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. Apache Pig and Apache HCatalog
• B. Spark and Phoenix
• C. Apatite Hive and Apache Kafka
• D. Apache Storm and Apache HBase

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 Spark library is imported and Scala functions are executed
• D. the Hive ORC library is imported to Spark and the ORC-formatted data stored in Apache Hive tables becomes accessible

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 data analysts can use the notebooks.
What should you install?

• A. Zeppelin on workstations that access the batch layer
• B. Jupyter in the batch layer
• C. Jupyter on workstations that access the batch layer
• D. Zeppelin in the batch layer

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

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. text, JSON, Apache Avro, and Apache Parquet
• C. OXPS, binary, text and JSON
• D. XML, Apache Avro, text, and ORC