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NEW QUESTION: 1
You have created several Infotiles based on the client requirements, You now want to group them together for display. How do you accomplish this?
A. No need to group them. Open them directly on the plan going to Open (choose area) > Choose Infotile.
B. First build them into a tile set in Manage Table, Graphs, and Analysis Sets. Then open the tile set on the plan by going to Open (choose area) > Choose tile set.
C. First build them into a planning group in Manage Planning Groups. Then open the planning group on the plan by going to Open (choose area) > Choose planning group.
D. First build them into a info set in Manage Infosets. Then open the info set on the plan by going to Open (choose area) > Choose info set.
E. First build them into a planning measure in Manage Planning Measures. Then open the planning measure on the plan by going to Open (choose area) > Choose planning measure.
Answer: B

NEW QUESTION: 2
Which types of objects can be changed with Engineering Change Management (ECM)? (Choose three)
A. Bill of material
B. Production version
C. Material master
D. Work center
E. Task list
Answer: A,C,E

NEW QUESTION: 3
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You are planning a big data infrastructure by using an Apache Spark cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The architecture of the infrastructure is shown in the exhibit. (Click the Exhibit button.)

The architecture will be used by the following users:
Support analysts who run applications that will use REST to submit Spark jobs.

Business analysts who use JDBC and ODBC client applications from a real-time view. The business

analysts run monitoring queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries.
Data analysts who publish notebooks drawn from batch layer, serving layer, and speed layer queries.

All of the notebooks must support native interpreters for data sources that are batch processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The following data sources are used:
Hive for sales data

Apache HBase for operations data

HBase for logistics data by using a single region server

You need to ensure that the analysts can query the logistics data by using JDBC APIs and SQL APIs.
Which technology should you implement?
A. Apache Hive
B. Apache Phoenix
C. Apache Storm
D. Apache Spark
Answer: B
Explanation:
Explanation/Reference:
Explanation:
References: http://phoenix.apache.org/

NEW QUESTION: 4
Google Kubernetes Engine（GKE）の上に製品を構築しています。単一のGKEクラスタがあります。顧客ごとに、そのクラスターでポッドが実行されており、顧客はポッド内で任意のコードを実行できます。顧客のポッド間の分離を最大化したい。あなたは何をするべきか？
A. GKEノードにcos_containerdイメージを使用します。 cloud.google.com/gke-os-distribution：cos_containerdという値を持つnodeSelectorを顧客のポッドの仕様に追加します。
B. バイナリ認証を使用し、顧客のポッドで使用されるコンテナーイメージのみをホワイトリストに登録します。
C. Container Analysis APIを使用して、顧客のポッドが使用するコンテナーの脆弱性を検出します。
D. gvisorに構成されたサンドボックスタイプでGKEノードプールを作成します。パラメータruntimeClassName：gvisorを顧客のポッドの仕様に追加します。
Answer: D