Efficient implementation of faceted search in relational databases

Question

I am trying to implement a Faceted search or tagging with multiple-tag filtering. In the faceted navigation, only not-empty categories are displayed and the number of items

Answer 1

Faceted Search is an analytic problem, which means dimensional design is a good bet. Aka, the thing you search against must be in tabular form.

Include all columns of interest in your analytic table.

Put continuous values into buckets.

Use boolean columns for "many" items like categories or tags, example if there are three tags "foo", "bar", and "baz", you would have three boolean columns.

Use a materialized view to create your analytic table.

Index the crap out of it. Some databases support indexes for this type of application.

Only filter once.

Union your results.

Build pre-aggregated materialized views for common queries.

This article might help you too: https://blog.jooq.org/2017/04/20/how-to-calculate-multiple-aggregate-functions-in-a-single-query/

with filtered as (
    select
    *
    from cars_analytic
    where
        [some search conditions]
)

--for each facet:

select
    'brand' as facet,
    brand as value,
    count(*) as count
from
    filtered
group by
    brand

union

select
    'cool-tag' as facet,
    'cool-tag'as value,
    count(*) as count
from
    filtered
where
    cool_tag

union

...


-- sort at the end
order by
    facet,
    count desc,
    value

100,000 records with 5 facets in ~ 150 ms