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You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data

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. Interactive Query
B. Apache Hadoop
C. Apache HBase

D. Apache Spark

Explanation:
Lambda Architecture with Azure:
Azure offers you a combination of following technologies to accelerate real-time big data analytics:
1. Azure Cosmos DB, a globally distributed and multi-model database service.
2. Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications.
3. Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process.
4. 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/

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