To identify the top users consuming compute resources, a data engineering team needs to monitor usage within their Databricks workspace for better resource utilization and cost control.
The team decided to use Databricks system tables, available under the System catalog in Unity Catalog, to gain detailed visibility into workspace activity. Which SQL query should the team run from the System catalog to achieve this?

• A.SELECT sku_name,
  identity_metadata.created_by AS user_email,
  COUNT(usage_quantity) AS total_dbus
  FROM system.billing.usage
  GROUP BY user_email, sku_name
  ORDER BY total_dbus DESC
  LIMIT 10
• B.SELECT identity_metadata.run_as AS user_email,
  SUM(usage_quantity) AS total_dbus
  FROM system.billing.usage
  GROUP BY user_email
  ORDER BY total_dbus DESC
  LIMIT 10
• C.SELECT sku_name,
  identity_metadata.created_by AS user_email,
  SUM(usage_quantity * usage_unit) AS total_dbus
  FROM system.billing.usage
  GROUP BY user_email, sku_name
  ORDER BY total_dbus DESC
  LIMIT 10
• D.SELECT sku_name,
  usage_metadata.run_name AS user_email,
  SUM(usage_quantity) AS total_dbus
  FROM system.billing.usage
  GROUP BY user_email, sku_name
  ORDER BY total_dbus DESC
  LIMIT 10

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A production cluster has 3 executor nodes and uses the same virtual machine type for the driver and executor.
When evaluating the Ganglia Metrics for this cluster, which indicator would signal a bottleneck caused by code executing on the driver?

• A.The five Minute Load Average remains consistent/flat
• B.Bytes Received never exceeds 80 million bytes per second
• C.Total Disk Space remains constant
• D.Network I/O never spikes
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• E.Overall cluster CPU utilization is around 25%

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A distributed team of data analysts share computing resources on an interactive cluster with autoscaling configured. In order to better manage costs and query throughput, the workspace administrator is hoping to evaluate whether cluster upscaling is caused by many concurrent users or resource-intensive queries.
In which location can one review the timeline for cluster resizing events?

• A.Workspace audit logs
• B.Driver's log file
• C.Ganglia
• D.Cluster Event Log
• E.Executor's log file

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Which statement describes the correct use of pyspark.sql.functions.broadcast?

• A.It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.
• B.It marks a column as small enough to store in memory on all executors, allowing a broadcast join.
• C.It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.
• D.It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.
• E.It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.

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Each configuration below is identical to the extent that each cluster has 400 GB total of RAM 160 total cores and only one Executor per VM.
Given an extremely long-running job for which completion must be guaranteed, which cluster configuration will be able to guarantee completion of the job in light of one or more VM failures?

• A.- Total VMs: 2
  - 200 GB per Executor
  - 80 Cores / Executor
• B.- Total VMs: 4
  - 100 GB per Executor
  - 40 Cores / Executor
• C.- Total VMs: 8
  - 50 GB per Executor
  - 20 Cores / Executor
• D.- Total VMs: 16
  - 25 GB per Executor
  - 10 Cores / Executor
• E.- Total VMs: 1
  - 400 GB per Executor
  - 160 Cores/Executor

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