QuestDB Docker

Contents

QuestDB Docker#

High performance time series

Superior developer experience with SQL and time series extensions. Speed and reliability to solve ingestion speed bottlenecks.

Demo#

Docker#

docker run -d --name questdb \
  -p 9000:9000 -p 9009:9009 -p 8812:8812 -p 9003:9003 \
  questdb/questdb:7.3.7

http://localhost:9000/

Create my first dataset#

Creating a table#

CREATE TABLE sensors (ID LONG, make STRING, city STRING);

Inserting data#

INSERT INTO sensors
    SELECT
        x ID, --increasing integer
        rnd_str('Eberle', 'Honeywell', 'Omron', 'United Automation', 'RS Pro') make,
        rnd_str('New York', 'Miami', 'Boston', 'Chicago', 'San Francisco') city
    FROM long_sequence(10000) x;

'sensors';

CREATE TABLE readings
AS(
    SELECT
        x ID,
        timestamp_sequence(to_timestamp('2019-10-17T00:00:00', 'yyyy-MM-ddTHH:mm:ss'), rnd_long(1,10,0) * 100000L) ts,
        rnd_double(0)*8 + 15 temp,
        rnd_long(0, 10000, 0) sensorId
    FROM long_sequence(10000000) x)
TIMESTAMP(ts)
PARTITION BY MONTH;

Running queries#

readings;

SELECT count() FROM readings;

SELECT avg(temp) FROM readings;

SELECT *
FROM readings
JOIN(
    SELECT ID sensId, make, city
    FROM sensors)
ON readings.sensorId = sensId;

# Aggregation keyed by city
SELECT city, max(temp)
FROM readings
JOIN(
    SELECT ID sensId, city
    FROM sensors) a
ON readings.sensorId = a.sensId;

# Aggregation by hourly time buckets
SELECT ts, city, make, avg(temp)
FROM readings timestamp(ts)
JOIN
    (SELECT ID sensId, city, make
    FROM sensors
    WHERE city='Miami' AND make='Omron') a
ON readings.sensorId = a.sensId
WHERE ts IN '2019-10-21;1d' -- this is an interval between 2019/10/21 and the next day
SAMPLE BY 1h -- aggregation by hourly time buckets
ALIGN TO CALENDAR; -- align the ts with the start of the hour (hh:00:00)

Deleting tables#

DROP TABLE readings;
DROP TABLE sensors;

Connect#

HTTP REST API#

curl -F data=@data.csv http://localhost:9000/imp

Runtime Environment#

Java 11
C++

Screenshots#

References#