Google Cloud Functions are serverless services that respond to events, such as data coming from our device. We are now going to set up a Cloud Function to extract the data sent by the device, process it immediately, and store it in the central data storage:

1. From the Google Cloud Console's left-hand menu, click on Cloud Functions and then Enable API:

2. Once it is enabled, we can click on the Create function section.

3. We can then define the name of our function as iiot-book-function-1 and the memory allocated as 128 MB. The trigger is Cloud Pub/Sub and the topic is signals, which we created a few paragraphs prior on the Building the devices registry section:

4. Under the source code section of the inline editor on the index.js tab, we can copy and paste the following code:

// needs npm install --save @google-cloud/bigtable
// Imports the Google Cloud client library
const Bigtable = require('@google-cloud/bigtable');

// The name of the Cloud Bigtable instance
const INSTANCE_NAME = 'iiot-book-data';
const PROJECT_NAME = 'iiot-book'; //replace with iiot-book-local for simulation
// The name of the Cloud Bigtable table
const TABLE_NAME = 'iiot-book-signals';
const COLUMN_FAMILY_ID='signal1';
const COLUMN_QUALIFIER='value';

var bigtableOptions = {
  projectId: PROJECT_NAME,
};

// Create a Bigtable client
const bigtable = new Bigtable(bigtableOptions);

// Connect to an existing instance:my-bigtable-instance
const instance = bigtable.instance(INSTANCE_NAME);

// Connect to an existing table:my-table
const table = instance.table(TABLE_NAME);

exports.helloPubSub = (event, callback) => {
  const pubsubMessage = event.data;

  const str = Buffer.from(pubsubMessage.data, 'base64').toString();
  console.log(str);

  const data= str.split(',');
  console.log({
      'device': data[0],
      'tag': data[1],
      'value': data[2],
      'ts': data[3], 
      'quality': data[4]

    });

  const deviceId=data[0];
  const tag=data[1];
  const value=data[2];
  const timestamp = data[3];

    try {

    const tsarray = [deviceId +"#"+ timestamp];
    const rowsToInsert = tsarray.map((ts, index) => ({
      key: `${ts}`,
      data: {
        [tag]: {
          [COLUMN_QUALIFIER]: {
            value: value
          },
        },
      },
    }));
    await table.insert(rowsToInsert);
} catch (err) {
    console.error(`Error inserting data:`, err);
    callback(); //DONE WITH ERROR
  }
  
};

5. Under the source code section on the package.json tab, we can copy and paste the following code:

{
  "name": "sample-pubsub",
  "version": "0.0.1",
  "dependencies": {
    "@google-cloud/bigtable" : "^1.0.0"
  }
}

The purpose of this code is to parse our MQTT message and to store it in Google Bigtable. We can now run our example.