What should you use to meet each requirement?

HOTSPOT

You are designing an Al solution that must meet the following processing requirements:

Use a parallel processing framework that supports the in-memory processing of high volumes of data.

Use in-memory caching and a columnar storage engine for Apache Hive queries.

What should you use to meet each requirement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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Answer:

Explanation:

Box 1: Apache Spark

Apache Spark is a parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. Apache Spark in Azure HDInsight is the Microsoft implementation of Apache Spark in the cloud.

Box 2: Interactive Query

Interactive Query provides In-memory caching and improved columnar storage engine for Hive queries.

References: https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-overview

https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/interactive-query/apache-interactive-query­get-started