Boosting Erlang: Optimizing Key Comparisons

Understanding the Challenge: Optimizing Erlang Comparisons

Hey guys, let's dive into some potential performance improvements in Erlang, specifically within the leveled project. We're going to focus on the leveled_sst file generation, a CPU-intensive process. The core of this issue lies within the leveled_sst:form_slot/7 function. This function is responsible for building slots, which can hold up to 128 or 256 keys depending on the type of slot. The function uses leveled_sst:key_dominates/3 to compare keys. It's a pretty critical function because it decides the order of keys within these slots. Think of it like sorting ingredients before you start cooking! There was a recent forum discussion about optimizing comparisons within data structures. This highlighted that these comparisons, although individually fast, are called a lot. The aim here is to reduce the time spent in these functions. Improving this can lead to significant overall performance gains, especially during heavy load scenarios.

The process involves comparing keys from two lists to determine the next key to add to a slot. The decision is made by comparing which key at the head of the list is '<' than the other. Sounds simple enough, right? But here's where it gets interesting – and where the optimization opportunities lie. It's not always a straightforward comparison. First off, what happens when keys are equal? That's where the Sequence Number (SQN) comes in. The key with the bigger SQN 'wins'. Also, consider what happens if the merge is happening into the basement. In this scenario, keys with expiry times (and tombstones) need to be potentially reaped. It adds a layer of complexity. Then there's the slot type. All slots begin as no_lookup. However, as soon as a key that isn’t an ?IDX key is encountered, it needs to become a lookup slot, which have a smaller size. This change adds an extra step. And the first key added to the slot has to be returned as the first key along with the slot. This means that optimizing these functions can translate directly into improvements in how fast these data structures are built.

So, where's the problem? The Erlang profiler shows that leveled_sst:key_dominates/3, leveled_sst:form_slot/7, and leveled_codec:to_lookup/1 are called very frequently. While each call might be quick, the sheer volume of calls adds up, eating into the overall performance. The profiler data from the original text confirms that these functions have a considerable impact on CPU usage. This is a classic case of optimizing hot spots – those frequently called functions that take up a significant portion of the execution time. Addressing these bottlenecks can lead to more efficient and faster data processing.

Deep Dive: Analyzing the Bottlenecks

Now, let's get our hands dirty and really dig into the problem. Examining the profile data, we can see that leveled_sst:key_dominates/3 and leveled_sst:form_slot/7 are the main culprits. These functions are called millions of times. The cost per call seems small, but multiplied by such a high frequency, their combined cost is substantial. The leveled_codec:to_lookup/1 function is also worth looking at, given that it is only used by form_slot.

Let's break down the key functions. leveled_sst:key_dominates/3 probably handles the comparison logic. This is where we decide which key