# Preloading

# Premise

At the core of preloading is the desire to reduce the amount of times Botanist generates n + 1 queries. Many solutions exist to approach this problem, the most common in GraphQL being DataLoader (opens new window). Botanist does not contain a full re-implementation of DataLoader, but does make significant efforts to avoid runaway n + 1 query creation.

# The n + 1 Problem

Imagine the following hypothetical query:

query {
    heros(...) {
        enemies {

A fairly typical nested query by all accounts. A naive approach to loading the required data might yield queries looking like:

SELECT id, first_name FROM heros WHERE id IN (1, 2, 3, 4, 5);
SELECT id, first_name FROM enemies WHERE id = 1;
SELECT id, first_name FROM enemies WHERE id = 2;
SELECT id, first_name FROM enemies WHERE id = 3;
SELECT id, first_name FROM enemies WHERE id = 4;
SELECT id, first_name FROM enemies WHERE id = 5;

While not particularly problematic at a small scale, as we increase the number of heros we query for or begin requesting additional nested data from our enemies, the number of queries begins to grow exponentially. At the moment, for every new hero we end up with a new SQL query.

# Preloading

To avoid the above case, when Botanist loads the query above it will bulk preload descendant models before their individual resolvers run. The loading process looks something like:

  1. Load all Heros using a bulk query (like the first line in the above example). This happens any time we use a bulk resolver and doesn't rely on any special preloading logic.
  2. Inspect the Juniper LookAheadSelection (opens new window) to determine what fields are being queried on these Heros.
    • If these fields are plain fields (i.e they map to columns in the underlying database), do nothing as they should already have been loaded in the first query.
    • If these fields are behind HasOne or HasMany relationships, take note of the primary key(s) being requested.
  3. Load all of the newly discovered primary keys in bulk (per given type). In the above example, this consolidates all enemies queries into one query utilizing IN.
  4. Cache these 'preloaded' models on their parent models (stored in 'hidden' fields of type Option<T> or Option<Vec<T>>).
  5. Rinse and repeat. Attempt this process on all of the models that were just preloaded, continuing until there are no more descendant models with children to preload.

Once preloading is finished, when a field that was preloaded is resolved, we return the model loaded during preloading instead of performing a new query. This solves most, but not all n + 1 query issues. In general, it provides satisfactory performance for my current use.