Impara Cost-Based Optimization | Planning and Optimization

Cost-based optimization is a process used by SQL engines to choose the most efficient way to execute a query. The optimizer evaluates multiple possible execution plans and estimates their costs before selecting one. Several factors influence the cost estimation:

I/O operations: the number of disk reads and writes required;
CPU usage: the processing power needed to evaluate expressions and perform joins;
Row counts: the estimated number of rows processed at each step;
Index usage: whether indexes can speed up data access;
Data distribution and table sizes: how data is spread across tables.

The SQL engine analyzes these factors for each potential plan. It may consider whether to read an entire table (a full table scan) or use an index to find specific rows more quickly. The optimizer's goal is to minimize the total cost, which usually translates to faster query execution and lower resource consumption.


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-- Example: Query that could use a full table scan or an index scan
SELECT name, salary
FROM employees
WHERE salary > 60000;

When the SQL engine receives a query like the one above, it considers alternative ways to retrieve the results. For instance, it might scan the entire employees table to find all rows where salary > 60000, or it might use an index on the salary column (if one exists) to jump directly to the relevant rows. The optimizer estimates the cost of each plan, factoring in the expected number of rows, the amount of data to read from disk, and the CPU needed to process the filter. The plan with the lowest estimated cost is chosen for execution.


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-- Example: Join query affected by cost-based optimization
SELECT e.name, d.name AS department
FROM employees e
JOIN departments d ON e.department_id = d.id
WHERE d.name = 'Engineering';

1. What is the primary goal of cost-based optimization in SQL query execution?

2. Which factor is NOT typically considered in cost estimation?

3. Fill in the blank: The optimizer selects the plan with the ________ estimated cost.

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I/O operations: the number of disk reads and writes required;
CPU usage: the processing power needed to evaluate expressions and perform joins;
Row counts: the estimated number of rows processed at each step;
Index usage: whether indexes can speed up data access;
Data distribution and table sizes: how data is spread across tables.