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This document is intended for:
BAPCORE SPRINGYCORE Administrators
BAPCORE SPRINGYCORE Developers
BAPCORE SPRINGYCORE Architects
This document is a walkthrough to create /and edit an Analytic Ingest Model through the Sprngy UI.
Pre-requisites:
The list of tools required to run/develop in the UI are as follows:
Visual Studio Code (Developers only)
Python 3.8.10
Flask 1.1.4
Node 14.17.6
npm 7.24.1
R 3.6.3
Big Analytixs Sprngy Libraries
Analytic Model
An Analytic model is used to run standard Big Analytixs algorithms/use cases.
There are three aspects to this model:
Create/Edit Analytical Model - This flow is to create (in the case it does not exist) or edit (in the case that it exists) an Analytic Model manually.
Bulk Upload Analytical Model - Big Analytixs gives you the capability to upload a whole model created in a CSV file without manually creating it Sprngy Platform Bulk Uploads UI Documentation
Run Analytic Workload - After creating an Analytic Model, we can run the analytic workload in order to have data processed for that respective Algorithm Run Analytic Workload
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to create processors for a specific analytics. With analytic model one can execute commands on top of the processed data such as getting top 10 sales from a shopping centric use case.
Create an Analytic Model:
Home Screen:
The image below is the Home screen of the UI. From the side menu open ‘Meta Data Configuration' option, then select 'Analytical Model’ option.
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Click on the three lines (pulls up the menu) and click on the “Create/Edit Analytical Model”
Screen0:
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Create/Edit Ingest:
Step 1 -
After clicking on the Analytical Model menu option below screen will be displayed.
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Here from the dropdown list select the module name for which you want to create the Analytic model for, and in the Processor Name dropdown select 'Create New' for a new processor or select existing processor from the drop-down to edit that model. On Submit, an analytic form will be displayed.
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For example, we are choosing ‘BAPRAM’ as the module name.
If editing an existing analytic model, you will be routed directly to the variable grid where you can view, add, edit or delete any of the variables.
Analytic Form:
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analytical model. Then click on create new in case of first time creating that processor else select the processor from the dropdown and click on 'Submit'.
This checks the existence of a analytical model. If there is a previously created or even initiated analytical model then it will bring back that data, if creating analytical model for the very first time then provides blank fields for input.
Step 2 -
After submission, the below screen will be rendered. Here you can provide information regarding the analytical model for given entity.
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Here, whatever processor name you give for the first variable would be fixed for the rest of the variables. You will have to fill out this page. An example of the filled page will look like this:
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The View Icon - This icon navigates you to another screen which displays the details of the particular variable
Edit Icon - The Edit icon gives you the ability to edit that particular variable
Delete Icon - The Delete Icon gives you the ability to delete that particular attribute. A pop-up will appear reconfirming your decision to delete the variable
Once you add all the required variables, click on ‘Final Submit’ to save your model to the HDFS. It is IMPORTANT to remember that you have to click on the “FINAL SUBMIT” button in order for your changes to be permanently saved.
Bulk Upload Analytic Model
There is also one other way to create a analytic model, that is by uploading a CSV file. For this, you are required to have a analytic model .csv file with all the required fields. To directly upload a csv -
Home Screen:
The image below is the Home screen of the UI.
From the side menu open ‘Meta Data Configuration' option, then select 'Analytical Model’ option.
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Step 1 -
After clicking on the Analytical Model menu option below screen will be displayed.
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Select the module and entity for which you want to upload a analytic model. In the file upload option browse or drag and drop the analytic model csv file and click Submit.