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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 HBase
B. Apache Spark
C. Apache Storm
D. Apache Hadoop
Answer: C
Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-storm-overview

NEW QUESTION: 2
In order for a MQEndpoint policy to use a CCDT file, what must be done in addition to setting the ccdt property?
A. Set the CCDT file path as a BAR file override in any BAR file that uses the MQEndpoint policy.
B. Run the mqsichangepolicy command to specify the CCDT file path.
C. Run the mqsichangeproperties command to specify the CCDT file path.
D. Create a configurable service to specify the CCDT file path.
Answer: C
Explanation:
If you set the ccdt property in an MQEndpoint policy document to use a CCDT file, you must also run the mqsichangeproperties command to specify the CCDT file path. Use the following form, where IBNODE and file_path represent the integration node name, and the path to the CCDT file:
mqsichangeproperties IBNODE -o BrokerRegistry -n mqCCDT -v file_path
References:
https://www.ibm.com/support/knowledgecenter/en/SSMKHH_10.0.0/com.ibm.etools.mft.doc/bi62102_.htm

NEW QUESTION: 3

A. Yes
B. No
Answer: A
Explanation:
Explanation: References: https://www.microsoft.com/en-us/licensing/licensing-programs/enterprise.aspx

NEW QUESTION: 4
Which device type supports Exchange ActiveSync configuration with Onboard?
A. Linux laptop
B. Mac OS X device
C. Windows laptop
D. Apple iOS device
E. Android device
Answer: D
Explanation:
Exchange ActiveSync configurations you define can be used in configuration profiles to automatically configure an email account on an iOS device.
References: http://www.arubanetworks.com/techdocs/ClearPass/6.6/Guest/Content/Onboard/CreateEditActiveSync.htm