How Fast Path and Regular Path Work in PostgreSQL Functions

Welcome to this deep dive into PostgreSQL's function execution mechanisms! If you're a developer working with PostgreSQL, you've probably called functions from your application code countless times. But have you ever wondered what's happening behind the scenes when you invoke those functions? Today, we're exploring the "fast path" and "regular path" approaches to executing functions in PostgreSQL. We'll break it down step by step, keeping things straightforward and practical.

Understanding Function Execution in PostgreSQL

PostgreSQL allows you to define and execute functions (also known as stored procedures in some databases) to encapsulate logic on the server side. When your application needs to run one of these functions, it sends a request over the connection. The way this request is handled can follow different "paths" depending on how you structure the call.

The two main paths we'll discuss are:

• Regular Path: The standard way of executing queries and functions using libpq (PostgreSQL's C library interface) or equivalent in other drivers.
• Fast Path: A specialized, lower-level interface designed for simple function calls, offering a more direct route to the server.

These paths primarily come into play from the client side, using APIs like libpq. Under the hood, they affect how parameters are passed, results are retrieved, and overhead is managed.

The Regular Path

The regular path is what most developers use without even thinking about it. When you execute a function via a query like `SELECT my_function(arg1, arg2);`, you're going through the standard query execution pipeline.

How It Works

1. Query Submission: Your client library (e.g., libpq's `PQexec` or prepared statements via `PQprepare` and `PQexecPrepared`) sends the SQL statement to the server.
2. Parsing and Planning: The server parses the query, plans the execution (considering indexes, joins if any, etc.), and optimizes it.
3. Execution: The function is invoked, parameters are bound, and the result is computed.
4. Result Handling: Results are sent back in text or binary format, with the client handling conversion and buffering.

This path is flexible and supports complex queries, including those with multiple statements or set-returning functions. Modern best practices often involve prepared statements, which cache plans on the server for repeated use, reducing overhead.

Pros

• Versatile: Handles any type of query or function, including aggregates, windows, or procedures.
• Safe and Modern: Supports binary data transmission for efficiency, and it's the recommended approach in current PostgreSQL versions.
• Error Handling: Built-in support for detailed error messages and transaction management.

Cons

• Overhead: Involves more steps like full query parsing, which can add latency for very simple calls.

If you're using higher-level drivers like JDBC or psycopg2 (Python) they typically use this path under the covers.

The Fast Path: Bypassing the Overhead for Speed

The fast path is a legacy interface in libpq that's optimized for invoking simple server functions directly. It's like a shortcut that skips some of the regular query machinery, making it potentially quicker for basic use cases.

How It Works

Instead of sending a full SQL query, you use the `PQfn` function in libpq to call a server function by its Object ID (OID).

Here's a quick breakdown:

• Length of the parameter.
• Whether it's an integer (for byte-swapping).
• The actual value (as a pointer or direct integer).

For NULLs, set length to -1.

• `result_buf` is a pre-allocated buffer for the return value.
• The server executes the function and fills the buffer directly.

Differences from the Regular Path

• Bypass Parsing: No SQL string is sent or parsed; it's a direct function invocation by OID.
• Binary-Only: Always uses binary transmission, but you handle buffers yourself.
• Limited Scope: Only for plain functions (not aggregates, windows, or set-returning ones). Can't handle complex results like result sets.
• Performance: Potentially faster for very simple, frequent calls due to less protocol overhead, but the difference is minimal today with optimized prepared statements.

Pros

• Efficiency for Simples: Less latency for basic scalar functions.
• Direct Control: Fine-grained handling of binary data.

Cons

• Obsolete-ish: PostgreSQL docs note it's somewhat outdated. Prepared statements with binary mode offer similar speed plus more features.
• Risky: You must allocate buffers correctly—no automatic checks. Security risks if misused (it's a "trapdoor" into internals).
• Not Portable: Specific to libpq; other drivers might have equivalents (e.g., JDBC's Fastpath), but it's not universal.
• No Sets: Can't return multiple rows.

When to Choose Fast Path vs Regular Path

• Use Regular Path for most cases: It's safer, more flexible, and performant enough with prepared statements. Ideal for applications with varied queries or when using ORMs.
• Consider Fast Path if: You're in a high-performance C/C++ app calling the same simple function millions of times, and you've measured a bottleneck in the regular path. But first, try optimizing with binary prepared statements!

In modern PostgreSQL (version 16+ as of 2025), the performance gap is small, so fast path is rarely needed unless you're squeezing every microsecond.

Conclusion

Exploring the difference between the fast path and the regular path helps us understand how PostgreSQL actually runs functions behind the scenes. The fast path is lightweight and direct, making it useful for quick calls, while the regular path provides more features, error handling, and flexibility.

For most applications, the regular path is the safer and more practical option, but knowing about the fast path can help when you need maximum performance for specific cases.

Before making changes, always measure. Use tools like EXPLAIN ANALYZE or pg_stat_statements to see where time is being spent. That way, you’ll know whether switching execution paths will really make a difference.