Hello there,
I am new to TigerGraph and have been experimenting with its powerful graph analytics capabilities. While I have been able to get some basic queries running; I have started to encounter performance issues as the complexity of my queries increases. I am hoping to get some insights from the community on best practices for optimizing query performance in TigerGraph.
How important is schema design in TigerGraph for query performance? Are there specific design patterns or strategies that I should follow to ensure my graph is optimized for faster queries?
What role does indexing play in TigerGraph? Are there particular indexes that should be created to speed up query execution, and if so, how do I determine which indexes are necessary?
Are there common pitfalls to avoid when writing GSQL queries that can negatively impact performance? For instance, are there certain functions or operations that are known to be particularly resource-intensive?
What tools or methods are available in TigerGraph for profiling and debugging queries? How can I identify the bottlenecks in my query execution?
Does the underlying hardware significantly affect query performance in TigerGraph? If so, what kind of hardware configuration is recommended for optimal performance?
Also, I have gone through this post; http://dev.tigergraph.com/forum/t/changing-configuration-not-changing-query-time-power-bi/ which definitely helped me out a lot.
Are there any case studies or examples available that demonstrate effective optimization techniques in TigerGraph? I would love to see some real-world scenarios where query performance was significantly improved.
Thank you in advance for your help and assistance.
