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NEW QUESTION: 1
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 Spark
B. Apache HBase
C. Apache Storm
D. Apache Hadoop
Answer: C
Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storm-overview
NEW QUESTION: 2
ボットネットは、DDoS攻撃を実行するために大量のGREカプセル化されたパケットで人気のあるWebサイトを攻撃しました。ニュースアウトレットは、特定のタイプの冷蔵庫が悪用され、クラッシュしたWebサイトに送信パケットを送信するために使用されていたことを発見しました。冷蔵庫は次のカテゴリのどれに属しますか？
A. SoC
B. ICS
C. IoT
D. MFD
Answer: C
NEW QUESTION: 3
When content from a flow is loaded into a region, overflowed content:
A. is buffered for download.
B. is truncated and an error flag is set.
C. attempts to fit into the region by auto-adjusting the styles.
D. continues into the next region.
Answer: D
NEW QUESTION: 4
More than one CNAME record is generated for the same domain name when Alibaba Cloud Anti-DDoS Premium Service Instance is purchased for load balancing purpose.
A. True
B. False
Answer: B
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