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NEW QUESTION: 1
What statement is true regarding database and index reorganization in relation to directory-container storage pools?
A. Offline Index reorganization is not necessary because the server completes inline index reorganizations with a CLEANUP ONLY technique
B. Index reorganization is still necessary but not so often as with legacy file based deduplication pools
C. Database reorganization will automatically be started when the reorg_db_threshold is reached
D. Database reorganization is not necessary because the inventory component of the server will no longer become fragmented
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Do I need to run offline index reorganization if I use directory-container storage pools?
No. The server completes inline index reorganizations with a CLEANUP ONLY technique. No other type of index reorganization is required.
References: https://www.ibm.com/developerworks/community/wikis/home?lang=en#!/wiki/Tivoli%
20Storage%20Manager/page/Directory-container%20storage%20pools%20FAQs?section=q13

NEW QUESTION: 2
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:

NEW QUESTION: 3
RJ-45コネクタがデータを送信するために使用する2つのピンはどれですか？ （2つ選択）
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: C,E

NEW QUESTION: 4
Azure Machine Learning Studioでイメージ分類モデルを作成します。
モデルをコンテナー化されたWebサービスとしてデプロイする必要があります。
どの4つのアクションを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答エリアに移動し、正しい順序に並べます。

Answer:
Explanation:

Explanation

The following diagram illustrates the complete deployment workflow:
The deployment workflow includes the following steps:
* Register the model in a registry hosted in your Azure Machine Learning Service workspace
* Register an image that pairs a model with a scoring script and dependencies in a portable container
* Deploy the image as a web service in the cloud or to edge devices
* Monitor and collect data
* Update a deployment to use a new image.
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/service/concept-model-management-and-deploym