โ07-02-2023 07:17 PM
Preparing for databricks eligibility!
Is the content below correct?
"If the queries are running sequentially then scale up (increase the size of the cluster from 2x small to 4x large) If the queries are running concurrently or with many users then scale out (add more clusters. Increase the SQL endpoints scaling range)" |
โ07-04-2023 02:03 AM
Scaling in Databricks involves two aspects: vertical scaling (scale up) and horizontal scaling (scale out).
Vertical Scaling (Scale Up):
Horizontal Scaling (Scale Out):
To summarize:
Keep in mind that the decision to scale up or scale out depends on the specific requirements of your workload, the complexity of your queries, and the concurrency level. It's essential to monitor and analyze the performance of your queries to determine the optimal scaling strategy.
Additionally, when it comes to SQL endpoints, scaling the range refers to adjusting the number of concurrent queries allowed. This can be useful when you have many users running queries simultaneously and need to ensure sufficient resources are available.
It's also worth noting that scaling alone might not be the only solution for improving performance. Optimizing your queries, leveraging query tuning techniques, and utilizing appropriate caching mechanisms can also significantly enhance query execution in Databricks.
โ07-04-2023 02:03 AM
Scaling in Databricks involves two aspects: vertical scaling (scale up) and horizontal scaling (scale out).
Vertical Scaling (Scale Up):
Horizontal Scaling (Scale Out):
To summarize:
Keep in mind that the decision to scale up or scale out depends on the specific requirements of your workload, the complexity of your queries, and the concurrency level. It's essential to monitor and analyze the performance of your queries to determine the optimal scaling strategy.
Additionally, when it comes to SQL endpoints, scaling the range refers to adjusting the number of concurrent queries allowed. This can be useful when you have many users running queries simultaneously and need to ensure sufficient resources are available.
It's also worth noting that scaling alone might not be the only solution for improving performance. Optimizing your queries, leveraging query tuning techniques, and utilizing appropriate caching mechanisms can also significantly enhance query execution in Databricks.
โ07-04-2023 05:27 PM
Can I use the serverless feature for SQL endpoints to troubleshoot query concurrency?
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