H3 快速入门 (Databricks SQL) - Azure Databricks - Databricks SQL

Databricks SQL 查询与 Databricks Runtime 11.3 LTS 及更高版本

查询 1：验证是否已设置基础数据。请参阅笔记本。
use catalog geospatial_docs;
use database nyc_taxi;
show tables;
-- Verify initial data is setup (see instructions in setup notebook)
-- select format_number(count(*),0) as count from yellow_trip;
-- select * from nyc_zipcode;
查询 2：H3 NYC 邮政编码 - 在分辨率 12 处应用 h3_polyfillash3。
use catalog geospatial_docs;
use database nyc_taxi;
-- drop table if exists nyc_zipcode_h3_12;
create table if not exists nyc_zipcode_h3_12 as (
  select
    explode(h3_polyfillash3(geom_wkt, 12)) as cell,
    zipcode,
    po_name,
    county
    nyc_zipcode
-- optional: zorder by `cell`
optimize nyc_zipcode_h3_12 zorder by (cell);
select
  nyc_zipcode_h3_12;
查询 3：H3 出租车行程 - 在分辨率 12 处应用 h3_longlatash3。
use catalog geospatial_docs;
use database nyc_taxi;
-- drop table if exists yellow_trip_h3_12;
create table if not exists yellow_trip_h3_12 as (
  select
    h3_longlatash3(pickup_longitude, pickup_latitude, 12) as pickup_cell,
    h3_longlatash3(dropoff_longitude, dropoff_latitude, 12) as dropoff_cell,
  except
      rate_code_id,
      store_and_fwd_flag
    yellow_trip
-- optional: zorder by `pickup_cell`
-- optimize yellow_trip_h3_12 zorder by (pickup_cell);
select
  yellow_trip_h3_12
 where pickup_cell is not null;
查询 4：H3 LGA 上车人次 - 从拉瓜迪亚 (LGA) 上车 2500 万人次
use catalog geospatial_docs;
use database nyc_taxi;
create
or replace view lga_pickup_h3_12 as (
  select
  except(cell),
    yellow_trip_h3_12 as s
    inner join nyc_zipcode_h3_12 as t on s.pickup_cell = t.cell
  where
    t.zipcode = '11371'
select
  format_number(count(*), 0) as count
  lga_pickup_h3_12;
-- select
  --   *
  -- from
  --   lga_pickup_h3_12;
查询 5：H3 金融区下车人次 - 金融区的总下车人次为 3400 万
use catalog geospatial_docs;
use database nyc_taxi;
create
or replace view fd_dropoff_h3_12 as (
  select
  except(cell),
    yellow_trip_h3_12 as s
    inner join nyc_zipcode_h3_12 as t on s.dropoff_cell = t.cell
  where
    t.zipcode in ('10004', '10005', '10006', '10007', '10038')
select
  format_number(count(*), 0) as count
  fd_dropoff_h3_12;
-- select * from fd_dropoff_h3_12;
查询 6：H3 LGA-FD - 金融区中从 LGA 上车的下车人次为 82.7 万
use catalog geospatial_docs;
use database nyc_taxi;
create
or replace view lga_fd_dropoff_h3_12 as (
  select
    fd_dropoff_h3_12
  where
    pickup_cell in (
      select
        distinct pickup_cell
        lga_pickup_h3_12
select
  format_number(count(*), 0) as count
  lga_fd_dropoff_h3_12;
-- select * from lga_fd_dropoff_h3_12;
查询 7：按邮政编码计算的 LGA-FD - 按邮政编码和条形图计算金融区下车人次
use catalog geospatial_docs;
use database nyc_taxi;
select
  zipcode,
  count(*) as count
  lga_fd_dropoff_h3_12
group by
  zipcode
order by
  zipcode;
查询 8：按 H3 计算的 LGA-FD - 按 H3 单元格和地图标记可视化效果计算 FD 下车人次
use catalog geospatial_docs;
use database nyc_taxi;
select
  zipcode,
  dropoff_cell,
  h3_centerasgeojson(dropoff_cell) :coordinates [0] as dropoff_centroid_x,
  h3_centerasgeojson(dropoff_cell) :coordinates [1] as dropoff_centroid_y,
  format_number(count(*), 0) as count_disp,
  count(*) as `count`
  lga_fd_dropoff_h3_12
group by
  zipcode,
  dropoff_cell
order by
  zipcode,
  `count` DESC;
快速入门-Python：H3 NYC 出租车（拉瓜迪亚到曼哈顿）
获取笔记本
与 Databricks SQL 中的快速入门结构相同的快速入门结构，在 Notebooks + kepler.gl 中使用 Spark Python 绑定。
快速入门-Scala：H3 NYC 出租车（拉瓜迪亚到曼哈顿）
获取笔记本
与 Databricks SQL 中的快速入门结构相同的快速入门结构，通过 Python 单元格在 Notebooks + kepler.gl 中使用 Spark Scala 绑定。
快速入门-SQL：H3 NYC 出租车（拉瓜迪亚到曼哈顿）
获取笔记本
与 Databricks SQL 中的快速入门结构相同的快速入门结构，通过 Python 单元格在 Notebooks + kepler.gl 中使用 Spark SQL 绑定。