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NEW QUESTION: 1
What can be created in Attribute Groups within Contact Builder? Choose 2.
A. Attribute Groups
B. Relationships
C. Populations
D. Data Extensions
Answer: B,D
NEW QUESTION: 2
Data hiding analysis can be useful in
A. identifying the amount of central processing unit (cpu) usage over time to process the data.
B. determining the level of encryption used to encrypt the data.
C. detecting and recovering data that may indicate knowledge, ownership or intent.
D. preventing a denial of service attack on a set of enterprise servers to prevent users from accessing the data.
Answer: C
NEW QUESTION: 3
会社は、販売トランザクションや顧客アカウント情報など、大規模なデータセットをAzureに保存します。
データを分析するソリューションを設計する必要があります。次のHDInsightクラスターを作成する予定です。
クラスタがクエリ要件をサポートしていることを確認する必要があります。
どのクラスタータイプをお勧めしますか?回答するには、回答領域で適切な構成を選択します。
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。
Answer:
Explanation:
Box 1: Interactive Query
Choose Interactive Query cluster type to optimize for ad hoc, interactive queries.
Box 2: Hadoop
Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process.
Note: In Azure HDInsight, there are several cluster types and technologies that can run Apache Hive queries.
When you create your HDInsight cluster, choose the appropriate cluster type to help optimize performance for your workload needs.
For example, choose Interactive Query cluster type to optimize for ad hoc, interactive queries. Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process. Spark and HBase cluster types can also run Hive queries.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/hdinsight-hadoop-optimize-hive-query?toc=%2Fko-kr%2F