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NEW QUESTION: 1
What are the main camera lens parameters? (Multiple choice)
A. Field of view
B. Resolution
C. Focal length
D. Aperture
Answer: A,B,C,D

NEW QUESTION: 2
You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to collect, process, and maintain data. The analytical data store performs poorly.
You must implement a solution that meets the following requirements:
Provide data warehousing
Reduce ongoing management activities
Deliver SQL query responses in less than one second
You need to create an HDInsight cluster to meet the requirements.
Which type of cluster should you create?
A. Apache Hadoop
B. Apache Spark
C. Apache HBase
D. Interactive Query
Answer: B
Explanation:
Lambda Architecture with Azure:
Azure offers you a combination of following technologies to accelerate real-time big data analytics:
Azure Cosmos DB, a globally distributed and multi-model database service.
Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications.
Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process.
The Spark to Azure Cosmos DB Connector

Note: Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing and stream processing methods, and minimizing the latency involved in querying big data.
References:
https://sqlwithmanoj.com/2018/02/16/what-is-lambda-architecture-and-what-azure-offers-with-its-new-cosmos-db/

NEW QUESTION: 3
You plan to perform batch processing in Azure Databricks once daily.
Which type of Databricks cluster should you use?
A. interactive
B. High Concurrency
C. job
Answer: C
Explanation:
Explanation
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.
Note: 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.
References:
https://docs.databricks.com/administration-guide/cloud-configurations/aws/cmbp.html#scenario-3-scheduledba

NEW QUESTION: 4

A. Option D
B. Option C
C. Option E
D. Option B
E. Option A
Answer: B

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