Relational database management and querying are frequently done using the Structured Query Language. Users can combine the output of many SELECT queries into a single result set using the UNION operator, a helpful SQL union feature. Knowing when and how to use UNION effectively can help expedite reporting and data retrieval. Using UNION, you can remove duplicate records and generate more complete query results.
Important UNION Rules
=> Same Number of Columns
Every SELECT statement must return the same number of columns.
=> Compatible Data Types
All queries must be able to use the data types of the associated columns.
=> Default Removal of Duplicates
By default, UNION removes duplicate rows from the final result set.
=> Column Order Is Important
All SELECT statements must have the same column order.
How UNION Works in SQL
The UNION in SQL joins the result sets of two or more SELECT queries into a single result set by deleting duplicate entries by default. Each SELECT statement in the UNION must have the same number of columns and order. To retain duplicates, use UNION ALL instead. The queries within the UNION are conducted individually and then merged. It is frequently used to combine similar data from several tables or queries, making it handy for reporting and data aggregation while maintaining data consistency across datasets.
Syntax of UNION
The basic syntax of the UNION operator is:
SELECT column_name(s) FROM table1
UNION
SELECT column_name(s) FROM table2
- The number of columns obtained by each SELECT query within the UNION must be identical.
- Columns at the same position in each SELECT statement should be of identical data types.
- For example, the data types “char” and “varchar” are identical.
- The SELECT statements’ columns must be in the correct sequence.
Common Use Cases of UNION in SQL
=> Combining Information from Several Tables with Comparable Structures
Combining data from several tables with the same structure but storing various kinds of information is one of UNION’s most popular uses. For instance, if a company maintains separate tables for domestic and international customers but needs a unified list, UNION can be used:
SELECT customer_id, name, email FROM domestic_customers
UNION
SELECT customer_id, name, email FROM international_customers
This query consolidates customer data from both tables while eliminating duplicate records.
=> Integrating Current and Historical Data
Organizations frequently maintain distinct tables for historical and current data to enhance efficiency and effectively handle big datasets. Analysts can use UNION to retrieve historical and current data using a single query:
SELECT customer_id, name, email FROM domestic_customers
UNION
SELECT customer_id, name, email FROM international_customers.
This query consolidates customer data from both tables while eliminating duplicate records.
=> Retrieving Data from Several Sources
When dealing with different databases or schemas, the UNION facilitates consolidating data from various sources into a single dataset. For example, if sales data is housed in many regional databases, a UNION query can generate a combined report:
SELECT product_id, sales_amount FROM sales_db1.north_region_sales
UNION
SELECT product_id, sales_amount FROM sales_db2.south_region_sales.
Performance Considerations of UNION in SQL
The UNION operator is used to merge the results of many SELECT queries. While it is useful for combining datasets, it has performance implications that can affect query execution time and resource utilization.
=> Sorting Overhead
By default, SQL union performs an implicit DISTINCT operation to delete duplicate records. This necessitates sorting or hashing, which can be computationally expensive, particularly with huge datasets. If duplicates are not a problem, UNION ALL is preferred since it avoids the costly deduplication step.
=> Index Utilization
While indexes boost query efficiency, they may not always be fully utilized when using UNION, especially for sorting. Having suitable indexes on the involved tables can help increase performance.
=> Execution Plan Complexity
Each SELECT statement within a UNION is processed individually before the results are merged. If the individual queries are sophisticated, the overall execution strategy may become inefficient. Optimizing each SELECT query independently and ensuring it returns only the relevant data can improve performance.
=> Memory and CPU Usage
Sorting and deduplication demand a large amount of memory and CPU resources. If the dataset is huge, temporary tables or partitions may help increase speed.
Use UNION ALL whenever possible to improve performance and ensure proper indexing and query structure.
Summing It Up
The SQL union operator is a powerful SQL feature that combines data from numerous queries while removing duplicates. Understanding its application and optimizing queries properly can dramatically boost database performance. For the best results, utilize UNION ALL when duplicate records are required and UNION when a clean, unique dataset is needed.
