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NEW QUESTION: 1
View the exhibit and examine the structure of the SALES, CUSTOMERS, PRODUCTSand TIMEStables.

The PROD_IDcolumn is the foreign key in the SALEStables, which references the PRODUCTStable.
Similarly, the CUST_IDand TIME_IDcolumns are also foreign keys in the SALEStable referencing the CUSTOMERSand TIMEStables, respectively.
Evaluate the following CREATE TABLEcommand:
CREATE TABLE new_sales (prod_id, cust_id, order_date DEFAULT SYSDATE)
AS
SELECT prod_id, cust_id, time_id
FROM sales;
Which statement is true regarding the above command?
A. The NEW_SALEStable would get created and all the NOTNULLconstraints defined on the specified columns would be passed to the new table.
B. The NEW_SALEStable would not get created because the column names in the CREATETABLE command and the SELECTclause do not match.
C. The NEW_SALEStable would not get created because the DEFAULTvalue cannot be specified in the column definition.
D. The NEW_SALEStable would get created and all the FOREIGNKEYconstraints defined on the specified columns would be passed to the new table.
Answer: A

NEW QUESTION: 2
Flowlogistic Case Study
Company Overview
Flowlogistic is a leading logistics and supply chain provider. They help businesses throughout the world manage their resources and transport them to their final destination. The company has grown rapidly, expanding their offerings to include rail, truck, aircraft, and oceanic shipping.
Company Background
The company started as a regional trucking company, and then expanded into other logistics market.
Because they have not updated their infrastructure, managing and tracking orders and shipments has become a bottleneck. To improve operations, Flowlogistic developed proprietary technology for tracking shipments in real time at the parcel level. However, they are unable to deploy it because their technology stack, based on Apache Kafka, cannot support the processing volume. In addition, Flowlogistic wants to further analyze their orders and shipments to determine how best to deploy their resources.
Solution Concept
Flowlogistic wants to implement two concepts using the cloud:
Use their proprietary technology in a real-time inventory-tracking system that indicates the location of

their loads
Perform analytics on all their orders and shipment logs, which contain both structured and unstructured

data, to determine how best to deploy resources, which markets to expand info. They also want to use predictive analytics to learn earlier when a shipment will be delayed.
Existing Technical Environment
Flowlogistic architecture resides in a single data center:
Databases

- 8 physical servers in 2 clusters
- SQL Server - user data, inventory, static data
- 3 physical servers
- Cassandra - metadata, tracking messages
10 Kafka servers - tracking message aggregation and batch insert
Application servers - customer front end, middleware for order/customs

- 60 virtual machines across 20 physical servers
- Tomcat - Java services
- Nginx - static content
- Batch servers
Storage appliances

- iSCSI for virtual machine (VM) hosts
- Fibre Channel storage area network (FC SAN) - SQL server storage
Network-attached storage (NAS) image storage, logs, backups
10 Apache Hadoop /Spark servers

- Core Data Lake
- Data analysis workloads
20 miscellaneous servers

- Jenkins, monitoring, bastion hosts,
Business Requirements
Build a reliable and reproducible environment with scaled panty of production.

Aggregate data in a centralized Data Lake for analysis

Use historical data to perform predictive analytics on future shipments

Accurately track every shipment worldwide using proprietary technology

Improve business agility and speed of innovation through rapid provisioning of new resources

Analyze and optimize architecture for performance in the cloud

Migrate fully to the cloud if all other requirements are met

Technical Requirements
Handle both streaming and batch data

Migrate existing Hadoop workloads

Ensure architecture is scalable and elastic to meet the changing demands of the company.

Use managed services whenever possible

Encrypt data flight and at rest

Connect a VPN between the production data center and cloud environment
SEO Statement
We have grown so quickly that our inability to upgrade our infrastructure is really hampering further growth and efficiency. We are efficient at moving shipments around the world, but we are inefficient at moving data around.
We need to organize our information so we can more easily understand where our customers are and what they are shipping.
CTO Statement
IT has never been a priority for us, so as our data has grown, we have not invested enough in our technology. I have a good staff to manage IT, but they are so busy managing our infrastructure that I cannot get them to do the things that really matter, such as organizing our data, building the analytics, and figuring out how to implement the CFO' s tracking technology.
CFO Statement
Part of our competitive advantage is that we penalize ourselves for late shipments and deliveries. Knowing where out shipments are at all times has a direct correlation to our bottom line and profitability.
Additionally, I don't want to commit capital to building out a server environment.
Flowlogistic's management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?
A. Cloud Dataflow, Cloud SQL, and Cloud Storage
B. Cloud Pub/Sub, Cloud SQL, and Cloud Storage
C. Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage
D. Cloud Load Balancing, Cloud Dataflow, and Cloud Storage
E. Cloud Pub/Sub, Cloud Dataflow, and Local SSD
Answer: B
Explanation:
Explanation/Reference:

NEW QUESTION: 3
COALESCE関数について正しい説明はどれですか。
A. リストには最大5つの式を含めることができます。
B. リスト内の式の少なくとも1つにNOT NULL値が必要です。
C. リスト内のすべての式が同じデータ型である必要があります。
D. すべての行のリストで最高のNOT NULL値を返します。
Answer: C
Explanation:
The COALESCE Function
The COALESCE function returns the first nonnull value from its parameter list. If all its parameters are null, then null is returned.
The COALESCE function takes two mandatory parameters and any number of optional parameters. The syntax is COALESCE(expr1, expr2, ..., exprn), where expr1 is returned if it is not null, else expr2 if it is not null, and so on. COALESCE is a general form of the NVL function, as the following two equations illustrate:
COALESCE(expr1, expr2) = NVL(expr1, expr2)
COALESCE(expr1, expr2, expr3) = NVL(expr1, NVL(expr2, expr3))
The data type COALESCE returns if a not null value is found is the same as that of the first not null parameter.
To avoid an "ORA-00932: inconsistent data types" error, all not null parameters must have data types compatible with the first not null parameter.

NEW QUESTION: 4
An e-commerce company is running a web application in an AWS Elastic Beanstalk environment.
In recent months, the average load of the Amazon EC2 instances has been increased to handle more traffic. The company would like to improve the scalability and resilience of the environment.
The Development team has been asked to decouple long-running tasks from the environment if the tasks can be executed asynchronously. Examples of these tasks include confirmation emails when users are registered to the platform, and processing images or videos. Also, some of the periodic tasks that are currently running within the web server should be offloaded.
What is the most time-efficient and integrated way to achieve this?
A. Create an Amazon SQS queue and send the tasks that should be decoupled from the Elastic Beanstalk web server environment to the SQS queue. Create a fleet of EC2 instances under an Auto Scaling group. Use an AMI that contains the application to process the asynchronous tasks, configure the application to listen for messages within the SQS queue, and create periodic tasks by placing those into the cron in the operating system. Create an environment variable within the Elastic Beanstalk environment with a value pointing to the SQS queue endpoint.
B. Create a second Elastic Beanstalk worker tier environment and deploy the application to process the asynchronous tasks there. Send the tasks that should be decoupled from the original Elastic Beanstalk web server environment to the auto-generated Amazon SQS queue by the Elastic Beanstalk worker environment. Place a cron.yaml file within the root of the application source bundle for the worker environment periodic tasks. Use environment links to link the web server environment with the worker environment.
C. Create an Amazon SQS queue and send the tasks that should be decoupled from the Elastic Beanstalk web server environment to the SQS queue. Create a fleet of EC2 instances under an Auto Scaling group. Install and configure the application to listen for messages within the SQS queue from UserData and create periodic tasks by placing those into the cron in the operating system. Create an environment variable within the Elastic Beanstalk web server environment with a value pointing to the SQS queue endpoint.
D. Create a second Elastic Beanstalk web server tier environment and deploy the application to process the asynchronous tasks. Send the tasks that should be decoupled from the original Elastic Beanstalk web server to the auto-generated Amazon SQS queue by the Elastic Beanstalk web server tier environment. Place a cron.yaml file within the root of the application source bundle for the second web server tier environment with the necessary periodic tasks. Use environment links to link both web server environments.
Answer: D

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