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NEW QUESTION: 1
A company is setting up a brand new datacenter and would like to keep the cabling infrastructure out of sight but still accessible to the network administrators. Infrastructure cost is not an issue.
Which of the following should be installed to meet the requirements?
A. Conduit
B. Patch panels
C. Raised floor
D. Cable trays
Answer: C
NEW QUESTION: 2
Drag and Drop Question
Guard Root / Guard Loop
Drag the description from the left to add on appropriate section on right.
Answer:
Explanation:
NEW QUESTION: 3
Which three are true concerning Hybrid Columnar Compression (HCC) deployed on Exadata storage?
A. By default, decompression is performed by Exadata Storage Servers.
B. HCC can be used only when the Exadata Smart Flash Cache is configured in Write-Through mode.
C. Rows residing in HCC compressed segments, are always self- contained in a single database block.
D. Row-level locks are supported on HCC compressed data.
E. HCC data is never cached in the Exadata Smart Flash Cache.
F. Rows residing in HCC compressed segments, are always self- contained in a single compression unit.
Answer: A,D,F
Explanation:
Explanation/Reference:
C: The decompression process typically takes place on the Oracle Exadata Storage Server in order to maximize performance and offload processing from the database server.
E: A logical construct called the compression unit is used to store a set of hybrid columnar compressed rows. When data is loaded, column values for a set of rows are grouped together and compressed. After the column data for a set of rows has been compressed, it is stored in a compression unit.
F: What happens when I update a row on compressed tables? What about locks?
BASIC and OLTP:
the updated row stays in the compressed block 'usual' Oracle's row-level locks Hybrid columnar:
Updated row is moved, as in a delete + insert
How to see that? With dbms_rowid package
New row is OLTP compressed if possible
Lock affects the entire CU that contains the row
Note: Oracle's Hybrid Columnar Compression technology is a new method for organizing data within a database block. As the name implies, this technology utilizes a combination of both row and columnar methods for storing data. This hybrid approach achieves the compression benefits of columnar storage, while avoiding the performance shortfalls of a pure columnar format.
Incorrect Answers:
B: Data remains compressed not only on disk, but also remains compressed in the Exadata Smart Flash Cache, on Infiniband, in the database server buffer cache, as well as when doing back-ups or log shipping to Data Guard.
References: http://www.oracle.com/technetwork/database/exadata/ehcc-twp-131254.pdf
NEW QUESTION: 4
For this question, refer to the TerramEarth case study.
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?
A. Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.
B. Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.
C. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
D. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi- Regional bucket. Run the ETL process using data in the bucket.
Answer: B
Explanation:
Topic 3, JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart- owned U.S. data centers.
Database
* Oracle Database stores user profiles
* 20 TB
* Complex table structure
* Well maintained, clean data
* Strong backup strategy
* PostgreSQL database stores user credentials
* Single-homed in US West
No redundancy
Backed up every 12 hours
* 100% uptime service level agreement (SLA)
* Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
Twin, dual core CPUs
32GB of RAM
* Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
Single dual-core CPU
2 4 GB of RAM
* Twin 250 GB HDD (RAID 1)
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long-term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure.
However, because of changing market trends, we need to outsource our infrastructure to ensure our long-term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.