Data science team members are using a single cluster to perform data analysis, although cluster size was chosen to handle multiple users and auto-scaling was enabled, the team realized queries are still running slow, what would be the suggested fix for this?

Data science team members are using a single cluster to perform data analysis, although cluster size was chosen to handle multiple users and auto-scaling was enabled, the team realized queries are still running slow, what would be the suggested fix for this?
A . Setup multiple clusters so each team member has their own cluster
B . Disable the auto-scaling feature
C . Use High concurrency mode instead of the standard mode
D . Increase the size of the driver node

Answer: C

Explanation:

The answer is Use High concurrency mode instead of the standard mode, https://docs.databricks.com/clusters/cluster-config-best-practices.html#cluster-mode High Concurrency clusters are ideal for groups of users who need to share resources or run ad-hoc jobs. Databricks recommends enabling autoscaling for High Concurrency clusters.

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