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Quick Install on Docker

This document describes how to install TDengine in a Docker container and perform queries and inserts.

Run TDengine

If Docker is already installed on your computer, pull the latest TDengine Docker container image:

docker pull tdengine/tdengine:latest

Or the container image of specific version:

docker pull tdengine/tdengine:

And then run the following command:

docker run -d -p 6030:6030 -p 6041:6041 -p 6043-6049:6043-6049 -p 6043-6049:6043-6049/udp tdengine/tdengine

Note that TDengine Server 3.0 uses TCP port 6030. Port 6041 is used by taosAdapter for the REST API service. Ports 6043 through 6049 are used by taosAdapter for other connectors. You can open these ports as needed.

Run the following command to ensure that your container is running:

docker ps

Enter the container and open the bash shell:

docker exec -it <container name> bash

You can now access TDengine or run other Linux commands.

Note: For information about installing docker, see the official documentation.

Open the TDengine CLI

On the container, run the following command to open the TDengine CLI:

$ taos


Test data insert performance

After your TDengine Server is running normally, you can run the taosBenchmark utility to test its performance:

Start TDengine service and execute taosBenchmark (formerly named taosdemo) in a terminal.


This command creates the meters supertable in the test database. In the meters supertable, it then creates 10,000 subtables named d0 to d9999. Each table has 10,000 rows and each row has four columns: ts, current, voltage, and phase. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a groupId tag from 1 to 10 and a location tag of either California.Campbell, California.Cupertino, California.LosAngeles, California.MountainView, California.PaloAlto, California.SanDiego, California.SanFrancisco, California.SanJose, California.SantaClara or California.Sunnyvale.

The taosBenchmark command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in ten to twenty seconds.

You can customize the test deployment that taosBenchmark creates by specifying command-line parameters. For information about command-line parameters, run the taosBenchmark --help command. For more information about taosBenchmark, see taosBenchmark.

Test data query performance

After using taosBenchmark to create your test deployment, you can run queries in the TDengine CLI to test its performance:

From the TDengine CLI (taos) query the number of rows in the meters supertable:

SELECT COUNT(*) FROM test.meters;

Query the average, maximum, and minimum values of all 100 million rows of data:

SELECT AVG(current), MAX(voltage), MIN(phase) FROM test.meters;

Query the number of rows whose location tag is California.SanFrancisco:

SELECT COUNT(*) FROM test.meters WHERE location = "California.SanFrancisco";

Query the average, maximum, and minimum values of all rows whose groupId tag is 10:

SELECT AVG(current), MAX(voltage), MIN(phase) FROM test.meters WHERE groupId = 10;

Query the average, maximum, and minimum values for table d10 in 10 second intervals:

SELECT FIRST(ts), AVG(current), MAX(voltage), MIN(phase) FROM test.d10 INTERVAL(10s);

In the query above you are selecting the first timestamp (ts) in the interval, another way of selecting this would be \_wstart which will give the start of the time window. For more information about windowed queries, see Time-Series Extensions.

Additional Information

For more information about deploying TDengine in a Docker environment, see Using TDengine in Docker.