Move Raw Imagery to the Cloud + Use Cloud Image Formats {MRF & COG}
Generalize Features When Possible
Use Materialized | Index SQL Views
SELECT
st_simplify(st_transform(or_parcels.crook_co_parcels.geom, 2992), 1.0::double precision) AS GEOM,
or_parcels.crook_co_parcels.id AS OBJECTID,
or_parcels.crook_co_parcels.taxlot as TAXLOT
FROM or_parcels.crook_co_parcels
WHERE ST_Area(geom) > 10000 limit 500;
Use Generalization in Tandem with Scale Dependency {Nested Layers}
Top Five {opinionated}:
Trim Down Queries - Scale Dependent & Minimum SQL
Move Raw Imagery to the Cloud + Use Cloud Image Formats {MRF & COG}
CREATE MATERIALIZED VIEW washington_land.vw_washington_taxlots
AS
SELECT uuid_generate_v4() AS objectid,
st_transform(asotin_taxlots.geom, 2927) AS geom,
asotin_taxlots.parcel_id AS pin
FROM washington_land.asotin_taxlots;
Works well for data that needs to be populated/hydrated at an interval (i.e. daily | weekly)
Things That Helped Me:
Docker Images With Data & DBs
Be Comfortable with SQL {EXPLAIN}
Test On Minimal Hardare
Synology NAS Device(s)
Our Challenge
1. Know The Performance Baseline of Your Data
2. Fast Maps = {Happy Apps | Happy Users}
I Would Love To Hear Your Performance Tricks - Thank You