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NEW QUESTION: 1
A customer wants to implement an OpenFlow solution where packets that do not match any flow entries in the OpenFlow table on the switch are not sent to the controller Rather, packets not matching should be handled normally by the switch. Which command enables this functionality on an HP 3800 series switch?
A. openflow instance sales mode normal
B. openflow instance sales mode hybrid
C. openflow instance sales mode passive
D. openflow instance sales mode active
Answer: C
Explanation:
Explanation/Reference:
OpenFlow instance mode
OpenFlow can work either in active or passive mode.
Passive mode
There is one-way communication from the OpenFlow controller to the switch. Packets that do not match any flow in the flow table on the switch are not sent to the controller. Such packets of new flows are handled normally by the switch.
Active mode
New packets of a flow that the switch is not aware of are sent to the OpenFlow controller.
Reference: HP Switch Software OpenFlow Administrator's Guide K/KA/WB 15.14
http://h20628.www2.hp.com/km-ext/kmcsdirect/emr_na-c03991489-1.pdf (OpenFlow instance mode, passive mode)

NEW QUESTION: 2
製造会社のデータエンジニアは、大量の非構造化データを受け取るデータ処理プラットフォームを設計しています。データエンジニアは、Amazon Redshiftに適切に構成されたスタースキーマを入力する必要があります。
この目的のための最も効率的なアーキテクチャ戦略は何ですか?
A. 非構造化データをRedshiftにロードし、分析スキーマに挿入するための構造化データを抽出するために文字列解析関数を使用します。
B. AWS Marketplace ETLツールを使用してデータを正規化し、結果をAmazon S3に永続化し、AWS Lambdaを使用してデータをRedshiftに挿入します。
C. データがAmazon S3に保存されたら、S3イベント通知とAWS Lambdaを使用してファイルの内容を変換します。 Redshiftの分析スキーマにデータを挿入します。
D. Amazon EMRを使用して非構造化データを変換し、CSVデータを生成します。 CSVデータをRedshift内の分析スキーマにコピーします。
Answer: D

NEW QUESTION: 3
Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You are implementing a batch processing solution by using Azure HDInsight.
You have two tables. Each table is larger than 250 TB. Both tables have approximately the same number of rows and columns.
You need to match the tables based on a key column. You must minimize the size of the data table that is produced.
What should you do?
A. Use an Azure Data Factory linked service that stores the data in Azure Data Lake.
B. Increase the number of spark.executor.instances in an Apache Spark job that stores the data in a text format.
C. Use a broadcast join in an Apache Hive query that stores the data in an ORC format.
D. Decrease the level of parallelism in an Apache Spark job that stores the data in a text format.
E. Use an Azure Data Factory linked service that stores the data in an Azure DocumentDB database.
F. Use a shuffle join in an Apache Hive query that stores the data in a JSON format.
G. Increase the number of spark.executor.cores in an Apache Spark job that stores the data in a text format.
H. Use an action in an Apache Oozie workflow that stores the data in a text format.
Answer: F
Explanation:
Explanation/Reference:
Explanation:
References: http://www.openkb.info/2014/11/understanding-hive-joins-in-explain.html