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

NEW QUESTION: 2
Cloud Service A is hosted by Virtual Server A, which is hosted by Hypervisor A on Physical Server A.
Virtual Server B is hosted by Hypervisor B on Physical Server B.
Cloud Service Consumer A accesses Cloud Service A and the request is intercepted by an SLA monitor (1). Cloud Service A receives the request (2) and accesses Cloud Storage Device A and Cloud Storage Device B (3).
Cloud Service Consumer A belongs to Organization A, which is leasing all of the IT resources shown in the figure as part of an laaS environment.

Cloud Storage Device B has a higher performance capacity than Cloud Storage Device A.
Cloud Storage Device C has a higher performance capacity than Cloud Storage Device B.
The requests being received by Cloud Service A from Cloud Service Consumer A have recently increased in both quantity and in the amount of data being queried, written and read from Cloud Storage Device A.
As a result, Cloud Storage Device A's capacity is frequently reached and it has become unstable at times, timing out with some requests and rejecting other requests.
Cloud Storage Device C is used by Organization A to store backup data on a daily basis.
One day, a hardware failure within Cloud Storage Device C results in the permanent loss of data. Organization A requires a system that will prevent this type of failure from resulting in data loss.
The cloud provider is planning to implement a routine maintenance schedule for Cloud Storage Devices A, B, and C and issues a notice stating that the new schedule will start next week. An outage of 30 minutes every Thursday and Sunday at 8:00 PM is needed for the maintenance tasks. Upon hearing this, Organization A complains that they cannot afford to have Cloud Storage Devices A and B become inoperable, especially not during the weekdays.
Which of the following statements describes a solution that can address Organization A's issues?
A. None of the above.
B. The Intra-Storage Device Vertical Data Tiering pattern can be applied to enable dynamic scaling between Cloud Storage Devices A, B and C.
The Dynamic Failure Detection and Recovery pattern can be applied to establish a resilient watchdog system that is able to respond dynamically to prevent data loss. The Service State Management pattern can be applied to keep a copy of the data in Cloud Storage Devices A, B and C during the maintenance outages.
C. The Load Balanced Virtual Switches pattern can be applied to increase the bandwidth of Physical Server A so that data processing problems within Cloud Storage Device A can be prevented. The Non-Disruptive Service Relocation pattern can be applied to automatically relocate Cloud Storage Device A to Physical Server B so that data access is not interrupted. The Storage Maintenance Window pattern can be applied to replicate the data in Cloud Storage Device D for retrieval before the outages begin.
D. The Cross-Storage Device Vertical Tiering pattern can be applied to enable dynamic scaling between Cloud Storage Devices A, B and C.
The Redundant Storage pattern can be applied by designating Cloud Storage Device D as the secondary storage to which Organization A's data can be replicated. In order to prevent planned or unplanned outages from affecting Organization A's data access, the Storage Maintenance Window pattern can be applied to replicate the data in Cloud Storage Device D for retrieval before the outages begin.
Answer: D

NEW QUESTION: 3
A customer SAP system landscape is made up of several systems, all systems have to be migrated to
a different database.
System set 1 (ERP): Development, Quality Assurance, Production
System set 2 (BW): Development, Production.
How may system copies are involved for system 2 (BW)?
A. 1 X Development, 2 X Production
B. 1 X Development, 1X Quality Assurance, 2 X Production
C. 1 X Development, 2 X Production, homogeneous system copy from production to Quality
Assurance.
D. 2 X Development, 2 X Production.
Answer: A