Paytm is an Indian e-commerce payment system and financial technology company. It is currently available in 11 Indian languages and offers online use-cases like mobile recharges, utility bill payments, travel, movies, and events bookings as well as in-store payments at grocery stores, fruits and vegetable shops, restaurants, parking, tolls, pharmacies and educational institutions with the Paytm QR code
After naming the datasource, the configure tab would require the user to provide the Webhook Url.The credentials can be tested if they are valid or not by testing the connection before updating.
Upon selection and naming the data source, a connection URL is generated.
An example of the URL could be:
The user needs to copy this URL and save it for editing later. Post copying, the user can click on create.
Optimising Incremental Ingestion in Paytm Database
Also users can select Yes or No to Optimize Incremental Ingestion. If optimize is Yes, all the datasets will undergo full ingestion on every Sunday or every night. If optimize is No, data will be ingesting incrementally and it never goes under complete ingestion.
Post clicking on create, the user will be redirected to the data set page, wherein the user needs to name the table name, unique key and time column and then click on create.
This will create a table in the warehouse. But, this table will not have any data. Users can push data into this table using the Webhook URL created earlier.
In the URL, the user needs to fill the API details. In order to generate API keys, the user can go to Admin -> Permissions -> Api Keys.
Note: Please note, users with Analyst or Developer roles may not have access to the Admin tab. Please check with Admin for API key and secret.
Once on the Permissions page,the user can click on ‘ API keys’ and then ‘New’ to generate new API keys and secret keys.
Once the API key and secret key is generated, users can edit the Webhook URL and add the API key and secret key to the URL.
Now, User can login to their Paytm account from https://dashboard.paytm.com/. Update the webhook url in Developer Settings -> Webhook URL.
Post url update, users can then schedule the jobs and select the ingestion frequency. It is recommended to set the Autorun frequency of ingestion to real time or every 1 hour. Bigger values of frequency are not recommended for webhook data.
This will enable the user to push data from data sources to Sprinkle.
More datasets can be added, if required and data can be sent to those tables by adding the table name in the webhook url.
For adding a new data set in the same data source, the user can go back to Datasets, click on “Add Datasets”.
After adding the dataset, clicking on Create the user will get redirected to the Ingestion job page. Here the concurrency (number of tables that can run in parallel, a maximum of 7) can be set preferentially before running the job. The status of the job will be updated in the tab below once it’s complete. The jobs can also be set to run automatically by enabling autorun. By default, the frequency is set to every night. Frequency can be changed by clicking on More --> Autorun-->Change Frequency.