...

This document is a walkthrough to create 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:

...

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

...

Analytic model is defined.

Run Analytic Workload

Run Analytic Workloads page let’s lets the user apply analytics on the processed data. For successfully running an analytic workload, analytical model along with the data on the source location specified in the analytical model is required.

...

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.

In default configuration of Sprngy, Raw Data Lake (RDL) is same as Staging Data Lake (SDL). For advanced enterprise implementations, a Raw Data Lake can be configured to be separate from Staging Data Lake. This is handled through professional services request to Sprngy’s support team.

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

...

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

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

...