Database Concepts

What is a Query Execution Plan?

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A query execution plan is a detailed roadmap that shows exactly how a database will execute your SQL query. When you submit a query, the database doesn’t just start grabbing data randomly. Rather, it creates a step-by-step strategy for retrieving and processing your data in the most efficient way possible.

The query execution plan is that strategy made visible.

Basically, the SQL you write tells the database what you want, but the execution plan shows you how it’s actually going to get it. This includes which tables it’ll scan, what indexes it’ll use, how it’ll join tables together, and in what order everything will happen.

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What is an Index Scan?

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An index scan is a method databases use to retrieve data by reading through an index from start to finish. The database reads every entry in the index sequentially, checking each one to see if it matches your query conditions.

This is different from an index seek, where the database jumps directly to specific values in the index. Index scans happen when the database determines it needs to examine a large portion of the index, or when it can’t use the index’s sorted structure to go directly to the data you need.

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What is an Index Seek?

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An index seek is the fastest way a database can use an index to find data. When you perform a seek, the database jumps directly to the exact location in the index where your data lives, grabs what it needs, and moves on. No scanning, no reading through irrelevant entries. Just a precise lookup using the index’s sorted structure.

This is fundamentally different from an index scan, where the database reads through the index sequentially. Seeks are only possible when your query conditions allow the database to pinpoint specific index entries without examining others.

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What is Query Optimization?

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Query optimization is the process of finding the most efficient way to execute a database query.

When you write a SQL query, you’re basically telling the database what data you want, but the database has to figure out how to actually retrieve it. That’s the main job of the query optimizer. The query optimizer is a dedicated component of the database management system (DBMS) that evaluates various possible execution paths and selects the most efficient one.

But there are also things that we can do to help the query optimizer, such as writing efficient SQL, properly indexing tables, maintaining up-to-date statistics, etc.

Understanding how the optimizer works and knowing how to steer it toward better execution plans is what we mean by query optimization.

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What is a UNION ALL in SQL?

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UNION ALL is SQL’s way of combining result sets from multiple queries without worrying about duplicates. If you’ve used UNION before, UNION ALL is its faster, less fussy sibling that keeps every single row from all your queries, even if some rows are identical.

So UNION removes duplicate rows automatically, while UNION ALL keeps everything.

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What is a UNION in SQL?

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If you ever find yourself needing to combine the results from multiple SELECT statements into a single result set, UNION is probably going to be the tool for the job. By “UNION“, I mean the UNION operator.

The UNION operator takes the output from two SELECT queries and stacks them on top of each other. It basically merges two lists into one, removing any duplicates along the way.

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What is a Cross Join?

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Cross joins are one of the more straightforward join types in SQL, but they’re also one of the most misunderstood and potentially dangerous if used carelessly. Understanding when and how to use them properly can help you solve certain data problems efficiently while avoiding performance disasters.

A cross join returns the Cartesian product of two tables. This means that it combines every row from the first table with every row from the second table. If you have 10 rows in one table and 5 rows in another, you might immediately assume that it will return 15 rows. But you’d be wrong. A cross join will return 50 rows. No join condition in the ON clause. Just every possible combination of rows.

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What is a Self Join?

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When working with SQL databases, you’ll sometimes encounter scenarios where the data you need to compare or relate exists in the same table. Typical examples of this include employees who manage other employees, tasks that depend on other tasks, or categories nested within categories. These situations call for a specific querying approach called a self join.

A self join is a technique that lets you compare and relate rows within a single table. This makes them perfect for working with hierarchical data, finding relationships between records, and solving a wide range of queries that would otherwise be difficult or impossible with standard joins alone.

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What is a Subquery?

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A subquery is a query nested inside another SQL statement. It’s basically a query within a query. You’re using the results of one SELECT statement to help another SQL statement do its job.

Subqueries let you break down complex problems into smaller, more manageable pieces, making your SQL more readable and often more powerful. The outer query relies on the inner query (the subquery) to provide data, filter results, or perform calculations. Once the subquery executes and returns its results, the outer query uses that information to complete its task.

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What is a Materialized View?

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A materialized view is a database object that stores the results of a query physically on disk, rather than computing them on the fly every time you need them. It’s basically a snapshot of your query results that you can refresh periodically. Unlike regular views (which are just saved queries that execute each time you use them), materialized views pre-compute and cache the data, making subsequent reads much faster.

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