SQL Comma Dilemmas: Should You Trail Behind or Lead Ahead?

In the world of SQL, commas are more than just punctuation, they are battlegrounds for debates

Matteo Bennio
Google Cloud - Community
5 min readJul 27, 2024

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Illustration for the article created using DALL-E

In the world of SQL, there are many debates, but one seemingly trivial topic has the potential to spark surprisingly passionate discussions: SQL comma placement. In this article, we’re not talking about optimizing your queries for performance. Instead, we’re focusing on the formatting of SQL code, specifically the discussion between leading and trailing commas.

Many programming languages happily allow a trailing comma after the final element in a list. But not SQL (depending on the dialect) and JSON. This restriction has prompted some developers to adopt a different approach: starting new lines with a leading comma for better code management and editing efficiency.

Comma Strategies in SQL

Before we dive into the pros and cons, let’s set the stage. In the world of SQL, commas are more than just punctuation; they are battlegrounds for debates. Should they lead or trail? To illustrate, let’s put them side by side.

Comparison of leading comma and trailing comma styles in SQL queries

In this simple example, commas either end each line (trailing) or begin each new line (leading). This choice, while seemingly minor, can shape how we structure and manage our SQL queries.

Trailing Comma vs. Leading Comma

In the SQL community, there are two main camps: those who advocate for trailing commas and those who swear by leading commas. Each camp has its reasons, and even prominent figures like Lak Lakshmanan, Director for Data Analytics and AI Solutions at Google Cloud, suggest using leading commas in the BigQuery bible. Let’s explore the reasoning behind each view through various aspects.

Human Readability

Trailing commas are what most of us are used to. They align with our natural reading patterns, making the code flow smoothly. However, leading commas create a vertical alignment that can make it easier to scan and spot items quickly, especially in longer lists. It might look a bit unusual at first, but once you get used to it, it can be quite efficient.

Potential for Syntax Errors

Trailing commas can lead to syntax errors if left at the end of a list, as some SQL engines will not accept this. This makes commenting out or removing the last lines more cumbersome, requiring you to edit the preceding line to remove the unnecessary comma, adding an extra step. Additionally, rearranging lines with trailing commas can be tricky and requires careful adjustment to ensure commas are correctly placed.

Leading commas mitigate these risks. Commenting out, removing, and switching lines becomes simpler and less error-prone since each line starts with a comma, making these changes effortless.

Demonstrating potential syntax errors with trailing comma style

Version Control

Version control is where leading commas truly shine. Changes are neat and tidy, making diffs easier to read. Each modification stands alone, reducing the visual noise in your code reviews. Trailing commas, however, can make diffs harder to read, as changes can affect multiple lines.

Git diff comparison: Trailing comma vs. Leading comma examples

Note: These points assume that the first column is typically a primary attribute, which is less likely to be commented out, rearranged, or modified. If the first column is frequently modified, leading commas can suffer from similar drawbacks as trailing commas.

Now that we’ve laid out the pros and cons of each style, we can see why the discussion is so heated. Both methods have their merits and challenges, and your choice might depend on your team’s preferences and the tools you use.

What the Numbers Tell Us

To better understand the impact of leading versus trailing commas, let’s look at what research and data have to say. Two significant analyses come from Benn Stancil, co-founder and CTO of Mode, and Felipe Hoffa, an ex-Googler now with Snowflake.

Both examined a massive amount of SQL code. Mode analyzed nearly a billion queries, while Felipe Hoffa sifted through 320 GB of SQL from 80,000 GitHub repositories. The results? Despite leading commas showing better performance metrics (fewer syntax errors and more GitHub stars), the vast majority of developers remain loyal to trailing commas. Stancil’s analysis also revealed that the preference for trailing commas and the better performance of leading commas remain consistent across different database types and seniority levels.

BigQuery’s Take

Google BigQuery adds an interesting twist to the trailing versus leading comma discussion. Unlike some SQL dialects that throw a syntax error if a trailing comma is left at the end of a list, GoogleSQL allows trailing commas. So, even though leading commas are recommended by top experts at Google, BigQuery supports trailing commas. Additionally, if you use the “Format Query” feature in the BigQuery UI, it will convert your leading commas to trailing commas. The BigQuery documentation also consistently uses trailing commas.

Conclusion

Did we manage to settle the question? Probably not, but hopefully, it has given you something to think about. Even with a simple SELECT statement, you have to select from multiple choices. There’s no absolute right or wrong here; the key is to stay consistent and use one approach within your team. I hope you found this topic engaging, and maybe it will ignite an interesting discussion at your next daily stand-up.

Wrapping things up, here’s a fun snippet from Benn Stancil:

While leaders lead with leading commas, and trailing commas are leading signs of failing lines, and the tale aligns no matter the database breed, we’re not agreed that it’s best to concede to lead because the more we scale our query kneading, the more we follow the trail to trailing from leading. Because it’s people, who do the reading.

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Google Cloud - Community
Google Cloud - Community

Published in Google Cloud - Community

A collection of technical articles and blogs published or curated by Google Cloud Developer Advocates. The views expressed are those of the authors and don't necessarily reflect those of Google.

Matteo Bennio
Matteo Bennio

Written by Matteo Bennio

Data Analyst at Pampers Messaging Team, specializing in BigQuery practices and data engineering. https://www.linkedin.com/in/matebenyo/

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