timesacledb 测试demo数据运行

docker run -d --name timescaledb -p 5432:5432 timescale/timescaledb-postgis

https://timescaledata.blob.core.windows.net/datasets/nyc_data.tar.gz

CREATE DATABASE nyc_data;
\c nyc_data
CREATE EXTENSION IF NOT EXISTS timescaledb CASCADE;

psql -U postgres -d nyc_data -h localhost < nyc_data.sql

psql -U postgres -d nyc_data -h localhost -c "\COPY rides FROM nyc_data_rides.csv CSV"

SELECT date_trunc(‘day‘, pickup_datetime) as day, avg(fare_amount) FROM rides WHERE passenger_count > 1 AND pickup_datetime < ‘2016-01-08‘ GROUP BY day ORDER BY day;
SELECT date_trunc(‘day‘, pickup_datetime) as day, COUNT(*) FROM rides GROUP BY day ORDER BY day LIMIT 5;

SELECT time_bucket(‘5 minute‘, pickup_datetime) AS five_min, count(*) FROM rides WHERE pickup_datetime < ‘2016-01-01 02:00‘ GROUP BY five_min ORDER BY five_min;

EXPLAIN SELECT * FROM rides;

CREATE EXTENSION postgis;
ALTER TABLE rides ADD COLUMN pickup_geom geometry(POINT,2163);
ALTER TABLE rides ADD COLUMN dropoff_geom geometry(POINT,2163);

UPDATE rides SET pickup_geom = ST_Transform(ST_SetSRID(ST_MakePoint(pickup_longitude,pickup_latitude),4326),2163);
UPDATE rides SET dropoff_geom = ST_Transform(ST_SetSRID(ST_MakePoint(dropoff_longitude,dropoff_latitude),4326),2163);

SELECT time_bucket(‘30 minutes‘, pickup_datetime) AS thirty_min, COUNT(*) AS near_times_sq
  FROM rides
  WHERE ST_Distance(pickup_geom, ST_Transform(ST_SetSRID(ST_MakePoint(-73.9851,40.7589),4326),2163)) < 400
    AND pickup_datetime < ‘2016-01-01 14:00‘
  GROUP BY thirty_min ORDER BY thirty_min;

总的来说简单，同时具有时序数据库的特点，对于我们来说不需要关注数据多的时候性能的问题，还是很不错的，对于ha 以及集群功能还有待
研究