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NEW QUESTION 1
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You are implementing a batch processing solution by using Azure HDInsight. You have a table that contains sales data. You plan to implement a query that will return the number of orders by zip code. You need to minimize the execution time of the queries and to maximize the compression level of the resulting data. What should you do?
A. Use a shuffle join in an Apache Hive query that stores the data in a JSON format.
B. Use a broadcast join in an Apache Hive query that stores the data in an ORC format.
C. Increase the number of spark.executor.cores in an Apache Spark job that stores the data in a text format.
D. Increase the number of spark.executor.instances in an Apache Spark job that stores the data in a text format.
E. Decrease the level of parallelism in an Apache Spark job that stores the data in a text format.
F. Use an action in an Apache Oozie workflow that stores the data in a text format.
G. Use an Azure Data Factory linked service that stores the data in Azure Data Lake.
H. Use an Azure Data Factory linked service that stores the data in an Azure DocumentDB database.