BigQuery Joins and Unions

Google BigQuery is a powerful data warehousing platform that enables users to process and analyze large volumes of data in real-time. With BigQuery's query language SQL, it becomes easy to extract insights from the vast amount of data stored in the platform. In this article, we will discuss one of the most critical features of BigQuery - Joins and Unions.

Joins are an essential part of data analysis as they allow users to combine multiple tables based on a common key or column. There are three types of joins supported by BigQuery: INNER JOIN, LEFT OUTER JOIN, and FULL OUTER JOIN. Let's take a closer look at each type of join in more detail.

1. INNER JOIN - This is the most common type of join used to combine two tables based on a common key or column. The output of this join will contain only those rows that have matching values in both tables.

SELECT * 
FROM table1 
INNER JOIN table2 
ON table1.common_key = table2.common_key;

In the above example, we are joining two tables named table1 and table2 based on a common column common_key. The output will only contain those rows that have matching values in both tables for the common_key column.

2. LEFT OUTER JOIN - This type of join is used to combine two tables, where all rows from the left table are included in the result set, even if they do not have a match in the right table.

SELECT * 
FROM table1 
LEFT JOIN table2 
ON table1.common_key = table2.common_key;

In this example, we are joining two tables named table1 and table2 based on a common column common_key. The output will include all rows from the left table (table1) and only those rows from the right table (table2) that have matching values for the common_key column.

3. FULL OUTER JOIN - This type of join is used to combine two tables, where all rows from both tables are included in the result set, even if they do not have a match in the other table.

SELECT * 
FROM table1 
FULL JOIN table2 
ON table1.common_key = table2.common_key;

In this example, we are joining two tables named table1 and table2 based on a common column common_key. The output will include all rows from both the left and right tables, even if they do not have a match in the other table.

Unions, on the other hand, combine multiple tables into a single result set, where each row represents data from a different table. In BigQuery, there are two types of unions: UNION ALL and UNION. Let's take a closer look at each type of union in more detail.

1. UNION ALL - This type of union combines all rows from multiple tables into a single result set without any filtering or duplication removal.

SELECT * 
FROM table1 
UNION ALL 
SELECT * 
FROM table2;

In this example, we are combining two tables named table1 and table2. The output will contain all rows from both the tables, including duplicates.

2. UNION - This type of union combines all rows from multiple tables into a single result set without any filtering or duplication removal but with duplicates removed.

SELECT * 
FROM table1 
UNION 
SELECT * 
FROM table2;

In this example, we are combining two tables named table1 and table2. The output will contain all rows from both the tables, but duplicates will be removed.

In conclusion, joins and unions are essential features of BigQuery that enable users to extract insights from large volumes of data stored in the platform. Whether it's combining two or more tables based on a common column or merging multiple tables into a single result set, BigQuery makes it easy for users to perform complex queries and analyze data efficiently.