Advanced SQL

Welcome to the exciting realm of Advanced SQL! In this section, we'll delve into more complex and powerful features of SQL that go beyond basic querying and data manipulation. Prepare to expand your SQL skillset and become proficient in handling intricate database operations.

Window Functions

Window functions perform calculations across a set of table rows that are related to the current row. They are different from aggregate functions because they don't collapse the rows in the result set. Each row retains its identity while being analyzed with respect to the window frame.

Key concepts include:

• PARTITION BY: Divides the rows into partitions where the window function is applied.
• ORDER BY: Sorts the rows within each partition.
• Window Frame: Defines the set of rows that will be used in the calculation (e.g., ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW).

Examples:

    SELECT
        column1,
        column2,
        RANK() OVER (PARTITION BY partition_column ORDER BY order_column DESC) AS ranking
    FROM
        table_name;
        

Common Table Expressions (CTEs)

CTEs are named temporary result sets defined within the execution scope of a single SELECT, INSERT, UPDATE, or DELETE statement. They are not stored as objects, but only exist during query execution. They are crucial in making complex queries more readable and manageable.

Use cases include:

• Breaking complex queries: Breaking complex queries into simpler logical units.
• Recursive queries: Performing recursive processing of data (common for hierarchical data).
• Multiple references: Using a result set multiple times in one query.

Example:

    WITH SalesSummary AS (
        SELECT
            customer_id,
            SUM(order_amount) AS total_spent
        FROM
            orders
        GROUP BY
            customer_id
    )
    SELECT
        customers.name,
        SalesSummary.total_spent
    FROM
        customers
    JOIN
        SalesSummary ON customers.id = SalesSummary.customer_id;
        

Subqueries

A subquery (or inner query) is a query nested inside another query. Subqueries can be used in the SELECT, FROM, or WHERE clauses of another query. There are three types of subqueries: scalar, row, and table.

• Scalar Subqueries: Return a single value.
• Row Subqueries: Return one row of multiple columns.
• Table Subqueries: Return multiple rows and multiple columns.

Example:

    SELECT
        name
    FROM
        employees
    WHERE
        department_id IN (
            SELECT
                id
            FROM
                departments
            WHERE
                location = 'New York'
        );
        

Advanced Joins

Beyond basic inner joins, SQL offers other types of joins that handle cases where data may be missing in one or more tables, like:

• Left Join: Includes all rows from the left table and the matching rows from the right table.
• Right Join: Includes all rows from the right table and the matching rows from the left table.
• Full Outer Join: Includes all rows from both tables.

Example:

    SELECT
        customers.name,
        orders.order_date
    FROM
        customers
    LEFT JOIN
        orders ON customers.id = orders.customer_id;
        

Data Manipulation Language (DML) Advanced

Moving beyond simple INSERT, UPDATE, and DELETE statements, you can leverage techniques like:

• INSERT INTO ... SELECT: Inserts rows from the result of a query.
• UPDATE ... JOIN: Updates rows in one table based on matching rows from another table.
• DELETE ... JOIN: Deletes rows in one table based on matching rows from another table.

Example:

    UPDATE
        employees
    SET
        salary = salary * 1.10
    WHERE
        department_id IN (
            SELECT id FROM departments WHERE name = 'Engineering'
        );
        

Transactions and Concurrency

Transactions are a sequence of operations performed as a single logical unit of work, ensuring that database changes follow ACID properties:

• Atomicity: All changes in a transaction either fully succeed or fully fail.
• Consistency: The database remains in a consistent state after a transaction.
• Isolation: Transactions are isolated from the effects of other concurrent transactions.
• Durability: Committed transactions persist even if the system fails.

Understanding transaction handling and concurrency control is essential for building reliable, multi-user applications.

Indexing Strategies

Effective indexing is critical for optimal database performance. Learn to choose the correct types of indexes for different use cases:

• B-tree Index: Commonly used for range searches and equality conditions.
• Hash Index: Optimized for equality conditions but doesn't support range searches.
• Composite Index: Index on multiple columns that enhances query performance.

Understand when and how to create an index for frequently accessed columns in WHERE, JOIN, and ORDER BY clauses.

This section lays the foundation for tackling complex data requirements and advanced database administration tasks, enabling you to efficiently handle a wide range of data challenges.