Getting Started: Inserting Data


  1. Introduction
  2. Inserting Data
  3. Portals
  4. Exporting Data
  5. SQL
  6. Alerting

Network Commands

In the previous section you inserted data manually using the web interface. Proceed by inserting data in network command format.

Network commands provide a compact syntax to insert both time series data as well as metadata.

command_name field_prefix:[field_name=]field_value

Open the console and send these commands into ATSD.

echo -e "series e:br-1905 m:temperature=25" \
  > /dev/tcp/atsd_hostname/8081
echo -e "entity e:br-1905 t:serial_number=N12002" \
  > /dev/tcp/atsd_hostname/8081

Refresh the Series Statistics page and Entity Editor to verify that the temperature sample is received and the entity tag series_number is set by the database.

You can also insert the same network commands on the Data > Data Entry page for convenience.


While the network commands are optimized for writing data, the REST API provides endpoints to both write and read data by sending HTTP requests in JSON format.

Sending Values at a Specific Time

Open the console and send a single observation with a specific datetime into the Series: Insert endpoint. Replace <username> with your username.

curl https://atsd_hostname:8443/api/v1/series/insert \
  --insecure -w "%{http_code}\n" \
  --user <username> \
  --header "Content-Type: application/json" \
  --data '[{"entity": "br-1905", "metric": "temperature", "data": [{ "d": "2018-06-01T14:00:00Z", "v": 17.0 }]}]'

The payload transmitted to the database is a JSON document containing the series key and an array of datetime:value samples. The array data can contain any number of samples.

  "entity": "br-1905",
  "metric": "temperature",
  "data": [
    { "d": "2018-06-01T14:00:00Z", "v": 17.0 },
    { "d": "2018-06-01T14:05:00Z", "v": 17.5 }

Sending Values at the Current Time

Send a modified version, where the datetime is set to present time using the date -u +"%Y-%m-%dT%H:%M:%SZ" command.

curl https://atsd_hostname:8443/api/v1/series/insert \
  --insecure -w "%{http_code}\n" \
  --user <USER> \
  --header "Content-Type: application/json" \
  --data '[{"entity": "br-1905", "metric": "temperature", "data": [{ "d": "'$(date -u +"%Y-%m-%dT%H:%M:%SZ")'", "v": 19.0 }]}]'

Reload the Series Statistics page and observe new values.

Sending Values Continuously

Replace <username>:<password> with user credentials in the curl command provided below to send random values between 20 and 40 into the database every five seconds.

for i in {1..100}; do \
curl https://atsd_hostname:8443/api/v1/series/insert \
  --insecure -w "%{http_code}\n" \
  --user <username>:<password> \
  --header "Content-Type: application/json" \
  --data '[{"entity": "br-1905", "metric": "temperature", "data": [{ "d": "'$(date -u +"%Y-%m-%dT%H:%M:%SZ")'", "v": '"$RANDOM_TEMPERATURE"' }]}]'; \
sleep 0.5; \

Refer to API Documentation and examples for more information.

CSV Files

CSV is one of the most commonly used tabular formats. Despite widespread use, the format remains non-standardized. ATSD provides a flexible CSV Parser that converts CSV files of any composition into structured database records.

Create a CSV file temperature.csv.

2018-Jun-01 00:00:00,BR-1905,32.5
2018-Jun-01 00:30:00,BR-1905,31.5
2018-Jun-01 01:00:00,BR-1905,30.0
2018-Jun-01 01:30:00,BR-1905,29.0
2018-Jun-01 02:00:00,BR-1905,25.0

Open Data > CSV Parsers and select Import from the split-button located at the bottom of the page.

Attach temperature_parser.xml and import the parser.

Open Data > CSV File Upload, attach the temperature.csv file and process it with the newly created temperature_parser.

Open the CSV Tasks page and check the number of processed rows is 6.

For this basic example, the parser maps file columns to series command fields based on column names specified in the header. The parser performs the following specific actions:

  • date column is mapped to datetime field and parsed with yyyy-MMM-dd HH:mm:ss pattern in UTC time zone which is set explicitly.
  • asset column is mapped to entity field.
  • The remaining columns, including temperature, are automatically classified as metric columns.
date = '2018-Jun-01 00:00:00' -> datetime = '2018-06-01T00:00:00Z'
asset = 'BR-1905'             -> entity = 'br-1905'
temperature = 32.5            -> metric (temperature) = 32.5

Refresh the Series Statistics page to check that the values from the CSV file are present in the database.

Refer to CSV Parser Documentation for more examples.

Continue to Part 3: Portals.