When requesting a 280000 row report (approximately 110 MB) using the Compressor, an error occurs when using a 32-bit browser. In a 64-bit browser no error occurs.
We are using a version 2.7.22 (build 12/30/2019 11:55:10) of Flexmonster and java.
We performed the tests on the 32-bit Firefox browser.
Attached is the console log
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Being a client-side component, Flexmonster relies on resources available to the browser, and this affects the loading time and the maximum size of the data that can be handled on every particular machine.
This means that the client computer’s RAM and the browser’s specifications determines how much data can be loaded at once.
In case the 32-bit version of a browser is used, it is possible that it does not provide a possibility to handle such a large data set.
Also, our team has noticed that you were facing problems with the OCSV data type described within the following thread.
It would be useful for us to know whether the issue with 32-bit browsers persists when using a CSV data type instead of the OCSV one.
We are looking forward to hearing from you.
We performed tests with the same amount of data imported to Flexmonster from a CSV file and it worked. The problem occurs when using the compressor.
We are already using the CSV data source type with Compressor, but the problem persists.
We believe this is not a problem with RAM.
Could you simulate a report of this magnitude using the Compressor in a 32-bit browser?
Could you send us an example?
Thank you for your feedback.
As a possible solution, our team would like to kindly suggest considering migration to the custom API data source in order to resolve the problem connected with passing the data through the Data Compressor.
Flexmonster custom data source API is designed for summarized data retrieval from a server to Flexmonster Pivot.
This API will work for projects with their own data access layer, where filtering and aggregation are delegated to a server, and Flexmonster receives ready-to-show data.
A huge benefit of this approach is that you can load already aggregated data and work with much bigger data sources as a result.
More information about custom API data source and sample projects can be found following the link: API data source.
Please let us know if the option described above seems promising to you and if you need more details from our side.