What should you use to meet each requirement?

HOTSPOT
You are designing an AI 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.
Hot Area:

Correct Answer:

Explanation/Reference:
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-query-get-started