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NEW QUESTION: 1
An application developer plans to use an XML component as a data source when using higher level device components.
Which XML component provides this service?
A. XML Station
B. XML Client
C. XML VDN
D. XML Routing
Answer: A
Explanation:
Explanation/Reference:
Reference: https://downloads.avaya.com/css/P8/documents/100175255 (p.39)

NEW QUESTION: 2
You are a VMware consultant who has been hired to take over a mismanaged VMware vSphere 5 platform estate. You are presented with the vCenter administrator password and given the following information.
1.The system has full production support from VMware.
2.The platform has been suffering from performance problems for two weeks.
3.No documentation exists.
Your role is to design and implement a platform that meets the following requirements:
-R001: Stable for current workloads -R002: Supportable by operations staff
Which of the following discovery methods should be used?
A. Passive discovery
B. Active discovery
Answer: A
Explanation:
There are two types of discovery methods:
Active discovery can run processes which are detrimental and can impact a system, and normally
requires anagent.
With passive discovery, data is obtained in a non-impactful, non-intrusive manner with no agents.
Data such asthis normally needs more experience to obtain and interpret/present.

NEW QUESTION: 3

A. Option C
B. Option B
C. Option A
D. Option D
Answer: C

NEW QUESTION: 4
オンライン小売業者がAmazon DynamoDBを使用して、顧客トランザクションに関連するデータを保存しています。テーブル内のアイテムには、トランザクションを説明するいくつかの文字列属性と、ショッピングカートやトランザクションに対応するその他の詳細を含むJSON属性が含まれています。平均アイテムサイズは最大250 KBで、そのほとんどはJSON属性に関連付けられています。平均では、1か月あたり最大3GBのデータが生成されます。
顧客はテーブルにアクセスして取引履歴を表示し、必要に応じて取引の詳細を確認します。テーブルに対するクエリの90％は、トランザクション履歴ビューを作成するときに実行されます。
トランザクションの詳細を取得する10％。テーブルはCustomerIDでパーティション分割され、トランザクションデータでソートされます。
クライアントはテーブルにプロビジョニングされた非常に高い読み取り容量を持ち、非常に均一な使用率を経験しますが、他のNoSQLソリューションと比較したAmazon DynamoDBのコストについて不平を言っています。
品質を低下させずに、クライアントの読み取りクエリに関連するコストを削減する戦略はどれですか？
A. 最終的に一貫した読み取りを使用するようにすべてのデータベース呼び出しを変更し、トランザクション履歴が1秒古くなる可能性があることをお客様に通知します。
B. TransactionIDでパーティション化するプライマリテーブルを変更し、顧客でパーティション化され、日付でソートされたGSIを作成し、小さな属性をGSIに投影し、GSIにサマリーデータとJSON詳細のプライマリテーブルを照会します。
C. 日付でソートされたLSIを作成し、JSON属性をインデックスに投影し、サマリーデータのプライマリテーブルとJSON詳細のLSIをクエリします
D. テーブルを垂直方向にパーティション化し、基本属性をプライマリテーブルに格納し、JSONデータを含むセカンダリテーブルへの外部キー参照を作成します。サマリーデータのプライマリテーブルとJSONの詳細のセカンダリテーブルをクエリします。
Answer: D