To get 2 distinct rows from 1 row with 3 tables in SQL Oracle, you can use the UNION ALL operator. This operator is used to combine the result set of two or more SELECT statements.
In this case, you can write two SELECT statements, each retrieving distinct rows from the specific tables, and then use the UNION ALL operator to combine the results.
For example:
SELECT column1, column2 FROM table1 WHERE condition1 UNION ALL SELECT column1, column2 FROM table2 WHERE condition2;
This query will retrieve distinct rows from table1 and table2, based on the specified conditions, and combine them into a single result set.
How to handle duplicate records while querying multiple tables in SQL?
There are several ways to handle duplicate records while querying multiple tables in SQL:
- Use the DISTINCT keyword in your query to eliminate duplicate records from the result set. For example:
SELECT DISTINCT column1, column2 FROM table1 JOIN table2 ON table1.column = table2.column;
- Use the GROUP BY clause in your query to group the records based on certain columns and perform aggregate functions. This can help eliminate duplicates in the result set. For example:
SELECT column1, COUNT(*) FROM table1 JOIN table2 ON table1.column = table2.column GROUP BY column1;
- Use subqueries to filter out duplicate records before joining multiple tables. For example:
SELECT column1, column2 FROM (SELECT DISTINCT column1 FROM table1) AS t1 JOIN table2 ON t1.column1 = table2.column;
- Use the ROW_NUMBER() function to assign a unique row number to each record and then filter out duplicates based on this row number. For example:
WITH CTE AS ( SELECT column1, column2, ROW_NUMBER() OVER (PARTITION BY column1 ORDER BY column2) AS rn FROM table1 JOIN table2 ON table1.column = table2.column ) SELECT column1, column2 FROM CTE WHERE rn = 1;
By using these techniques, you can effectively handle duplicate records while querying multiple tables in SQL.
What is the significance of DISTINCT keyword in SQL queries?
The DISTINCT keyword is used in SQL queries to retrieve unique values from a specified column or combination of columns. It eliminates duplicate rows from the result set and returns only distinct values.
The DISTINCT keyword is helpful in situations where you need to eliminate duplicate records from a table or retrieve only unique values from a column. It helps in simplifying the output and improving the readability of the results.
Overall, the DISTINCT keyword helps in better data visualization, data analysis, and making the SQL query results more meaningful.
What is the significance of normalization in eliminating duplicate records?
Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. By eliminating duplicate records through normalization, it ensures that each piece of data is stored in only one place, making it easier to maintain consistency and accuracy of the data.
When duplicate records are consolidated and normalized, it helps to prevent inconsistencies and contradictory information that can arise from having multiple versions of the same data. This also reduces the risk of data errors and inconsistencies, leading to better data quality and reliability.
Normalization also helps in improving data retrieval and overall database performance by reducing the amount of redundant data stored in the database. This can lead to faster query processing and more efficient use of storage space.
Overall, normalization plays a significant role in ensuring that data is accurately and efficiently managed in a database, which is essential for making informed decisions and maintaining the integrity of the data.
