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Disclaimer

Big Analytixs Sprngy Platform Azure Engineering Guide

Release 1.0.0.1

Copyright © Big AnalytixsSprngy. All rights reserved.

This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing.

This document is intended for:

  • BAPCORE SPRINGYCORE Administrators

  • BAPCORE SPRINGYCORE Developers

  • BAPCORE SPRINGYCORE Architects

 

This document is a walkthrough to run, re-run and delete workload through Big Analytixs UIcreate and edit an Ingest Model through the Sprngy UI.

Pre-requisites:

The list of tools required to run/develop in the UI are as follows:

  1. Visual Studio Code (Developers only)

  2. Python 3.8.10

  3. Flask 1.1.4

  4. Node 14.17.6

  5. npm 7.24.1

  6. R 3.6.3

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  1. Sprngy Libraries

Run Analytic Workload

On the home screen click on ‘Run Analytic Workload’

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Before Run Analytic Workloads page let’s the user apply analytics on the processed data. For successfully running an analytic workload, it is important to have appropriate data in the required data lakes. By clicking on the run workload from the menu we get to the page below:

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On submit it will display a loader while running the workload in the background and when it is done will display a “SUCCESS” or “FAILURE” response on the screenanalytical model along with the data on the source location specified in the analytical model is required.

Home Screen:

The image below is the Home screen of the UI. From the side menu open 'Workload Management' option, then select 'Run Analytic Workloads’ option.

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Step 1 -

After clicking on the Run Analytic Workload menu option below screen will be displayed.

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On this page, select the module and entity for which you want to run an analytic workload. Select the layer on which the processing is to be applied, that is from RDBMS to RDL(raw data lake)/BDL(business data lake) or from RDL to BDL. You can also select if it is an end of day run or and intra day run.

On the right there is a Model status block, that gives information if the meta, ingest and analytical models are saved to the system.

Here, you can either click 'Submit' to run the workload or create a scheduled workload, by clicking on the scheduled workload toggle, to run at a certain interval.

Scheduled Workloads

For scheduling workloads there are two type - Daily, Custom.

In Daily, the workload will run daily at the given time.

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In Custom type scheduled workload you can select if you wish to run the selected workload every week, every month or every year.

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After selecting the required option click on submit button to initiate the workload processing or schedule creation in scheduled workload case.