Hi
@James LavierreI will join George and Marius in voting for REST API / TM1py
You will have no issues with 1-2 mb /15- 300k rows files.A few things I would like to bring here from my experience implementing the data upload functionality in
TeamOne Google Sheets add-on:
1. Does the data include any read-only / rule calculated values? Data quality \ error handling
The REST API call will fail if trying to update read-only or rule calculated cells (TeamOne
tm1import task has
checkIfUpdatable option)
You also have to think about error handling
2. Who will be importing data (admins or regular users)?
As you may know for IBM PA Cloud, you have to use non-interactive user accounts to connect through REST API.
So you may have to request additional accounts for users uploading the data
This spring we will be launching a new cloud application that will include TM1py hosting and built-in integrations to read\write data from\to IBM PA, please let me know if you would like to hear more or become an early adopter
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Vlad Didenko
Founder at Succeedium
TeamOne Google Sheets add-on for IBM Planning Analytics / TM1
https://succeedium.com/teamone/------------------------------
Original Message:
Sent: Tue January 17, 2023 11:10 AM
From: James Lavierre
Subject: REST API Data Load into IBM PA
Hi Marius,
Thanks for your response, the concern with tm1py is where to deploy it. As far as I know, IBM doesn't allow deploying 3rd party applications on PA cloud servers not even on rich clients . So I guess that force us to have additional server resides outside of IBM cloud environment that will host the app will be built on TM1py (mainly because those processes will be scheduled to run, and to schedule, you would need an environment).
BR,
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James Lavierre
Original Message:
Sent: Tue January 17, 2023 10:51 AM
From: Marius Wirtz
Subject: REST API Data Load into IBM PA
Hi James,
re 1, IMHO REST is not just a viable approach, but perhaps the preferred choice.
With TM1py updating 20k cells should be below 1 minute.
Updating 300k cells shouldn't take more than a few minutes (of course it always depends on the cube).
The biggest advantage of TM1py/REST is perhaps the features that Python brings to the table compared to Turbo Integrator when it comes to working with data (e.g. pandas) and connectivity (e.g. packages for GSheets, Salesforce, etc.).
Here is a sample of how to connect and write a CSV to a cube in IBM Cloud with TM1py:
write-to-tm1-cloud.pyGitHub | remove preview |
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Disclaimer: I created the TM1py project.
Marius
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Marius Wirtz
Original Message:
Sent: Mon January 16, 2023 02:08 PM
From: James Lavierre
Subject: REST API Data Load into IBM PA
Our customer is evaluating API approach for loading and extracting data from IBM PA cloud. Currently we are loading data through csv files transferred to IBM FTP location. The idea is to switch to REST API based integration.
We are trying to understand;
1. Is it feasible to to use REST api post method to update our sales cubes on a daily basis. Currently 3-4 csv files uploaded every day with avg size 1-2 mb , 15-20k rows maxing 300k rows (once in a while). How would be the performance with REST Api?
2. Is "Cognos command center" the best choice for accessing API basd sources and orchestrating with other TI processes? Can we deploy Cognos command center to the same IBM PA cloud (without additional server) and access external REST Json sources and post it to IBM PA?
Thanks in advance, would be great to hear your experience with REST based data integration on cloud.
BR,
James
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James Lavierre
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#PlanningAnalyticswithWatson