NEW QUESTION 1
DRAG DROP
You are evaluating the use of Azure HDInsight clusters for various workloads. Which type of HDInsight cluster should you create for each workloads?

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:
https://www.blue-granite.com/blog/how-to-choose-the-right-hdinsight-cluster

NEW QUESTION 2
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

NEW QUESTION 3
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 a consumer and a broker. Create a file import process to send messages.
Run the producer.
Does this meet the goal?

• A. Yes
• B. No

Answer: B

NEW QUESTION 4
HOTSPOT
You install the Microsoft Hive ODBC Driver on a computer that runs Windows 10 and has the 64-bit version of Microsoft Office 2021 installed.
You deploy a new Apache Interactive Hive cluster in Azure HDInsight. The cluster is hosted at myHDICluster.azurehdinsignt.net and contains a Hive table named hivesampletable that has 200,000 rows.
You plan to use HiveQL exclusively for the queries. The queries will return from 6,000 to 10,000 rows 90 percent of the time.
You need to configure a data source to ensure that you can use Microsoft Excel to access the data. The solution must ensure that the Hive queries execute as quickly as possible.
How should you configure the Advanced Options from the Microsoft Hive ODBC Driver DSN Setup dialog box? To answer select the appropriate options in the answer area.
NOTE:
Each correct selection is worth one point.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-connect-excel-hiveodbc-driver

NEW QUESTION 5
You use YARN to manage the resources for a Spark Thrift Server running on a Linux based Apache Spark cluster in Azure HDInsight.
You discover that the cluster does not fully utilize the resources. You want to increase resource allocation. You need to increase the number of executors and the allocation of memory to the Spark Thrift Server driver.
Which two parameters should you modify? Each correct answer presents part of the solution NOTE: Each correct selection is worth one point.

• A. spark.dynamicAllocation.maxExecutors
• B. spark.cores.max
• C. spark.executor.memory
• D. spark_thrift_cmd_opts
• E. spark.executor.instances

Answer: AC

Explanation:
References: https://stackoverflow.com/questions/37871194/how-to-tune-spark-executornumber-cores-and-executor-memory

NEW QUESTION 6
DRAG DROP
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
Start of Repeated Scenario:
You are planning a big data infrastructure by using an Apache Spark Cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The Architecture of the infrastructure is shown in the exhibit:

The architecture will be used by the following users:
* Support analysts who run applications that will use REST to submit Spark jobs.
* Business analysts who use JDBC and ODBC client applications from a real-time view. The business analysts run monitoring quires to access aggregate result for 15 minutes. The result will be referenced by subsequent quires.
* Data analysts who publish notebooks drawn from batch layer, serving layer and speed layer queries. All of the notebooks must support native interpreters for data sources that
are bath processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The Following data sources are used:
* Hive for sales data
* Apache HBase for operations data
* HBase for logistics data by suing a single region server.
End of Repeated scenario.
The business analysts require to monitor the sales data. The queries must be faster and more interactive than the batch layer queries.
You need to create a new infrastructure to support the queries. The solution must ensure that you can tune the cache policies of the queries.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to answer area.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:

NEW QUESTION 7
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
You need to deploy a NoSQL database to an HDInsight cluster. You will manage the servers that host the database by using Remote Desktop. The database must use the key/value pair format in a columnar model.
What should you do?

• A. Use an Azure PowerShell Script to create and configure a premium HDInsight cluste
• B. Specify Apache Hadoop as the cluster type and use Linux as the operating System.
• C. Use the Azure portal to create a standard HDInsight cluste
• D. Specify Apache Spark as the cluster type and use Linux as the operating system.
• E. Use an Azure PowerShell script to create a standard HDInsight cluste
• F. Specify Apache HBase as the cluster type and use Windows as the operating system.
• G. Use an Azure PowerShell script to create a standard HDInsight cluste
• H. Specify Apache Storm as the cluster type and use Windows as the operating system.
• I. Use an Azure PowerShell script to create a premium HDInsight cluste
• J. Specify Apache HBase as the cluster type and use Windows as the operating system.
• K. Use an Azure portal to create a standard HDInsight cluste
• L. Specify Apache Interactive Hive as the cluster type and use Windows as the operating system.
• M. Use an Azure portal to create a standard HDInsight cluste
• N. Specify Apache HBase as the cluster type and use Windows as the operating system.

Answer: G

Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hbase-overview

NEW QUESTION 8
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
Start of Repeated Scenario:
You have an initial data that contains the crime data from major cities.
You plan to build training models from the training data. You plan to automate the process of adding more data to the training models and to training 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 ptace.
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 tor the various tasks associated to the processing pipeline.
End of repeated Scenario.
You are planning a storage strategy for a large amount of analytic data used for the crime data analytics system. The initial data load involves aver 100 billion records, and more than two billion records will be added daily.
You already created an Apache Hadoop cluster in HDInsight premium.
You need to implement the storage strategy to meet the following requirements:
• The storage capacity must support 50 TB.
• The storage must he optimized tor Hadoop.
• The data must be stored in its native format
• Enterprise-level security based on Active Directory must be supported.
What should you create?

• A. a virtual machine (VM) by using the Window, that has premium storage- a G-series size, and uses Microsoft SQL Server 2021 to store the data
• B. an Azure Data Lake Analytics service by using Azure Power Shell
• C. an Azure Data Lake Store account by using the Azure portal
• D. an Azure Blob storage account by using the Azure portal

Answer: C

Explanation:
References: https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-getstarted-portal

NEW QUESTION 9
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
Start of Repeated Scenario:
You are planning a big data infrastructure by using an Apache Spark Cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The Architecture of the infrastructure is shown in the exhibit:

The architecture will be used by the following users:
* Support analysts who run applications that will use REST to submit Spark jobs.
* Business analysts who use JDBC and ODBC client applications from a real-time view. The business analysts run monitoring quires to access aggregate result for 15 minutes. The result will be referenced by subsequent quires.
* Data analysts who publish notebooks drawn from batch layer, serving layer and speed layer queries. All of the notebooks must support native interpreters for data sources that are bath processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The Following data sources are used:
* Hive for sales data
* Apache HBase for operations data
* HBase for logistics data by suing a single region server.
End of Repeated scenario.
You need to ensure that the support analysts can develop embedded analytics applications by using the least amount of development effort.
Which technology should you implement?

• A. Zeppelin
• B. Jupyter
• C. Apache Ambari
• D. Livy

Answer: D

Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-spark-livyrest-interface

NEW QUESTION 10
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution. Start of Repeated Scenario:
You have an initial data that contains the crime data from major cities.
You plan to build training models from the training data. You plan to automate the process of adding more data to the training models and to training 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 ptace.
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 tor the various tasks associated to the processing pipeline.
End of repeated Scenario.
You are designing the real-time portion of the input stream processing. The input will be a continuous stream of data and each record will be processed one at a time. The data will come from an Apache Kafka producer.
You need to identify which HDInsight cluster to use for the final processing of the input data. This will be used to generate continuous statistics and real-time analytics. The latency to process each record must be less than one millisecond and tasks must be performed in parallel.
Which type of cluster should you identify?

• A. Apache Storm
• B. Apache Hadoop
• C. Apache HBase
• D. Apache Spark

Answer: A

Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storm-overview

NEW QUESTION 11
DRAG DROP
You have a domain-joined Azure HDInsight cluster. You plan to assign permissions to several support staff.
You need to assign roles to the staff so that they can perform specific tasks.
The solution must use the principle of least privilege.
Which role should you assign for each task? To answer, drag the appropriate roles to the correct tasks. Each role 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.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:

NEW QUESTION 12
You are configuring the Hive views on an Azure HDInsight cluster that is configured to use Kerberos.
You plan to use the YARN loos to troubleshoot a query that runs against Apache Hadoop. You need to view the method, the service, and the authenticated account used to run the query. Which method call should you view in the YARN logs?

• A. HQL
• B. WebHDFS
• C. HDFS C* API
• D. Ambari REST API

Answer: D

NEW QUESTION 13
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
Start of Repeated Scenario:
You have an initial data that contains the crime data from major cities.
You plan to build training models from the training data. You plan to automate the process of adding more data to the training models and to training 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 ptace.
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 tor the various tasks associated to the processing pipeline.
End of repeated Scenario.
You plan to consolidate all of the stream into a single timeline, even though none of the streams report events at the same interval.
You need to aggregate the data from the feeds to align with the time interval stream. The result must be the sim of all values for each within a 10 second interval, with the keys being the hashtags.
Which function should you use?

• A. countByWindow
• B. reduccByWindow
• C. reduceByKeyAndWindow
• D. countByValueAndWindow
• E. updateStateByKey

Answer: E

NEW QUESTION 14
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
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

NEW QUESTION 15
DRAG DROP
You have an Apache Hive cluster in Azure HDInsight. You need to tune a Hive query to meet the following requirements:
• Use the Tez engine.
• Process 1,024 rows in a batch.
How should you complete this query? To answer, drag the appropriate values to the correct targets.

• A. Mastered
• B. Not Mastered

Answer: A

Explanation:

NEW QUESTION 16
You have on Apache Hive table that contains one billion rows.
You plan to use queries that will filter the data by using the WHERE clause. The values of the columns will be known only while the data loads into a Hive table.
You need to decrease the query runtime. What should you configure?

• A. static partitioning
• B. bucket sampling
• C. parallel execution
• D. dynamic partitioning

Answer: C

Explanation:
References: https://www.qubole.com/blog/5-tips-for-efficient-hive-queries/

NEW QUESTION 17
Note: This question is part of a series of questions that present the same Scenario. Each question I 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 correct solution.
You need to deploy an HDInsight cluster that will provide in memory processing, interactive queries, and micro batch stream processing. The cluster has the following requirements:
• Uses Azure Data Lake Store as the primary storage
• Can be used by HDInsight applications. What should you do?

• A. Use an Azure PowerShell Script to create and configure a premium HDInsight cluste
• B. Specify Apache Hadoop as the cluster type and use Linux as the operating System.
• C. Use the Azure portal to create a standard HDInsight cluste
• D. Specify Apache Spark as the cluster type and use Linux as the operating system.
• E. Use an Azure PowerShell script to create a standard HDInsight cluste
• F. Specify Apache HBase as the cluster type and use Windows as the operating system.
• G. Use an Azure PowerShell script to create a standard HDInsight cluste
• H. Specify ApacheStorm as the cluster type and use Windows as the operating system.
• I. Use an Azure PowerShell script to create a premium HDInsight cluste
• J. Specify Apache HBase as the cluster type and use Windows as the operating system.
• K. Use an Azure portal to create a standard HDInsight cluste
• L. Specify Apache Interactive Hive as the cluster type and use Windows as the operating system.
• M. Use an Azure portal to create a standard HDInsight cluste
• N. Specify Apache HBase as the cluster type and use Windows as the operating system

Answer: B

NEW QUESTION 18
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