This document describes how to install TDengine in a Docker container and perform queries and inserts.
- The easiest way to explore TDengine is through TDengine Cloud.
- To get started with TDengine in a non-containerized environment, see Quick Install from Package.
- If you want to view the source code, build TDengine yourself, or contribute to the project, see the TDengine GitHub repository.
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:184.108.40.206
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:
Enter the container and open the
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:
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
d9999. Each table has 10,000 rows and each row has four columns:
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
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
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
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
SELECT COUNT(*) FROM test.meters WHERE location = "California.SanFrancisco";
Query the average, maximum, and minimum values of all rows whose
groupId tag is
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.
For more information about deploying TDengine in a Docker environment, see Using TDengine in Docker.