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You plan to perform batch processing in Azure Databricks once daily. Which type of Databricks cluster should you use?
High Concurrency
automated
interactive

automated

Explanation:
Azure Databricks has two types of clusters: interactive and automated. You use interactive
clusters to analyze data collaboratively with interactive notebooks. You use automated
clusters to run fast and robust automated jobs.
Example: Scheduled batch workloads (data engineers running ETL jobs)
This scenario involves running batch job JARs and notebooks on a regular cadence
through the Databricks platform.
The suggested best practice is to launch a new cluster for each run of critical jobs. This
helps avoid any issues (failures, missing SLA, and so on) due to an existing workload
(noisy neighbor) on a shared cluster.
Reference:
https://docs.databricks.com/administration-guide/cloudconfigurations/
aws/cmbp.html#scenario-3-scheduled-batch-workloads-data-engineersrunning-
etl-jobs

You have the following Azure Stream Analytics query.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are designing an Azure Stream Analytics solution that will analyze Twitter data. You need to count the tweets in each 10-second window. The solution must ensure that each tweet is counted only once. Solution: You use a session window that uses a timeout size of 10 seconds. Does this meet the goal?
Yes
No

No

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