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QUESTION NO: 1
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an Apache Pig table named Sales in Apache HCatalog.
You need to make the data in the table accessible from Apache Pig.
Solution: You use the following script.
Does this meet the goal?
A. Yes
B. No
Answer: B
Explanation:
References: https://hortonworks.com/hadoop-tutorial/how-to-use-hcatalog-basic-pig-hive- commands/

QUESTION NO: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are building a security tracking solution in Apache Kafka to parse security logs. The security logs record an entry each time a user attempts to access an application. Each log entry contains the IP address used to make the attempt and the country from which the attempt originated.
You need to receive notifications when an IP address from outside of the United States is used to access the application.
Solution: Create two new consumers. Create a file import process to send messages. Start the producer.
Does this meet the goal?
A. Yes
B. No
Answer: B

QUESTION NO: 3
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training dat
a. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of
Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure HDInsight cluster types for the various tasks associated to the processing pipeline.
You need to meet the following stream analytics requirements:
Send tuples to bolts in a random, round-robin sequence.
Send tuples to a bolt based on one or more fields in the tuple.
Which type of stream grouping should you use for each requirement? To answer, drag the appropriate grouping types to the correct requirements. Each grouping type may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
References: https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.6.1/bk_storm-component- guide/content/storm-stream-groupings.html

QUESTION NO: 4
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 need to deploy an HDInsight cluster that will have a custom Apache Ambari configuration. The cluster will be joined to a domain and must perform the following:
Fast data analytics and cluster computing by using in-memory processing Interactive queries and micro-batch stream processing What should you do?
A. Use an Azure PowerShell script to create and configure a premium HDInsight cluster. Specify
Apache Hadoop as the cluster type and use Linux as the operating system.
B. Use the Azure portal to create a standard HDInsight cluster. Specify Apache Spark as the cluster type and use Linux as the operating system.
C. Use an Azure PowerShell script to create a standard HDInsight cluster. Specify Apache HBase as the cluster type and use Windows as the operating system.
D. Use an Azure PowerShell script to create a standard HDInsight cluster. Specify Apache Storm as the cluster type and use Windows as the operating system.
E. Use an Azure PowerShell script to create a premium HDInsight cluster. Specify Apache HBase as the cluster type and use Linux as the operating system.
F. Use an Azure portal to create a standard HDInsight cluster. Specify Apache Interactive Hive as the cluster type and use Linux as the operating system.
G. Use an Azure portal to create a standard HDInsight cluster. Specify Apache HBase as the cluster type and use Linux as the operating system.
Answer: C
Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-introduction

QUESTION NO: 5
You have an Azure HDlnsight cluster.
You need to build a solution to ingest real-time streaming data into nonrelational distributed database.
What should you use to build the solution?
A. Apatite Hive and Apache Kafka
B. Spark and Phoenix
C. Apache Storm and Apache HBase
D. Apache Pig and Apache HCatalog
Answer: C

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Updated: May 27, 2022