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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, delete the active lease for the reservation.
B. On DHCP1, recreate the reservation.
C. Run ipconfig.exe /registerdns.
D. Run ipconfig.exe /renew.
Answer: D

NEW QUESTION: 2

A. Option C
B. Option A
C. Option B
D. Option D
Answer: B,C
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. Configure the "Is Delegate Supported" field in the XML for the workflow rules.
B. Set the "ls Delegate Supported" field to "yes" in the workflow configuration.
C. Configure auto delegation by creating a new rule in the Rules Engine tool.
D. Configure the "ls Delegate Supported" field in the Corporate Data Model.
Answer: B,D

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. SQL
D. Spark
E. HBase
Answer: A,C,D
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