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NEW QUESTION: 1
A storage administrator has an 8 TB database. Half of the data is hot and frequently accessed. The other half of the data is older with infrequently used cold dat a. The administrator purchased 12, 800 GB SLC SSDs and placed them in a new disk folder called
"Database".
The administrator then created volumes for this database in the Database disk folder using the recommended storage profile. After the database had been running for one month, the Statistics tab for the database volumes showed 100% of the space is on Tier 1. However, the administrator expected that half of the data would be on Tier 1 and the rest would be moved to lower tiers.
What are the reasons for this issue?
A. Recommended storage profile will only use SSD tiers if any are available Cold data cannot move to the lower tier disks
B. Volumes were created in the Database disk folder
Data Progression cannot move the cold data to the lower tier disks
C. Sufficient space is available on Tier 1 for the entire 8 TB database Event cold data will remain on Tier 1 until it becomes full
D. Data Progression does not run on database volumes
Database vendors have specific requirements for laying out their data across tiers
Answer: B

NEW QUESTION: 2
An organization has recently incurred significant cost overruns on one of its construction projects. Management suspects that these overruns were caused by the contractor improperly charging for costs related to contract change orders. Which of the following procedures are appropriate for testing this suspicion?
1. Determine if the contractor has received proper approval of change orders from management.
2. Determine if the contractor has billed for original contract work cancelled by the change orders.
3. Determine if the contractor has charged change orders with costs already billed to the original contract.
4. Determine if the contractor has been paid for change orders that have not yet been completed.
A. 1 and 2 only
B. 3 and 4 only
C. 2 and 3 only
D. 1 and 3 only
Answer: C

NEW QUESTION: 3
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. Jupyter on workstations that access the batch layer
B. Zeppelin in the batch layer
C. Jupyter in the batch layer
D. Zeppelin on workstations that access the batch layer
Answer: D
Explanation:
Explanation/Reference:
Explanation:
References: https://dzone.com/articles/data-visualization-using-apache-zeppelin

NEW QUESTION: 4
You need to analyze 60,000,000 images stored in JPEG format, each of which is approximately 25 KB. Because you Hadoop cluster isn't optimized for storing and processing many small files, you decide to do the following actions:
1.Group the individual images into a set of larger files
2.Use the set of larger files as input for a MapReduce job that processes them directly with python using Hadoop streaming.
Which data serialization system gives the flexibility to do this?
A. SequenceFiles
B. JSON
C. Avro
D. CSV
E. HTML
F. XML
Answer: D,F