Problems with Big Data Solutions and Databricks- Any advice?

[juliemoore]

Hello everyone,

I am currently facing several challenges related to big data solutions, particularly with the Databricks. As many of you may know, Databricks is a powerful platform for data engineering and analytics, but I have encountered some significant performance issues that are hindering my workflow.

Specifically, I have noticed that data processing tasks tend to slow down considerably, especially when working with large datasets. This has resulted in longer run times for ETL (Extract, Transform, Load) jobs and delayed insights, which is critical for our decision-making processes. Additionally, integrating Databricks with other tools in our data pipeline has been somewhat cumbersome, leading to further complications.

I am reaching out to see if anyone else has experienced similar difficulties with Databricks. If so, what steps have you taken to troubleshoot these performance issues? Are there any best practices or optimization techniques that have worked for you in enhancing the efficiency of Databricks?

Any advice or insights would be greatly appreciated as we strive to improve our big data solutions and get the most out of the Databricks platform. 

Thank you for your help!

[gchandra]

Your problem statement is too generic. If your company is facing this, you can reach out to your SA; they will help you. If it's a personal project, then mention what you are trying in detail with cluster size, what you are trying to integrate with, how big your data is, and the list goes on.