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* **Redis**: To be used as a PubSub broker.
Now, let's dive into some core SQL concepts that are essential for working with **Databricks SQL**. First up: **SELECT** statements. The `SELECT` statement is the workhorse of SQL. It's used to retrieve data from one or more tables. You specify the columns you want to retrieve after the `SELECT` keyword. For example, `SELECT column1, column2 FROM table_name;`. The `FROM` clause specifies the table from which you want to retrieve the data. Next, **WHERE** clauses. The `WHERE` clause is used to filter the results based on certain conditions. This allows you to retrieve only the data that meets your criteria. For example, `SELECT * FROM table_name WHERE column1 = 'value';`. Then, there's the **JOIN** operation. Joins are used to combine data from multiple tables based on related columns. There are different types of joins, including `INNER JOIN`, `LEFT JOIN`, `RIGHT JOIN`, and `FULL OUTER JOIN`. The most common is the `INNER JOIN`, which returns only the rows that have matching values in both tables. Moving on, **GROUP BY** and **HAVING** clauses. The `GROUP BY` clause is used to group rows that have the same values in specified columns. It's often used with aggregate functions like `COUNT`, `SUM`, `AVG`, `MIN`, and `MAX`. The `HAVING` clause is used to filter the results of a `GROUP BY` query. Lastly, **ORDER BY** clause. The `ORDER BY` clause is used to sort the results of your query. You can sort by one or more columns in ascending (`ASC`) or descending (`DESC`) order. Understanding these core concepts is crucial for writing effective SQL queries in **Databricks SQL**. You'll use these building blocks to explore, analyze, and extract insights from your data.
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