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NEW QUESTION: 1
Your network contains a DHCP server named DHCP1. You have a DHCP reservation for a computer
named Computer1. You add a DNS server option to the reservation.
You need to ensure that Computer1 immediately receives the new option.
What should you do?
A. On DHCP1, recreate the reservation.
B. Run ipconfig.exe /renew.
C. Run ipconfig.exe /registerdns.
D. On DHCP1, delete the active lease for the reservation.
Answer: B

NEW QUESTION: 2

A. Option B
B. Option A
C. Option D
D. Option C
Answer: A,B
Explanation:
Explanation: http://www.cisco.com/c/en/us/support/docs/ip/generic-routing-encapsulation- gre/118361-technote-gre-00.html

NEW QUESTION: 3
How do you configure the Auto Delegate feature for workflows?
There are 2 correct answers to this question. Choose:
A. Set the "ls Delegate Supported" field to "yes" in the workflow configuration.
B. Configure the "ls Delegate Supported" field in the Corporate Data Model.
C. Configure auto delegation by creating a new rule in the Rules Engine tool.
D. Configure the "Is Delegate Supported" field in the XML for the workflow rules.
Answer: A,B

NEW QUESTION: 4
ビッグデータワークロードのインフラストラクチャを展開します。
Azure HDInsightとMicrosoft Machine Learning Serverを実行する必要があります。 RevoScaleR計算コンテキストを設定して、rx関数呼び出しを並行して実行する予定です。
Machine Learning Serverに使用できる3つの計算コンテキストは何ですか？それぞれの正解は完全な解決策を提示します。
注：それぞれの正しい選択には1ポイントの価値があります。
A. local parallel
B. local sequential
C. HBase
D. SQL
E. Spark
Answer: A,D,E
Explanation:
Explanation
Remote computing is available for specific data sources on selected platforms. The following tables document the supported combinations.
RxInSqlServer, sqlserver: Remote compute context. Target server is a single database node (SQL Server
2016 R Services or SQL Server 2017 Machine Learning Services). Computation is parallel, but not distributed.
RxSpark, spark: Remote compute context. Target is a Spark cluster on Hadoop.
RxLocalParallel, localpar: Compute context is often used to enable controlled, distributed computations relying on instructions you provide rather than a built-in scheduler on Hadoop. You can use compute context for manual distributed computing.
References:
https://docs.microsoft.com/en-us/machine-learning-server/r/concept-what-is-compute-context