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How to remove chart section to optimize performance

Answered
Rustam asked on September 18, 2024

Subject: Removing Chart Section to Optimize Performance

Flexmonster Support Team,

For our project, the charting functionality is not required. I would like to inquire if there is a way to fully remove or disable the charts section to prevent it from initializing or processing any chart-related calculations.

Given that we are working with large datasets, we are experiencing performance issues during analysis. I believe disabling the chart functionality may help reduce the processing time. Could you please advise if this is possible, and if so, how it can be implemented?

Thank you for your assistance.

Best regards,
Rustam

5 answers

Public
Maksym Diachenko Maksym Diachenko Flexmonster September 18, 2024

Hello, Rustam!

Thank you for reaching out to us.

Please note that Flexmonster does not perform background calculations for charts while the grid layout is displayed. Therefore, there is no need to disable charts in order to improve performance.

Our team would be glad to help you address the performance issues. But we would like to know the following details beforehand:

  • Data source(s) you are using.
  • The volume of data (quantity of columns and rows, file size).
  • Performance metrics, data loading time.

We are looking forward to hearing from you.

Best Regards,
Maksym

Public
Rustam September 19, 2024

Hello Maksym,

Thank you for your prompt response.

Regarding the performance details you requested, here is some additional information:

  • I am using the slice object for data presentation.
  • The dataset contains over 50 columns, with an average of 150,000 to 200,000 rows.
  • The file size ranges from approximately 6 MB to 15 MB.
  • Currently, data loading time is between 5 and 7 seconds for a dataset of 100,000 rows.

Please let me know if you need any further details or clarification to assist in optimizing performance.

Best regards,
Rustam

Public
Maksym Diachenko Maksym Diachenko Flexmonster September 19, 2024

Hello, Rustam!

Thank you for sharing this information with us.

Based on the input regarding the file size, we can determine whether you use a CSV or JSON data source. In our experience, this loading time is expected for the mentioned data volume within typical operational parameters. To provide more accurate assistance, we request the following information:

  1. Which data source type is used (JSON or CSV)?
  2. If you are using JSON, are you using an array of arrays or an array of objects format?
  3. Are you loading files via URL or from a local file system?
  4. Are you using pivot table layout (classic or compact), or a flat layout?

Looking forward to hearing from you.

Best Regards,
Maksym

Public
Rustam September 20, 2024

Hello Maksym,

Thank you for your prompt reply and assistance!

To clarify the points you mentioned:

  • I am using JSON as the data source.
  • The format is an array of objects.
  • The data is being fetched from a URL (an endpoint).
  • I am primarily working with a flat layout.

Please let me know if any additional details would be helpful.

Best regards,
Rustam

Public
Maksym Diachenko Maksym Diachenko Flexmonster September 20, 2024

Hello, Rustam!

Thank you for your reply.

In your case, the performance can be improved by decreasing the loading time via the network. These improvements revolve around decreasing the data file size. We suggest following the following steps:

  • Convert the JSON data to an array of arrays format. This would reduce the file size as the field names would be only present in the first array instead of repeating in each object. Please find the array of arrays data example below:
[
["Color", "Country", "State", "City", "Price", "Quantity"],
["green", "Canada", "Ontario", "Toronto", 174, 22],
["red", "USA", "California", "Los Angeles", 166, 19]
]
  • Use the gzip on your server to compress the data and thus reduce the amount of data sent to the client.

Please let us know if our suggestions have helped you achieve improved results.

Best Regards,
Maksym

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