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NEW QUESTION 26
What is the purpose of gold layer in Multi hop architecture?

A. Preserves grain of original data, without any aggregationsB. Eliminate duplicate recordsC. Data quality checks and schema enforcementD. Optimized query performance for business-critical dataE. Optimizes ETL throughput and analytic query performance

Answer: D

Explanation:
Explanation
Medallion Architecture - Databricks
Gold Layer:
1. Powers Ml applications, reporting, dashboards, ad hoc analytics
2. Refined views of data, typically with aggregations
3. Reduces strain on production systems
4. Optimizes query performance for business-critical data
Exam focus: Please review the below image and understand the role of each layer(bronze, silver, gold) in medallion architecture, you will see varying questions targeting each layer and its purpose.
Sorry I had to add the watermark some people in Udemy are copying my content.

 

NEW QUESTION 27
Which of the following locations in the Databricks product architecture hosts the notebooks and jobs?

A. JDBC data sourceB. Databricks FilesystemC. Data planeD. Databricks web applicationE. Control plane

Answer: E

Explanation:
Explanation
The answer is Control Pane,
Databricks operates most of its services out of a control plane and a data plane, please note serverless features like SQL Endpoint and DLT compute use shared compute in Control pane.
Control Plane: Stored in Databricks Cloud Account
*The control plane includes the backend services that Databricks manages in its own Azure account. Notebook commands and many other workspace configurations are stored in the control plane and encrypted at rest.
Data Plane: Stored in Customer Cloud Account
*The data plane is managed by your Azure account and is where your data resides. This is also where data is processed. You can use Azure Databricks connectors so that your clusters can connect to external data sources outside of your Azure account to ingest data or for storage.
Timeline Description automatically generated

 

NEW QUESTION 28
You had AUTO LOADER to process millions of files a day and noticed slowness in load process, so you scaled up the Databricks cluster but realized the performance of the Auto loader is still not improving, what is the best way to resolve this.

A. Merge files to one large fileB. Increase the maxFilesPerTrigger option to a sufficiently high numberC. Copy the data from cloud storage to local disk on the cluster for faster accessD. Setup a second AUTO LOADER process to process the dataE. AUTO LOADER is not suitable to process millions of files a day

Answer: B

Explanation:
Explanation
The default value of maxFilesPerTrigger is 1000 it can be increased to a much higher number but will require a much larger compute to process.
Graphical user interface, text, application, email Description automatically generated

https://docs.databricks.com/ingestion/auto-loader/options.html

 

NEW QUESTION 29
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