Clickstream producer

Danger

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In this project the clickstream data is read from a CSV file. This data represents fifteen days of shopping data gathered from a real online store.

Data published

A subset of this data is then published to the click-data topic:

ip - the IP address of the customer
original_timestamp - the Unix timestamp for the interaction
productId - product ID (the product ID is embedded in the URL for the product viewed)
userAgent - browser details for the client
userId - UUID for the user

This service runs continually, reloading the data from the CSV file. There's also an option (keep_timing) to keep the original timing of the data - this is the default in the ungated experience (the live demo).

Exploring the message format

If you click Topics in the main left-hand navigation you see the topics in the environment:

Click in the Data area to view live data. This takes you into the Quix data explorer. You can then select the stream and parameter data you'd like to explore. You can then view this data in either the Table or Messages view.

If you look at the messages in the Messages view, you'll see data has the following format:

{
  "Epoch": 0,
  "Timestamps": [
    1699973201619326000
  ],
  "NumericValues": {
    "original_timestamp": [
      1331802578
    ]
  },
  "StringValues": {
    "userId": [
      "F6F8B460-4204-4C26-A32C-B93826EDCB99"
    ],
    "ip": [
      "75.85.165.38"
    ],
    "userAgent": [
      "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_8) AppleWebKit/534.52.7 (KHTML, like Gecko) Version/5.1.2 Safari/534.52.7"
    ],
    "productId": [
      "VD55179433"
    ]
  },
  "BinaryValues": {},
  "TagValues": {}
}

The Quix data explorer is a very useful tool for debugging and monitoring your pipeline.

Viewing the deployed application

In the left-hand main navigation, click Deployments to see all the deployed services and jobs in the environment:

Click Clickstream producer to select the deployment. This takes you to an extremely useful screen where you can:

View the status of the deployment (such as CPU, memory usage, and replicas assigned).
See the live logs for the service.
See the topic lineage for the service.
Access Build logs (in case of errors when the service is built).
Access the Messages tab, where you can then see messages associated with the service in real time.

Viewing the application code

There are many ways to view the code for the application (which is then deployed as a job or service). The quickest way from the current screen is to click the area shown:

You'll now be in the code view with the version of the deployed code displayed.

If you review the code, you'll see that the CSV file is read on a background thread, and data published to streams based on the userId:

stream_producer = producer_topic.get_or_create_stream(row['userId'])
stream_producer.timeseries.publish(df_row)

If you keep the original timing of the data, that is respected, although the delays are kept within 0 and 10 seconds. If keep_timing is False then a delay of 200ms is used between publishing data:

if not keep_timing:
    # Don't want to keep the original timing or no timestamp? That's ok, just sleep for 200ms
    time.sleep(0.2)

Feel free to explore the code further.

🏃‍♀️ Next step

Part 3 - Data ingestion