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NEW QUESTION: 1
A company is deploying a service-based data environment. You are developing a solution to process this data.
The solution must meet the following requirements:
* Use an Azure HDInsight cluster for data ingestion from a relational database in a different cloud service
* Use an Azure Data Lake Storage account to store processed data
* Allow users to download processed data
You need to recommend technologies for the solution.
Which technologies should you use? To answer, select the appropriate options in the answer area.

Answer:
Explanation:

Explanation:
Box 1: Apache Sqoop
Apache Sqoop is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
Azure HDInsight is a cloud distribution of the Hadoop components from the Hortonworks Data Platform (HDP).
Incorrect Answers:
DistCp (distributed copy) is a tool used for large inter/intra-cluster copying. It uses MapReduce to effect its distribution, error handling and recovery, and reporting. It expands a list of files and directories into input to map tasks, each of which will copy a partition of the files specified in the source list. Its MapReduce pedigree has endowed it with some quirks in both its semantics and execution.
RevoScaleR is a collection of proprietary functions in Machine Learning Server used for practicing data science at scale. For data scientists, RevoScaleR gives you data-related functions for import, transformation and manipulation, summarization, visualization, and analysis.
Box 2: Apache Kafka
Apache Kafka is a distributed streaming platform.
A streaming platform has three key capabilities:
Publish and subscribe to streams of records, similar to a message queue or enterprise messaging system.
Store streams of records in a fault-tolerant durable way.
Process streams of records as they occur.
Kafka is generally used for two broad classes of applications:
Building real-time streaming data pipelines that reliably get data between systems or applications
Building real-time streaming applications that transform or react to the streams of data
Box 3: Ambari Hive View
You can run Hive queries by using Apache Ambari Hive View. The Hive View allows you to author, optimize, and run Hive queries from your web browser.
References:
https://sqoop.apache.org/
https://kafka.apache.org/intro
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-use-hive-ambari-view

NEW QUESTION: 2
Which statements is true about vSAN datastore?
A. VMwre vSAN can be implemented on top of any other datastores.
B. vSAN is a native Windows function.
C. vSAN is similar to RAW Device Mapping.
D. There is only one vSAN datastore per vSAN cluster
Answer: C

NEW QUESTION: 3
A company uses May 1 as the start of its fiscal year.
The company's management needs to define fiscal calendars and date intervals for financial activities and financial reporting.
You need to set up fiscal calendars and date intervals and understand how they are used in financial accounting.
Which of the following attributes or purposes does each of the data configurations have? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.


Answer:
Explanation:

References:
https://docs.microsoft.com/en-us/dynamics365/unified-operations/financials/budgeting/fiscal-calendars-fiscal-years-periods

NEW QUESTION: 4
Amazon Kinesisを使用してCloudWatchにメトリックスを送信する場合、メトリックス「PutRecord.Latency」を最もよく説明しているステートメントは次のうちどれですか？
A. Amazon Kinesisストリームごとの成功したPutRecordオペレーションの数であり、指定された期間にわたって測定されます。
B. PutRecords操作の統計を計算するためにPutRecords操作ごとにかかった時間です。
C. PutRecordオペレーションごとにかかった時間で、指定された期間にわたって測定されます。
D. Amazon KinesisストリームごとのPutRecordsオペレーションで成功したレコードの数であり、指定された期間にわたって測定されます。
Answer: C
Explanation:
Explanation
The metric PutRecord.Latency measures the time taken per PutRecord operation, measured over the specified time period.
Dimensions: StreamName
Statistics: Minimum, Maximum, Average
Units: Milliseconds
References: