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NEW QUESTION: 1
Which of the following critical success factors would likely persuade a company to use a SaaS service?
A. The decrease of company-owned physical system downtime
B. The lowering of thin client management costs
C. The increase of web presence
D. The elimination of company driven application maintenance and backups
Answer: D

NEW QUESTION: 2
Which operating system is HP Smart Zero Core built upon?
A. WebOS
B. HPThinPro
C. Windows
D. ChromeOS
Answer: B
Explanation:
Reference:
http://h10010.www1.hp.com/wwpc/pscmisc/vac/us/product_pdfs/HP_t510_021312_Data_Sheet.pdf

NEW QUESTION: 3
A company develops a series of mobile games. All games use a single leaderboard service.
You have the following requirements:
*Code should be scalable and allow for growth.
*Each record must consist of a playedId, gameId, score, and time played.
*When users reach a new high score, the system will save the new score using the SaveScore function below.
*Each game is assigned and Id based on the series title.
You have the following code. (Line numbers are included for reference only.) You store customer information in an Azure Cosmos database. The following data already exists in the database:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Yes
Code for CosmosDB, example:
// Parse the connection string and return a reference to the storage account.
CloudStorageAccount storageAccount = CloudStorageAccount.Parse(
CloudConfigurationManager.GetSetting("StorageConnectionString"));
// Create the table client.
CloudTableClient tableClient = storageAccount.CreateCloudTableClient();
// Retrieve a reference to the table.
CloudTable table = tableClient.GetTableReference("people");
// Create the TableOperation object that inserts the customer entity.
TableOperation insertOperation = TableOperation.Insert(customer1);
Box 2: No
A new record will always be added as TableOperation.Insert is used, instead of TableOperation.InsertOrReplace.
Box 3: No
No partition key is used.
Box 4: Yes
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/table-storage-how-to-use-dotnet

NEW QUESTION: 4
During non-peak hours, a Developer wants to minimize the execution time of a full Amazon DynamoDB table scan without affecting normal workloads. The workloads average half of the strongly consistent read capacity units during non-peak hours.
How would the Developer optimize this scan?
A. Use parallel scans while limiting the rate
B. Use sequential scans
C. Change consistency to eventually consistent during the scan operation
D. Increase read capacity units during the scan operation
Answer: A
Explanation:
Explanation
Parallel scans would help improve the scan performance while using limit parameter the provisioned throughput consumed can be limited.
Refer AWS documentation - DynamoDB Parallel Scan
By default, the Scan operation processes data sequentially. DynamoDB returns data to the application in 1 MB increments, and an application performs additional operations to retrieve the next 1 MB of data.
The larger the table or index being scanned, the more time the take to complete. In addition, a sequential Scan might not always be able to fully utilize the provisioned read throughput capacity: Even though DynamoDB distributes a large table s data across multiple physical partitions, a Scan operation can only read one partition at a time. For this reason, the throughput of a is constrained by the maximum throughput of a single partition.
To address these issues, the Scan operation can logically divide a table or secondary index into multiple segments, with multiple application workers scanning the segments in parallel. Each worker can be a thread (in programming languages that support multithreading) or an operating system process.
A parallel scan with a large number of workers can easily consume all of the provisioned throughput for the table or index being scanned. It is best to avoid such scans if the table or index is also incurring heavy read or write activity from other applications.
To control the amount of data returned per request, use the Limit parameter. This can help prevent situations where one worker consumes all of the provisioned throughput, at the expense of all other workers.