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NEW QUESTION: 1
A telecommunications company is celebrating its 50 year anniversary. It wants to serve a personalized experience to its customers based on how long they have been with the company. The company stores the long form date of their first contract.
How should an architect recommend incorporating this data into Audience Manager?
A. * Extract year and month from the CRM system
* Create a trait for each month (1 -12) and each year and combine into a segment
B. * Extract the year from the CRM system
* Create a trait for each 5 year range they have been a customer
C. * Extract the year from the CRM system
* Create a trait for each calendar year that the company has been in business
D. * Extract the month and year from the CRM system
* Create a trait for number of years since initial contract date
Answer: B

NEW QUESTION: 2
Amazon S3 has the following structure: S3://BUCKET/FOLDERNAME/FILENAME.zip Which S3 best practice would optimize performance with thousands of PUT request each second to a single bucket?
A. Prefix file names with timestamps; for example, s3://BUCKET/FOLDERNAME/2013-26-05-15-00-00- FILENAME.zip
B. Prefix folder names with user id; for example, s3://BUCKET/2013-FOLDERNAME/FILENAME.zip
C. Prefix folder names with random hex hashes; for example, s3://BUCKET/23a6-FOLDERNAME/ FILENAME.zip
D. Prefix file names with random hex hashes; for example, s3://BUCKET/FOLDERNAME/23a6- FILENAME.zip
Answer: C
Explanation:
Explanation
Refer AWS documentation - S3 Performance
Amazon S3 maintains an index of object key names in each AWS region. Object keys are stored in UTF-8 binary ordering across multiple partitions in the index. The key name dictates which partition the key is stored in. Using a sequential prefix, such as time stamp or an alphabetical sequence, increases the likelihood that Amazon S3 will target a specific partition for a large number of your keys, overwhelming the I/O capacity of the partition. If you introduce some randomness in your key name prefixes, the key names, and therefore the I/O load, will be distributed across more than one partition.
If you anticipate that your workload will consistently exceed 100 requests per second, you should avoid sequential key names. If you must use sequential numbers or date and time patterns in key names, add a random prefix to the key name. The randomness of the prefix more evenly distributes key names across multiple index partitions. Examples of introducing randomness are provided later in this topic.
One way to introduce randomness to key names is to add a hash string as prefix to the key name. For example, you can compute an MD5 hash of the character sequence that you plan to assign as the key name. From the hash, pick a specific number of characters, and add them as the prefix to the key name. The following example shows key names with a four-character hash

NEW QUESTION: 3
Consider a persistence application with following entity:
@Entity
Public class MyEntity {
@Column (name = "FIELDA_COLUMN")
int fieldA;
int fieldB;
int fieldC;
int fieldD;
An orm.xml is packaged in the application with the following contents:

Which two of following statement are true. (Choose two)
A. fieldD is a persistent attribute of MyEntity
B. fieldA is mapped to column FIELDA
C. fieldD is not a persistence attribute of MyEntity
D. fieldB is mapped to column NEW_COLB
Answer: C,D