alasarr

const { Pool } = require('pg');

const N_REQUESTS = 32; 
const CONCURRENCY = 32;


// Replace these with your Redshift cluster details
const config = {
  user: 'XXXX',
  host: 'XXX',

alasarr

const fetch = require('node-fetch')
const tilebelt = require('@mapbox/tilebelt')

const accessToken = ''
const projectId = 'carto-dev-data'

const url = `https://bigquery.googleapis.com/bigquery/v2/projects/${projectId}/queries`

async function runRequest (query) {
  const body = {

alasarr

Create an API using CARTO as a backend

Imagine you're going to build a backend to analyze the air quality of a region in Madrid.

You have the following two public datasets in BigQuery ready to be consumed:

• cartodb-gcp-backend-data-team.code_test.airquality_stations. It has the info of the airquality stations and its location.

• cartodb-gcp-backend-data-team.code_test.airquality_measurements. Measurements of each_station:

• timeinstant: time of the observation.

alasarr

## 

create or replace table `cartodb-on-gcp-backend-team.deckgl_summit.pharmacies` cluster by geom as 
select * from carto-demo-data.demo_tables.osm_pois_usa where subgroup_name='Pharmacy'

create or replace table `cartodb-on-gcp-backend-team.deckgl_summit.pharmacies_aoi` cluster by geom as 
select * except (geom),st_buffer(geom, 2000) as geom 

alasarr

----
-- BIGQUERY
---

-- Switzerland
create table carto-dev-data.public.derived_spatialfeatures_che_h3int_res8_v1_yearly_v2
cluster by h3
as 
select cast(concat('0x', h3) as int64) as h3, * except (h3)
from carto-dev-data.public.derived_spatialfeatures_che_h3res8_v1_yearly_v2;

alasarr

{
  "version": 8,
  "name": "Dark Matter",
  "metadata": {
    "maputnik:renderer": "mbgljs"
  },
  "sources": {
    "carto": {
      "type": "vector",
      "url": "https://tiles.basemaps.cartocdn.com/vector/carto.streets/v1/tiles.json"

alasarr

-- Switzerland
create table carto-dev-data.public.derived_spatialfeatures_che_h3res10_v1_yearly_v2_interpolated cluster by h3 
as 
with q as (
  select `carto-un`.carto.H3_TOCHILDREN(h3, 10) as h3_children,* except(h3)
   from `carto-dev-data.public.derived_spatialfeatures_che_h3res8_v1_yearly_v2` 
)
select h3, population/pow(7,2) as population, female/pow(7,2) as female, male/pow(7,2) as male
from q, unnest(q.h3_children) as h3;

alasarr

alasarr

zoom_level	tolerance (m)	tolerance (deg)

      0 |  78271.516953125 | 0.703124999902124
      1 | 39135.7584765625 | 0.351562499951062
      2 | 19567.8792382812 | 0.175781249975531
      3 | 9783.93961914062 | 0.0878906249877655
      4 | 4891.96980957031 | 0.0439453124938827
      5 | 2445.98490478516 | 0.0219726562469414
      6 | 1222.99245239258 | 0.0109863281234707

7 | 611.496226196289 | 0.00549316406173534

alasarr

{
  "tilejson":"2.2.0",
  "tiles":["https://cartocdn-gusc-a.global.ssl.fastly.net/cartovl/api/v1/map/be2b5a9267b5c73a91ba17d11728d756:1560342716956/{z}/{x}/{y}.mvt?api_key=default_public"],
  "minzoom": 3,
  "maxzoom": 7,
  "tilestats":{"layerCount":1,"layers":[{"layer":"429bbc773dcf729a70eaa2897637acd1","count":25648,"adapters":{"aggregation":false,"dates_as_numbers":false}}]}}