:

SELECT t1.*
FROM table t1
JOIN table t2
ON t1.column = t2.column
WHERE t1.id > t2.id;

For example, the following query returns all duplicate rows from the "employees" table based on the "email" column:

SELECT t1.*
FROM employees t1
JOIN employees t2
ON t1.email = t2.email
WHERE t1.id > t2.id;

It's also possible to use the DISTINCT keyword with the SELECT statement to return only unique rows, effectively removing the duplicates.

SELECT DISTINCT column1, column2, ...
FROM table;

It's worth noting that in some cases, duplicates can be removed by using a combination of both the GROUP BY and DISTINCT keywords.