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Create an MQTT to SQL Data Pipeline

At the end of this tutorial, we will see data starting from an MQTT broker and ending in a PostgreSQL table.

We'll use 2 connectors:

The Outbound connector will be using a PostgreSQL database. It will listen to the topic for new records and insert them into a table.

You can use your own PostgreSQL instance, if it can be reached over the internet. But you can still follow along by creating a PostgreSQL database at a hosting service, such as ElephantSQL.

Setup​

Start MQTT Connector​

This connector expects to take json input from the MQTT broker, from an MQTT topic named ag-mqtt-topic. These parameters will be reflected in the final JSON payload that gets produced to the fluvio topic mqtt-topic

MQTT connector config: mqtt.yml

info

All versions are marked with x.y.z. To find the latest version, run:

  • fluvio hub connector list
  • fluvio hub smartmodule list
# mqtt.yml
apiVersion: 0.1.0
meta:
 version: x.y.z
 name: fluvio-mqtt-connector
 type: mqtt-source
 topic: mqtt-topic
 direction: source

mqtt:
 url: "mqtt://test.mosquitto.org/"
 topic: "ag-mqtt-topic"
 timeout:
   secs: 30
   nanos: 0
 payload_output_type: json

Create MQTT connector​

$ fluvio cloud connector create --config mqtt.yml

Install mosquito - MQTT client​

First install mosquito to follow later steps for sending JSON to our test MQTT broker

-> On MacOS, you can install mosquitto with homebrew with the following command:
    brew install mosquitto

Start SQL connector(s)​

You can start one of both of the following connectors

  1. Connector with no transformation
    1. Download SmartModule for example
    2. Example connector config
    3. Start connector
  2. Connector with extra JSON to JSON transformation
    1. Download SmartModules for example
    2. Example connector config
    3. Start connector

SQL Connector with no transformation​

Download json-sql SmartModule​

Example output

$ fluvio hub sm download infinyon/json-sql@x.y.z
downloading infinyon/json-sql@x.y.z to infinyon-json-sql-x.y.z.ipkg
... downloading complete
... checking package
trying connection to fluvio router.dev.infinyon.cloud:9003
... cluster smartmodule install complete
SQL Connector with no transformation config​
# sql.yml
apiVersion: 0.1.0
meta:
 name: fluvio-sql-connector
 type: sql-sink
 version: x.y.z
 topic: mqtt-topic

sql:
 url: "postgres://user:password@db.postgreshost.example/dbname"
transforms:
 - uses: infinyon/json-sql@x.y.z
   with:
     invoke: insert
     mapping:
       table: "topic_message"
       map-columns:
         "device_id":
           json-key: "payload.device.device_id"
           value:
             type: "int"
             default: "0"
             required: true
         "record":
           json-key: "$"
           value:
             type: "jsonb"
             required: true

Start No transformation connector SQL connector

$ fluvio cloud connector create --config sql.yml

Connector with JSON to JSON transformation​

Download the Jolt and Json-Sql SmartModules used by this example connector

Example output

$ fluvio hub sm download infinyon/json-sql@x.y.z
downloading infinyon/json-sql@x.y.z to infinyon-json-sql-x.y.z.ipkg
... downloading complete
... checking package
trying connection to fluvio router.infinyon.cloud:9003
... cluster smartmodule install complete
$ fluvio hub sm download infinyon/jolt@x.y.z
downloading infinyon/jolt@x.y.z to infinyon-jolt-x.y.z.ipkg
... downloading complete
... checking package
trying connection to fluvio router.infinyon.cloud:9003
... cluster smartmodule install complete
Connector with JSON to JSON transformation config​
# sql-chain.yml
apiVersion: 0.1.0
meta:
 name: fluvio-sql-connector-chain
 type: sql-sink
 version: x.y.z
 topic: mqtt-topic

sql:
 url: "postgres://user:password@db.postgreshost.example/dbname"
 rust_log: "sql_sink=INFO,sqlx=WARN"
transforms:
 - uses: infinyon/jolt@x.y.z
   with:
     spec:
       - operation: shift
         spec:
           payload:
             device: "device"
       - operation: default
         spec:
           device:
             type: "mobile"
 - uses: infinyon/json-sql@x.y.z
   with:
     invoke: insert
     mapping:
       table: "topic_message"
       map-columns:
         "device_id":
           json-key: "device.device_id"
           value:
             type: "int"
             default: "0"
             required: true
         "record":
           json-key: "$"
           value:
             type: "jsonb"
             required: true

Start SQL connector with JSON transformation

$ fluvio cloud connector create --config sql-chain.yml

Install pgcli - PostgreSQL client​

Install pgcli to follow the later DB validation steps https://www.pgcli.com

tip

On MacOS, you can install pgcli with homebrew with the following command:

$ brew install pgcli

The actual test​

📋 Using example JSON, this is the sequence of events that will occur

  1. (user) [Publish JSON to MQTT broker][#publish-json-to-mqtt-broker"]
  2. (Inbound MQTT connector) Produce data to fluvio topic mqtt-topic
    1. Produce a transformed JSON object with config parameter data with the name of the MQTT topic embedded
  3. (Outbound SQL connector) Consume the inbound record from topic mqtt-topic
    1. Apply transformations to record (JSON to JSON connector only)
    2. Insert record into DB
  4. (user) [Validate JSON record in PostgreSQL database]
tip

If you are starting with a new database, you will need to create the table before sending messages to MQTT. It is not created automatically.

Table create query

create table topic_message(device_id int, record jsonb);

This is what our input JSON to MQTT looks like

example JSON (formatted)

{
   "device": {
       "device_id": 17,
       "name": "device17"
   }
}

Publish JSON to MQTT broker​

Run the following to send a test JSON message to the demo MQTT broker with mosquito ([Installation steps])

Command:

$ mosquitto_pub -h test.mosquitto.org -t ag-mqtt-topic -m '{"device": {"device_id":17, "name":"device17"}}'

Produced data in topic:

$ fluvio consume mqtt-topic -B
Consuming records from the beginning of topic 'mqtt-topic'
{"mqtt_topic":"ag-mqtt-topic","payload":{"device":{"device_id":17,"name":"device17"}}}

Produced data in topic: Run the following to connect to PostgreSQL DB with pgcli ([Installation steps]

View output in PostgreSQL​

Use pgcli to examine the database.

$ pgcli -U user -h db.postgreshost.example -p 5432 dbname

Check that the JSON from MQTT has been inserted into table

select * from topic_message;

Example output from both connectors

+-----------+-----------------------------------------------------------------------------------------------+
| device_id | record                                                                                        |
|-----------+-----------------------------------------------------------------------------------------------|
| 17        | {"payload": {"device": {"name": "device17", "device_id": 17}}, "mqtt_topic": "ag-mqtt-topic"} |
| 17        | {"device": {"name": "device17", "type": "mobile", "device_id": 17}}                           |
+-----------+-----------------------------------------------------------------------------------------------+
SELECT 2
Time: 0.080s

Output explanation:

In both cases, we’ve used the device_id key in the MQTT JSON as the value in the column of the same name. The first row is from our No Transformation connector. The record data appears unchanged from what we saw in the topic.

Resulting record

{
   "payload": {
       "device": {
           "name": "device17",
           "device_id": 17
       }
   },
   "mqtt_topic": "ag-mqtt-topic"
}

The second row is from our JSON to JSON transformation connector We’ve shifted the topic JSON data, so it more closely resembles the original JSON.

Then we enrich the payload by adding the .device.type key with the value mobile before inserting into the DB

{
   "device": {
       "name": "device17",
       "type": "mobile",
       "device_id": 17
   }
}

Move transformation to MQTT Connector​

  • Transformations in the transforms section of SQL Connector config are deliberately decoupled from connectors. We can move a SmartModule from an Inbound to an Outbound connector and accomplish the same result. The decision depends on the shape of the data you want to store in a topic. For Inbound connectors, the data is transformed before sending to Fluvio topic, while for Outbound, it happens after the data is sent to Fluvio topic but before it is sent to the connector.

Let's try it.

Modify our mqtt.yml config with one transformation that we are moving from the SQL Connector:

# mqtt.yml
apiVersion: 0.1.0
meta:
 version: x.y.z
 name: fluvio-mqtt-connector
 type: mqtt-source
 topic: mqtt-topic
 direction: source

mqtt:
 url: "mqtt://test.mosquitto.org/"
 topic: "ag-mqtt-topic"
 timeout:
   secs: 30
   nanos: 0
 payload_output_type: json

transforms:
 - uses: infinyon/jolt@x.y.z
   with:
     spec:
       - operation: shift
         spec:
           payload:
             device: "device"
       - operation: default
         spec:
           device:
             type: "mobile"

We don’t need this transformation on SQL Connector anymore, remove it from sql-chain.yml file:

# sql-chain.yml
apiVersion: 0.1.0
meta:
 name: fluvio-sql-connector-chain
 type: sql-sink
 version: x.y.z
 topic: mqtt-topic

sql:
 url: "postgres://user:password@db.postgreshost.example/dbname"

transforms:
 - uses: infinyon/json-sql@x.y.z
   with:
     invoke: insert
     mapping:
       table: "topic_message"
       map-columns:
         "device_id":
           json-key: "device.device_id"
           value:
             type: "int"
             default: "0"
             required: true
         "record":
           json-key: "$"
           value:
             type: "jsonb"
             required: true

We need to re-create connectors:

$ fluvio cloud connector delete fluvio-mqtt-connector
$ fluvio cloud connector create --config mqtt.yml

also, we delete one now obsolete SQL connector and re-create another without the transformation that we moved to MQTT:

$ fluvio cloud connector delete fluvio-sql-connector-chain
$ fluvio cloud connector delete fluvio-sql-connector
$ fluvio cloud connector create --config sql-chain.yml

And now, if we execute command:

$ mosquitto_pub -h test.mosquitto.org -t ag-mqtt-topic -m '{"device": {"device_id":17, "name":"device17"}}'

The new record differs from what we saw previously:

$ fluvio consume mqtt-topic -B
Consuming records from the beginning of topic 'mqtt-topic'
{"mqtt_topic":"ag-mqtt-topic","payload":{"device":{"device_id":17,"name":"device17"}}}
{"device":{"device_id":17,"name":"device17","type":"mobile"}}

We can see that the record was transformed before producing to Fluvio cluster.

However, in the database table, the new record equals to the previous one.

+-----------+-----------------------------------------------------------------------------------------------+
| device_id | record                                                                                        |
|-----------+-----------------------------------------------------------------------------------------------|
| 17        | {"payload": {"device": {"name": "device17", "device_id": 17}}, "mqtt_topic": "ag-mqtt-topic"} |
| 17        | {"device": {"name": "device17", "type": "mobile", "device_id": 17}}                           |
| 17        | {"device": {"name": "device17", "type": "mobile", "device_id": 17}}                           |
+-----------+-----------------------------------------------------------------------------------------------+
SELECT 3
Time: 0.080s

Although the final result is the same (the same records will end up in SQL database with the same content), choosing the proper side of a pipeline where transformations should reside may significantly affect performance on high volumes of data.

Conclusion​

After setting up our end-to-end MQTT to SQL scenario, we were able to send JSON data to the MQTT broker and track the data to the PostgreSQL table.

We saw the results for the JSON just being inserted into the table with the json-sql SmartModule.

Using SmartModule chaining with the jolt and json-sql SmartModules, we observed that the resulting JSON was successfully transformed.

We can choose on which side of a pipeline we wanted to transform our data without material impact to the result.