@convex-dev/geospatial/dist/component/lib/approximateCounter.js

A geospatial index for Convex

import { xxHash32 } from "./xxhash.js";
// We assume that (_id, key) is globally unique, so we can implement a probabilistic counter
// by incrementing and decrementing whenever `hash(_id + key) % SAMPLING_RATE == 0`. This has
// a few nice properties:
// - We uniformly sample across the increments/decrements of each key, not the keys themselves.
//   So, many concurrent increments and decrements to the same key won't contend.
// - The counter never goes negative, since we use a deterministic hash.
export const SAMPLING_RATE = 1024;
export async function increment(ctx, _id, key) {
    if (xxHash32(_id + key) % SAMPLING_RATE !== 0) {
        return;
    }
    const existing = await ctx.db
        .query("approximateCounters")
        .withIndex("key", (q) => q.eq("key", key))
        .first();
    if (existing) {
        await ctx.db.patch(existing._id, { count: existing.count + 1 });
    }
    else {
        await ctx.db.insert("approximateCounters", { key, count: 1 });
    }
}
export async function decrement(ctx, _id, key) {
    if (xxHash32(_id + key) % SAMPLING_RATE !== 0) {
        return;
    }
    const existing = await ctx.db
        .query("approximateCounters")
        .withIndex("key", (q) => q.eq("key", key))
        .first();
    if (!existing || existing.count === 0) {
        throw new Error(`Invariant failed: Missing counter for key ${key}`);
    }
    if (existing.count === 1) {
        await ctx.db.delete(existing._id);
    }
    else {
        await ctx.db.patch(existing._id, { count: existing.count - 1 });
    }
}
export async function estimateCount(ctx, key) {
    const existing = await ctx.db
        .query("approximateCounters")
        .withIndex("key", (q) => q.eq("key", key))
        .first();
    const count = existing?.count ?? 0;
    // Break ties between keys by their xxhash.
    return count * SAMPLING_RATE + (xxHash32(key) % SAMPLING_RATE);
}
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