Within the WHERE clause lies many possibilities for modifying your SQL statement. Among these possibilities are the EXISTS, UNIQUE, DISTINCT, and OVERLAPS predicates. Here are some examples of how to use these in your SQL statements.
DISTINCT is used to filter unique records out of the records that satisfy the query criteria. The "GROUP BY" clause is used when you need to group the data and it should be used to apply aggregate operators to each group.
Inner Join Creates Duplicate Records
- If the Product status is Pending (In ProdMaster)
- User is allowed to view the product (In Allowed User - User code)
- Show the product code / Product name without duplicate.
To use the WHERE clause to perform the same join as you perform using the INNER JOIN syntax, enter both the join condition and the additional selection condition in the WHERE clause. The tables to be joined are listed in the FROM clause, separated by commas.
Inner
Join joins two table on the basis of the column which is explicitly specified in the ON clause.
Difference between Natural JOIN and INNER JOIN in SQL :
| SR.NO. | NATURAL JOIN | INNER JOIN |
|---|
| 3. | In Natural Join, If there is no condition specifies then it returns the rows based on the common column | In Inner Join, only those records will return which exists in both the tables |
The FULL OUTER JOIN keyword returns all records when there is a match in left (table1) or right (table2) table records. Note: FULL OUTER JOIN can potentially return very large result-sets! Tip: FULL OUTER JOIN and FULL JOIN are the same.
The UNIQUE constraint ensures that all values in a column are different. Both the UNIQUE and PRIMARY KEY constraints provide a guarantee for uniqueness for a column or set of columns. A PRIMARY KEY constraint automatically has a UNIQUE constraint.
SQL | Remove Duplicates without Distinct
- Remove Duplicates Using Row_Number. WITH CTE (Col1, Col2, Col3, DuplicateCount) AS ( SELECT Col1, Col2, Col3, ROW_NUMBER() OVER(PARTITION BY Col1, Col2, Col3 ORDER BY Col1) AS DuplicateCount FROM MyTable ) SELECT * from CTE Where DuplicateCount = 1.
- 2.Remove Duplicates using self Join.
- Remove Duplicates using group By.
The SELECT DISTINCT statement is used to return only distinct (different) values. Inside a table, a column often contains many duplicate values; and sometimes you only want to list the different (distinct) values.
To count the number of different values that are stored in a given column, you simply need to designate the column you pass in to the COUNT function as DISTINCT . When given a column, COUNT returns the number of values in that column. Combining this with DISTINCT returns only the number of unique (and non-NULL) values.
COUNT(expression) like all aggregate functions, can take an optional DISTINCT clause. The DISTINCT clause counts only those columns having distinct (unique) values. COUNT DISTINCT does not count NULL as a distinct value. The ALL keyword counts all non-NULL values, including all duplicates.
The main difference between unique and distinct is that UNIQUE is a constraint that is used on the input of data and ensures data integrity. While DISTINCT keyword is used when we want to query our results or in other words, output the data.
The DISTINCT keyword is applied to all columns. It means that the query will use the combination of values in all columns to evaluate the distinction. If you want to select distinct values of some columns in the select list, you should use the GROUP BY clause.
The SQL LIKE OperatorThe LIKE operator is used in a WHERE clause to search for a specified pattern in a column. There are two wildcards often used in conjunction with the LIKE operator: % - The percent sign represents zero, one, or multiple characters. _ - The underscore represents a single character.
We've simply repeated the
JOIN clause and joined
three tables.
Joining 3 Tables Using a Junction Table
- The first step is to look at the schema and select the columns we want to show.
- The next step is to determine which tables will be necessary for the query.
- In the final part, we'll have to join all the tables together.
The SQL COUNT(), AVG() and SUM() Functions
- COUNT() Syntax. SELECT COUNT(column_name) FROM table_name. WHERE condition;
- AVG() Syntax. SELECT AVG(column_name) FROM table_name. WHERE condition;
- SUM() Syntax. SELECT SUM(column_name) FROM table_name. WHERE condition;
select city, length(city) from (select city from STATION order by length(city) DESC, city ASC) where rownum = 1 union select city, length(city) from (select city from STATION order by length(city), city ASC) where rownum = 1; The idea is to get the longest and shortest city then union them into one result.
SQL Server DIFFERENCE() FunctionThe DIFFERENCE() function compares two SOUNDEX values, and returns an integer. The integer value indicates the match for the two SOUNDEX values, from 0 to 4. 0 indicates weak or no similarity between the SOUNDEX values. 4 indicates strong similarity or identically SOUNDEX values.
How to count distinct values over multiple columns using SQL
- Method-1 Using a derived table (subquery) You can simply create a select distinct query and wrap it inside of a select count(*) sql, like shown below: SELECT COUNT(*)
- Method-2 Using Concatenated columns.
- Method-3 If performance is a factor.
- Enjoy great content like this and a lot more !
For this, we can use the ROW_NUMBER() function of SQL server. ROW_NUMBER() returns a unique row number for the current row. So now, the logic that we can use for our purpose is: Create a data source that will select all the required data that is grouped together by a column, along with a row number to each row.
In SQL, count (*) does not take parameters and returns the total number of rows in a particular table. The difference between COUNT (*) and COUNT (ALL) is that COUNT (*) also counts NULL values and duplicates but COUNT (ALL) does count only unique and non-null values.
Introduction to MySQL DISTINCT clauseWhen querying data from a table, you may get duplicate rows. In order to remove these duplicate rows, you use the DISTINCT clause in the SELECT statement.
When you specify a PRIMARY KEY constraint for a table, the Database Engine enforces data uniqueness by creating a unique index for the primary key columns. This index also permits fast access to data when the primary key is used in queries.
Join 4 tables in SQL query
- Friends id follower following --------------------- 1 2 3 2 4 5.
- Family id follower following --------------------- 1 5 6 2 7 8.
- Following id follower following --------------------- 1 9 10 2 11 12.
- Acquaintances id follower following --------------------- 1 13 14 2 15 16.
To join tables, you use the cross join, inner join, left join, or right join clause for the corresponding type of join. The join clause is used in the SELECT statement appeared after the FROM clause. Note that MySQL hasn't supported the FULL OUTER JOIN yet.
The simplest Join is INNER JOIN.
- INNER JOIN: The INNER JOIN keyword selects all rows from both the tables as long as the condition satisfies.
- LEFT JOIN: This join returns all the rows of the table on the left side of the join and matching rows for the table on the right side of join.
