Mastering SQL: How to Deduplicate Rows Efficiently

Which SQL statement is used to deduplicate rows in a table?

• A. SELECT DISTINCT
• B. DELETE
• C. CREATE VIEW
• D. GROUP BY

Answer: (A)

The use of the SQL statement SELECT DISTINCT is effective for deduplicating rows in a table because it retrieves unique records from the result set. When this statement is executed, it scans the specified columns and filters out any duplicate entries, returning only one instance of each unique row based on the selected fields. This is particularly useful when you want to have a clean dataset for analysis or reporting, where duplicates could skew results or provide incorrect interpretations. For instance, if you have a table with multiple entries for the same customer, using SELECT DISTINCT on the customer column would yield a single entry for each customer, thereby facilitating a clearer understanding of customer counts and demographics. Other SQL statements like DELETE are used to remove specific rows from a table but do not inherently identify duplicates across multiple records. The CREATE VIEW statement is intended for creating a virtual table based on the results of a query but does not serve the purpose of deduplication on its own. Finally, GROUP BY is often used in conjunction with aggregate functions to group data but does not directly deduplicate the rows; rather, it creates a summary based on grouped criteria. SELECT DISTINCT directly addresses the need to avoid duplicate entries in query results.

Imagine you're browsing through a store, trying to find that perfect shirt, but every rack is overflowing with duplicates. Frustrating, right? That’s kind of what dealing with a messy dataset feels like—especially when you're wrangling rows that should be unique. When you're preparing for the Data Engineering Associate with Databricks exam, understanding how to get those duplicates under control is key to making your dataset shine.

So, what’s the magic spell, you ask? It’s the SQL statement SELECT DISTINCT. Simple, yet incredibly effective. When you run this command, it’s like waving a wand that clears out the clutter. This statement reaches into your table, scans the columns you've specified, and filters out those pesky duplicate entries, leaving you with only the unique rows. You might think, "Well, why do I need this?" Well, let me explain.

Imagine you’re analyzing customer data for your business. If the table has multiple entries for the same customer, using SELECT DISTINCT on that customer column would present you with a tidy list of each unique customer. Now, isn’t that cleaner? You get a clearer picture of customer demographics, helping you make informed decisions without the distraction of duplicates skewing your results.

Now, you might wonder, what other SQL statements are floating around in this space? Let’s take a closer look. There's the DELETE statement, for instance, which can remove specific rows, but it doesn't pinpoint duplicates across your dataset. So, if you're thinking of using DELETE to clean up duplicates, it’s not right for the job. It’s more like trying to tidy up a cluttered room by throwing everything out.

Moving on, we have the CREATE VIEW statement. This nifty command helps create a virtual table based on your results, but it isn’t meant for deduplication. Picture it as setting up a fancy display of what’s already in your table—great for organization, but still filled with duplicates if that’s how your original table looks.

And let’s not forget the GROUP BY clause. This one is a little deceiving because you might think it could eradicate duplicates. While it does group data based on certain criteria, it doesn’t directly remove duplicates. Any duplicates present will still be there; GROUP BY just summarizes the data in a way that can be useful, especially when combined with aggregate functions.

Feeling a bit overwhelmed? Don’t be! The beauty of SQL and tools like Databricks is the way they simplify tasks that can seem daunting at first. Knowing how to use SELECT DISTINCT correctly not only gives you cleaner data, but it also lets you focus on what’s truly important—making smart decisions based on reliable information.

So as you continue your journey toward becoming a Data Engineering Associate, remember this vital tool. The power of SELECT DISTINCT lies in its ability to provide you with a unique dataset, free from the clutter of duplicates. Next time you’re crafting a SQL query, think of this as your go-to answer when faced with unwanted repetition. It’s like traipsing through that store again, except this time, you walk out with that perfect shirt—no duplicates in sight.