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NEW QUESTION: 1
Which two statements are true about the implementation of multicast in NSX-T Data Center? (Choose two.)
A. An Edge can be the Rendezvous Point.
B. Multicast is supported in ESXi and KVM transport nodes.
C. IGMP Snooping is used to populate multicast forwarding tables.
D. Multicast routing is implemented with PIM Sparse-Mode.
E. Tier-0 gateways can be the Rendezvous Point.
Answer: C,D
NEW QUESTION: 2
Which maintenance action releases the assigned chassis ID for future use?
A. Decommission chassis
B. Reset CMOS
C. Remove chassis
D. Acknowledge chassis
Answer: A
Explanation:
Explanation/Reference:
Reference:
http://www.cisco.com/c/en/us/td/docs/unified_computing/ucs/sw/gui/config/guide/2-2/ b_UCSM_GUI_Configuration_Guide_2_2/managing_the_chassis.html#task_EB93895D63664D
86ACDE9D13C222A452
NEW QUESTION: 3
A company named Fabricam, Inc, has a web app hosted in Microsoft Azure. Millions of users visit the app daily.
All of the user visits are logged in Azure Blob storage. Data analysts at Fabrikam built a dashboard that processes the user visit logs.
Fabrikam plans to use an Apache Hadoop cluster on Azure HDInsight to process queries. The queries will access the data only once.
You need to recommend a query execution strategy.
What is the best to recommend using to achieve the goal?
More than one answer choice may achieve the goal. Select the BEST answer.
A. Load the text files to parquet files, and then run dashboard queries on the parquet files.
B. Run the queries on the text files directly.
C. Load the text files to ORC files, and then run dashboard queries on the ORC files.
D. Load the text files to sequence files, and then run dashboard queries on the sequence files.
Answer: D
Explanation:
Explanation/Reference:
Explanation:
File format versatility and Intelligent caching: Fast analytics on Hadoop have always come with one big catch: they require up-front conversion to a columnar format like ORCFile, Parquet or Avro, which is time- consuming, complex and limits your agility.
With Interactive Query Dynamic Text Cache, which converts CSV or JSON data into optimized in-memory format on-the-fly, caching is dynamic, so the queries determine what data is cached. After text data is cached, analytics run just as fast as if you had converted it to specific file formats.
References: https://azure.microsoft.com/en-us/blog/azure-hdinsight-interactive-query-simplifying-big-data- analytics-architecture-and-operations/