ProxySQL: Fixing PostgreSQL Query Digest Normalization

Unpacking the PostgreSQL Digest Problem: Why It Matters to You

Hey guys, let's talk about something super important for anyone using ProxySQL with PostgreSQL: how our query digests are generated. For those new to the game, query digests are essentially unique, normalized representations of your SQL queries. Think of them like a standardized fingerprint for each query, regardless of minor variations like specific parameter values. They're absolutely crucial for understanding your database workload, identifying slow queries, making smart caching decisions, and enabling efficient query routing within ProxySQL. Without accurate digests, you're essentially flying blind when it comes to performance analysis and optimization, and nobody wants that!

Now, here's where we hit a snag, and it's a pretty significant one that's been tracked as Issue #5231. The core problem is that ProxySQL has been incorrectly normalizing PostgreSQL query digests, especially when it encounters quoted identifiers like "TableName" or "ColumnName". Instead of preserving these specific identifiers, the current system was replacing them with generic placeholders, typically a ?. Imagine you have two completely different queries, like SELECT * FROM "Attributes" WHERE "InventoryId"=123; and SELECT * FROM "Users" WHERE "UserId"=44;. In a perfect world, these should have wildly different digests because they refer to different tables and columns, right? But with this bug, both queries might end up with the exact same digest, perhaps something like select * from ? where ?=?. It's like having two different books but they both get assigned the same ISBN – utter chaos for a library system!

The impact of this on you, our awesome users, is pretty significant. First off, your performance monitoring data becomes misleading. You can't accurately track query performance if unrelated queries are bundled under the same digest. This makes it incredibly hard to pinpoint actual bottlenecks or understand specific query patterns. Secondly, if ProxySQL is making routing decisions or applying rules based on these digests, it might misinterpret your intentions, leading to suboptimal performance or even incorrect behavior. And third, and perhaps most insidious, this bug creates a breeding ground for silent regressions. You might think everything's fine, but under the hood, crucial information is being lost, making debugging a nightmare. Fixing this isn't just about squashing a bug; it's about restoring trust, ensuring accurate data, and making ProxySQL an even more robust and reliable partner for your PostgreSQL deployments. That's why we're undertaking this major project to enhance our PostgreSQL digest testing infrastructure – to fix this once and for all and make sure it never comes back. This isn't just a technical detail; it's fundamental to providing the high-quality insights and control you expect from ProxySQL. We're talking about giving you clear, precise visibility into your PostgreSQL queries, so you can optimize with confidence and avoid nasty surprises. Ultimately, this enhancement means a more stable, predictable, and performant database environment for everyone.

Phase 1: Building the Foundation – A Dedicated PostgreSQL Test Environment

Alright, let's dive into Phase 1, which is all about laying down a rock-solid foundation for our testing efforts. Historically, our existing test infrastructure for query digest generation in ProxySQL has been heavily geared towards MySQL. While that's been great for our MySQL users, it left a pretty big gap when it came to PostgreSQL-specific parsing behaviors, especially with those unique identifier rules. This imbalance meant that PostgreSQL-specific bugs, like the one we're tackling with Issue #5231, could slip through the cracks undetected. We simply didn't have the specialized tools to catch them.

That's why the very first, and arguably most critical, step here is to create a brand-new, dedicated PostgreSQL test file. We're talking about test_pgsql_query_digests_stages-t.cpp. This isn't just about adding a few lines of code; it's about establishing an entirely separate and focused testing environment. The beauty of this approach is modularity. By having a distinct file, we can tailor test cases specifically to PostgreSQL's syntax nuances, its quoting rules, and its unique ways of handling queries, without accidentally affecting or complicating our existing MySQL tests. This means cleaner code, easier maintenance in the long run, and a significantly reduced risk of introducing new regressions in either database ecosystem. We'll start by copying from the existing MySQL version (test_mysql_query_digests_stages-t.cpp) as a template – no need to reinvent the wheel, right? But then, the real work begins: customizing it completely to fit PostgreSQL's world.

Crucially, this phase also involves adding PostgreSQL support directly to our test framework. It's not enough to just have new test cases; the framework itself needs to understand the context of PostgreSQL. It needs to know how to interpret PostgreSQL-specific SQL, how to trigger the correct parsing logic, and how to validate the output against PostgreSQL's expectations. This is a deeper integration that ensures our tests are not just running, but running intelligently within a PostgreSQL context. We also need to get started on creating PostgreSQL-specific test data files. These files, like pgsql_quoted_identifiers_digests.hjson (which we'll flesh out more in Phase 2), will house all the specific PostgreSQL queries and their expected digest outcomes. Think of these as our blueprints for success, defining exactly what a correctly digested PostgreSQL query should look like. An absolutely vital rule throughout this entire process is: DO NOT modify the existing test_mysql_query_digests_stages-t.cpp. This is paramount for ensuring backward compatibility. We're enhancing ProxySQL for PostgreSQL, not breaking it for MySQL. By keeping these test suites separate and untouched, we guarantee that our existing, well-tested MySQL functionality remains rock-solid while we build out robust support for PostgreSQL. This focused approach means we can iterate faster, test more thoroughly, and ultimately deliver a more reliable product for all our users. This foundational work is what allows us to confidently move forward, knowing we're building on solid ground.

Phase 2: Mastering Quoted Identifiers – The Comprehensive Test Suite

Alright, moving on to Phase 2, where we tackle the nitty-gritty details of PostgreSQL's quoted identifiers. Guys, this is where things get really interesting and, frankly, a bit tricky. Unlike MySQL, which is often more forgiving or has different conventions, PostgreSQL takes its quoted identifiers (like "MyTable" or "snake_case_column") very seriously. These aren't just cosmetic flourishes; they're essential for preserving case sensitivity, allowing special characters in names, or using reserved keywords as identifiers. The problem with Issue #5231 was precisely that our digest generation wasn't respecting these nuances, treating them like generic placeholders instead of distinct, important parts of your query structure. This phase is all about fixing that oversight through exhaustive testing.

The heart of this phase is the creation of a brand-new test data file: pgsql_quoted_identifiers_digests.hjson. This isn't just any old file; it's going to be our comprehensive arsenal of test cases specifically designed to push the boundaries of how ProxySQL parses and digests PostgreSQL quoted identifiers. We need to ensure that absolutely every permutation and combination is covered to guarantee that these identifiers are preserved correctly in the digest, not incorrectly normalized. Think of it as creating a complete dictionary of how quoted identifiers should behave. We'll be meticulously crafting test cases covering several critical scenarios:

First, we'll start with basic quoted identifiers. This includes straightforward examples like "Users", "Orders", "Products", ensuring that the simplest forms are correctly recognized and preserved. This forms our baseline of expected behavior. Next, we'll move into mixed quoted/unquoted scenarios. In the real world, folks often mix and match. A query might have SELECT column_name FROM "TableName" WHERE "Id" = 123;. We need to ensure that our parser can gracefully handle these combinations, preserving the quoted parts while correctly processing the unquoted ones. This reflects how people actually write SQL, making our tests more realistic.

A particularly challenging area is escaped quotes within identifiers. Imagine you have an identifier like "table\"with\"quotes". That's a fun one, right? Our tests must confirm that these complex, escaped sequences are handled perfectly, without breaking the digest. Then there's case sensitivity preservation. PostgreSQL, unlike some other databases, respects the case of quoted identifiers. "UserTable" is different from "usertable" if quoted. Our digest must reflect this distinction, so test cases like `