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NEW QUESTION: 1
展示を参照してください。
ルーティングプロトコル間で再配布が有効になり、PC2、PC3、およびPC4がPC1に到達できない。問題を解決する2つの解決策は何ですか? (2つ選択してください。)
A. R2のRIPに再配布するときに、OSPFルートをRIP FROM EIGRPにフィルターします。
B. R2のRIPに再配布するときにRIPルートをフィルターしてRIPに戻す
C. R2でOSPFに再配布するときに、RIPおよびOSPFルートをフィルターしてEIGRPからOSPFに戻します
D. R3でOSPFに再配布するときに、EIGRPルートを除くすべてのルートをフィルタリングします。
E. R2のEIGRPに再配布するときに、RIPルートを除くすべてのルートをフィルタリングします。
Answer: A,B
Explanation:
Explanation
Even PC2 cannot reach PC1 so there is something wrong with RIP redistribution in R2. Because RIP has higher Administrative Distance (AD) value than OSPF and EIGRP so it will be looped when doing mutual redistribution.
NEW QUESTION: 2
Refer to the exhibit.
You configure a vPC between two Cisco Nexus 7010 Switches. The peer link will not come up.
What is the problem?
A. The system priority must be the same.
B. The role priority must be the same.
C. The vPC domain numbers must be different.
D. The configuration is incorrect.
Answer: A
NEW QUESTION: 3
Each day, company plans to store hundreds of files in Azure Blob Storage and Azure Data Lake Storage.
The company uses the parquet format.
You must develop a pipeline that meets the following requirements:
Process data every six hours
Offer interactive data analysis capabilities
Offer the ability to process data using solid-state drive (SSD) caching
Use Directed Acyclic Graph(DAG) processing mechanisms
Provide support for REST API calls to monitor processes
Provide native support for Python
Integrate with Microsoft Power BI
You need to select the appropriate data technology to implement the pipeline.
Which data technology should you implement?
A. HDInsight Apache Storm cluster
B. HDInsight Spark cluster
C. Azure Stream Analytics
D. Azure SQL Data Warehouse
E. HDInsight Apache Hadoop cluster using MapReduce
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Storm runs topologies instead of the Apache Hadoop MapReduce jobs that you might be familiar with.
Storm topologies are composed of multiple components that are arranged in a directed acyclic graph (DAG). Data flows between the components in the graph. Each component consumes one or more data streams, and can optionally emit one or more streams.
Python can be used to develop Storm components.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/storm/apache-storm-overview