microsoft

Similar documents
Exam Questions

exam. Microsoft Perform Data Engineering on Microsoft Azure HDInsight. Version 1.0

Microsoft. Exam Questions Perform Data Engineering on Microsoft Azure HDInsight (beta) Version:Demo

Microsoft Perform Data Engineering on Microsoft Azure HDInsight.

Microsoft. Exam Questions Perform Data Engineering on Microsoft Azure HDInsight (beta) Version:Demo

Microsoft. Perform Data Engineering on Microsoft Azure HDInsight Version: Demo. Web: [ Total Questions: 10]

BIG DATA COURSE CONTENT

Overview. Prerequisites. Course Outline. Course Outline :: Apache Spark Development::

HDInsight > Hadoop. October 12, 2017

The Hadoop Ecosystem. EECS 4415 Big Data Systems. Tilemachos Pechlivanoglou

Hadoop. Introduction / Overview

Hadoop 2.x Core: YARN, Tez, and Spark. Hortonworks Inc All Rights Reserved

Data Architectures in Azure for Analytics & Big Data

Innovatus Technologies

Big Data Syllabus. Understanding big data and Hadoop. Limitations and Solutions of existing Data Analytics Architecture

Delving Deep into Hadoop Course Contents Introduction to Hadoop and Architecture

Big Data Technology Ecosystem. Mark Burnette Pentaho Director Sales Engineering, Hitachi Vantara

SQT03 Big Data and Hadoop with Azure HDInsight Andrew Brust. Senior Director, Technical Product Marketing and Evangelism

Activator Library. Focus on maximizing the value of your data, gain business insights, increase your team s productivity, and achieve success.

Blended Learning Outline: Cloudera Data Analyst Training (171219a)

Overview. : Cloudera Data Analyst Training. Course Outline :: Cloudera Data Analyst Training::

CERTIFICATE IN SOFTWARE DEVELOPMENT LIFE CYCLE IN BIG DATA AND BUSINESS INTELLIGENCE (SDLC-BD & BI)

MODERN BIG DATA DESIGN PATTERNS CASE DRIVEN DESINGS

Hadoop. Course Duration: 25 days (60 hours duration). Bigdata Fundamentals. Day1: (2hours)

We are ready to serve Latest Testing Trends, Are you ready to learn?? New Batches Info

Index. Scott Klein 2017 S. Klein, IoT Solutions in Microsoft s Azure IoT Suite, DOI /

Apache Hive for Oracle DBAs. Luís Marques

Processing Unstructured Data. Dinesh Priyankara Founder/Principal Architect dinesql Pvt Ltd.

Microsoft Exam

Sizing Guidelines and Performance Tuning for Intelligent Streaming

Asanka Padmakumara. ETL 2.0: Data Engineering with Azure Databricks

Modern Data Warehouse The New Approach to Azure BI

Big Data Hadoop Developer Course Content. Big Data Hadoop Developer - The Complete Course Course Duration: 45 Hours

Oracle Big Data Connectors

Big Data Hadoop Course Content

Big Data. Big Data Analyst. Big Data Engineer. Big Data Architect

In-memory data pipeline and warehouse at scale using Spark, Spark SQL, Tachyon and Parquet

Big Data Architect.

Hadoop Development Introduction

Alexander Klein. #SQLSatDenmark. ETL meets Azure

Performance Tuning and Sizing Guidelines for Informatica Big Data Management

IBM Big SQL Partner Application Verification Quick Guide

Talend Big Data Sandbox. Big Data Insights Cookbook

Databases 2 (VU) ( / )

Cloud Computing & Visualization

Things Every Oracle DBA Needs to Know about the Hadoop Ecosystem. Zohar Elkayam

New Features and Enhancements in Big Data Management 10.2

An Introduction to Big Data Formats

Security and Performance advances with Oracle Big Data SQL

Franck Mercier. Technical Solution Professional Data + AI Azure Databricks

Hadoop Online Training

Databricks, an Introduction

Stages of Data Processing

MapR Enterprise Hadoop

DATA SCIENCE USING SPARK: AN INTRODUCTION

Hortonworks Data Platform

HADOOP COURSE CONTENT (HADOOP-1.X, 2.X & 3.X) (Development, Administration & REAL TIME Projects Implementation)

Agenda. Spark Platform Spark Core Spark Extensions Using Apache Spark

Increase Value from Big Data with Real-Time Data Integration and Streaming Analytics

Microsoft Big Data and Hadoop

April Copyright 2013 Cloudera Inc. All rights reserved.

Accelerate Big Data Insights

A Tutorial on Apache Spark

Big Data Analytics using Apache Hadoop and Spark with Scala

Distributed systems for stream processing

17/05/2017. What we ll cover. Who is Greg? Why PaaS and SaaS? What we re not discussing: IaaS

Blended Learning Outline: Developer Training for Apache Spark and Hadoop (180404a)

Apache Spark is a fast and general-purpose engine for large-scale data processing Spark aims at achieving the following goals in the Big data context

DHANALAKSHMI COLLEGE OF ENGINEERING, CHENNAI

Parallel Programming Principle and Practice. Lecture 10 Big Data Processing with MapReduce

Configuring and Deploying Hadoop Cluster Deployment Templates

Tuning Enterprise Information Catalog Performance

Flash Storage Complementing a Data Lake for Real-Time Insight

Introduction to Hadoop. High Availability Scaling Advantages and Challenges. Introduction to Big Data

Hadoop & Big Data Analytics Complete Practical & Real-time Training

IBM Data Science Experience White paper. SparkR. Transforming R into a tool for big data analytics

Adaptive Executive Layer with Pentaho Data Integration

Expert Lecture plan proposal Hadoop& itsapplication

Hadoop is supplemented by an ecosystem of open source projects IBM Corporation. How to Analyze Large Data Sets in Hadoop

Architecting Microsoft Azure Solutions (proposed exam 535)

Big Data Hadoop Stack

Hortonworks University. Education Catalog 2018 Q1

Cmprssd Intrduction To

Big Data Hadoop Certification Training

Hadoop course content

Techno Expert Solutions An institute for specialized studies!

Tuning the Hive Engine for Big Data Management

Topics. Big Data Analytics What is and Why Hadoop? Comparison to other technologies Hadoop architecture Hadoop ecosystem Hadoop usage examples

Impala. A Modern, Open Source SQL Engine for Hadoop. Yogesh Chockalingam

Data Storage Infrastructure at Facebook

Strategies for Incremental Updates on Hive

Report on The Infrastructure for Implementing the Mobile Technologies for Data Collection in Egypt

Hortonworks Data Platform

2/26/2017. Originally developed at the University of California - Berkeley's AMPLab

Processing of big data with Apache Spark

Talend Big Data Sandbox. Big Data Insights Cookbook

Azure Data Factory VS. SSIS. Reza Rad, Consultant, RADACAD

CONSOLIDATING RISK MANAGEMENT AND REGULATORY COMPLIANCE APPLICATIONS USING A UNIFIED DATA PLATFORM

HDP Security Overview

HDP Security Overview

Transcription:

70-775.microsoft Number: 70-775 Passing Score: 800 Time Limit: 120 min

Exam A QUESTION 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 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 Correct Answer: B /Reference: : QUESTION 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 new topics. Create a file import process to send messages. Start the consumer and run the producer. Does this meet the goal? A. Yes B. No Correct Answer: A /Reference: : 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 Correct Answer: B /Reference: : QUESTION 4 You have an Azure HDInsight cluster.

You need a build a solution to ingest real-time streaming data into a nonrelational distributed database. What should you use to build the solution? A. Apache Hive and Apache Kafka B. Spark and Phoenix C. Apache Storm and Apache HBase D. Apache Pig and Apache HCatalog Correct Answer: C /Reference: : References: http://storm.apache.org/ http://hbase.apache.org/ QUESTION 5 You have an 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 Correct Answer: C /Reference: :

References: https://www.qubole.com/blog/5-tips-for-efficient-hive-queries/ QUESTION 6 You plan to copy data from Azure Blob storage to an Azure SQL database by using Azure Data Factory. Which file formats can you use? A. binary, JSON, Apache Parquet, and ORC B. OXPS, binary, text and JSON C. XML, Apache Avro, text, and ORC D. text, JSON, Apache Avro, and Apache Parquet Correct Answer: D /Reference: : References: https://docs.microsoft.com/en-us/azure/data-factory/supported-file-formats-and-compression-codecs QUESTION 7 You have an Apache Spark cluster in Azure HDInsight. You plan to join a large table and a lookup table. You need to minimize data transfers during the join operation. What should you do? A. Use the reducebykey function. B. Use a Broadcast variable. C. Repartition the data. D. Use the DISK_ONLY storage level.

E. Store the lookup table to a disk. F. Store the lookup table to Azure Blob storage. Correct Answer: B /Reference: : References: https://www.dezyre.com/article/top-50-spark-interview-questions-and-answers-for-2017/208 QUESTION 8 You have an Apache Spark cluster in Azure HDInsight. You execute the following command. What is the result of running the command? A. the Hive ORC library is imported to Spark and external tables in ORC format are created B. the Spark library is imported and the data is loaded to an Apache Hive table C. the Hive ORC library is imported to Spark and the ORC-formatted data stored in Apache Hive tables becomes accessible D. the Spark library is imported and Scala functions are executed Correct Answer: C /Reference: : QUESTION 9 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 Correct Answer: AC /Reference: : References: https://stackoverflow.com/questions/37871194/how-to-tune-spark-executor-number-cores-and-executor-memory QUESTION 10 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 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. (Click the Exhibit button.)

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 queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries. 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 batch 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 using a single region server The business analysts report that they experience performance issues when they run the monitoring queries. You troubleshoot the performance issues and discover that the intermediate tables generated when the analysts run the queries cause pressure for the Java Virtual Machine (JVM) garbage collection per job. Which configuration settings should you modify to alleviate the performance issues? A. spark.sql.inmemorycolumnarstorage.batchsize B. spark.sql.broadcasttimeout C. spark.sql.files.opencostinbytes

D. spark.sql.shuffle.partitions Correct Answer: D /Reference: : QUESTION 11 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 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. (Click the Exhibit button.) 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 queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries. 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 batch 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 using a single region server 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 Correct Answer: D /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-spark-livy-rest-interface QUESTION 12 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 a NoSQL database to an HDInsight cluster. You will manage the server 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 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. Correct Answer: G /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hbase-overview QUESTION 13 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 enterprise data warehouse that will support in-memory analytics. The data warehouse must support connections that use the Microsoft Hive ODBC Driver and Beeline. The data warehouse will be managed by using Apache Amrabi only. 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. Correct Answer: F

/Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-use-interactive-hive QUESTION 14 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 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 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. Correct Answer: B /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-spark-overview QUESTION 15 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. Correct Answer: C /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-introduction QUESTION 16 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 data. 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 plan to consolidate all of the streams 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 alight with the time interval stream. The result must be the sum of all the values for each key within a 10 second interval, with the keys being the hashtags. Which function should you use? A. countbywindow B. reducebywindow C. reducebykeyandwindow D. countbyvalueandwindow E. updatestatebykey Correct Answer: E /Reference: : QUESTION 17 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 data. 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 are planning a storage strategy for a large amount of analytic data used for the crime data analytics system. The initial data load involves over 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 be optimized for 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 Data Science Virtual Machine template for Windows that has premium storage, a G-series size, and uses Microsoft SQL Server 2016 to store the data B. an Azure Data Lake Analytics service by using Azure PowerShell C. an Azure Data Lake Store account by using the Azure portal D. an Azure Blob storage account by using the Azure portal Correct Answer: C /Reference: : References: https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-get-started-portal QUESTION 18 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 data. 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 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 Correct Answer: A /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storm-overview QUESTION 19 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 Correct Answer: B /Reference: : References: https://hortonworks.com/hadoop-tutorial/how-to-use-hcatalog-basic-pig-hive-commands/ QUESTION 20 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 Correct Answer: B /Reference: : References: https://hortonworks.com/hadoop-tutorial/how-to-use-hcatalog-basic-pig-hive-commands/ QUESTION 21 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 Correct Answer: B /Reference: : References: https://hortonworks.com/hadoop-tutorial/how-to-use-hcatalog-basic-pig-hive-commands/ QUESTION 22 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 Correct Answer: A /Reference: : References: https://hortonworks.com/hadoop-tutorial/how-to-use-hcatalog-basic-pig-hive-commands/ QUESTION 23 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 workflow that retrieves data by using a U-SQL query. You need to provide the ability to query and combine data from multiple data sources. 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. Correct Answer: G /Reference: : References: https://www.sqlchick.com/entries/2017/10/29/two-ways-to-approach-federated-queries-with-u-sql-and-azure-data-lake-analytics QUESTION 24 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 two tables. Each table is larger than 250 TB. Both tables have approximately the same number of rows and columns. You need to match the tables based on a key column. You must minimize the size of the data table that is produced. 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. Correct Answer: A

/Reference: : References: http://www.openkb.info/2014/11/understanding-hive-joins-in-explain.html QUESTION 25 You deploy Apache Kafka to an Azure HDInsight cluster. You plan to load data into a topic that has a specific schema. You need to load the data while maintaining the existing schema. Which file format should you use to receive the data? A. JSON B. Kudu C. Apache Sequence D. CSV Correct Answer: A /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/kafka/apache-kafka-auto-create-topics QUESTION 26 You have an Apache Interactive Hive cluster in Azure HDInsight. The cluster has 12 processors and 96 GB of RAM. The YARN container size is set to 2 GB and the Tez container size is 3 GB. You configure one Tez container per processor. You are performing map joints between a 2-GB dimension table and a 96-GB fact table. You experience slow performance due to an inadequate utilization of the available resources. You need to ensure that the map joins are used.

Which two settings should you configure? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. A. SET hive.tez.container.size=98304 B. SET hive.auto.convert.join.noconditionaltask.size=2048mb C. SET yarn.scheduler.minimum-allocation-mb=6144mb D. SET hive.auto.convert.join.noconditionaltask.size=3072mb E. SET hive.tez.container.size=6144mb Correct Answer: C /Reference: : References: https://hortonworks.com/blog/how-to-plan-and-configure-yarn-in-hdp-2-0/ QUESTION 27 You have an Apache Hive cluster in Azure HDInsight. You plan to ingest on-premises data into Azure Storage. You need to automate the copying of the data to Azure Storage. Which tool should you use? A. Microsoft Azure Storage Explorer B. Azure Import/Export Service C. Azure Backup D. AzCopy Correct Answer: D /Reference: : References: https://docs.microsoft.com/en-us/azure/data-factory/tutorial-hybrid-copy-data-tool

QUESTION 28 You have an Apache HBase cluster in Azure HDInsight. You plan to use Apache Pig, Apache Hive, and HBase to access the cluster simultaneously and to process data stored in a single platform. You need to deliver consistent operations, security, and data governance. What should you use? A. Apache Ambari B. MapReduce C. Apache Oozie D. YARN Correct Answer: D /Reference: : References: https://hortonworks.com/blog/hbase-hive-better-together/ QUESTION 29 You have several Linux-based and Windows-based Azure HDInsight clusters. The clusters are indifferent Active Directory domains. You need to consolidate system logging for all of the clusters into a single location. The solution must provide near real-time analytics of the log data. What should you use? A. Apache Ambari B. YARN C. Microsoft System Center Operations Manager

D. Microsoft Operations Management Suite (OMS) Correct Answer: A /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-log-management QUESTION 30 You have an Apache Spark job. The performance of the job deteriorates over time. You plan to debug the job. You need to gather information that you can use to debug the job. Which tool should you use? A. YARN B. Spark History Server C. HDInsight Cluster Dashboard D. Jupyter Notebook Correct Answer: A /Reference: : https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-job-debugging QUESTION 31 You create a Linux-based Azure HDInsight cluster by using the Azure portal. You plan to use Microsoft Power Query for Excel to debug a job failure. You need to identify all of the components that failed for the head node.

Which component contains the log files? A. Azure Table Storage B. a worker node in an Apache Hadoop cluster C. Azure SQL Database D. Azure Blob storage Correct Answer: A /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-debug-jobs QUESTION 32 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 to perform real-time event processing. The cluster server must be managed by using Remote Desktop. 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. Correct Answer: D /Reference: :

References: https://github.com/huachao/azure-content/blob/master/articles/hdinsight/hdinsight-provision-clusters.md QUESTION 33 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 a domain-joined HDInsight cluster for query and analytics batch jobs. The cluster will be managed by using HDInsight applications. Apache Oozie will be used for scheduling jobs. 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. Correct Answer: A /Reference: : References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-provision-linux-clusters https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-use-oozie-linux-mac