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NEW QUESTION: 1
What command visualizes the general NetFlow data on the command line?
A. show ip cache flow
B. show ip flow top-talkers
C. show mls netflow ip
D. show ip flow export
E. show mls sampling
Answer: A
Explanation:
The following is an example of how to visualize the NetFlow data using the CLI. There are three methods to visualize the data depending on the version of Cisco IOS Software. The traditional show command for NetFlow is "show ip cache flow" also available are two forms of top talker commands. One of the top talkers commands uses a static configuration to view top talkers in the network and another command called dynamic top talkers allows real-time sorting and aggregation of NetFlow data. Also shown is a show MLS command to view the hardware cache on the Cisco Catalyst 6500 Series Switch.
The following is the original NetFlow show command used for many years in Cisco IOS Software.
Information provided includes packet size distribution; basic statistics about number of flows and export timer setting, a view of the protocol distribution statistics and the NetFlow cache.
R3#show ip cache flow
IP packet size distribution (469 total packets):
1-32 64 96 128 160 192 224 256 288 320 352 384 416 448
480 .000 .968 .000 .031 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 512 544 576
1024 1536 2048 2560 3072 3584 4096 4608
.000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 IP Flow Switching Cache, 278544 bytes 7 active, 4089 inactive, 261 added
1278 ager polls, 0 flow alloc failures Active flows timeout in 30 minutes Inactive flows timeout in
15 seconds IP Sub Flow Cache, 25736 bytes
1 active, 1023 inactive, 38 added, 38 added to flow 0 alloc failures, 0 force free 1 chunk, 1 chunk added last clearing of statistics never Protocol Total Flows Packets Bytes Packets Active(Sec) Idle(Sec) -------- Flows /Sec /Flow /Pkt
/Sec /Flow /Flow TCP-WWW 71 0.0 1 40 0.1 1.3 1.2 TCP-BGP 35 0.0 1 40 0.0 1.3 1.2 TCP-other
108 0.1 1 40 0.1 1.3 1.2 UDP-other 37 0.0 1 52 0.0 0.0 15.4 ICMP 3 0.0 5 100 0.0 0.0 15.3 Total:
254 0.2 1 42 0.4 1.1 3.5 (NetFlow cache below) SrcIf SrcIPaddress DstIf DstIPaddress Pr SrcP DstP Pkts Et1/0 172.16.7.2 Null 224.0.0.9 11 0208 0208 1 Et1/0 172.16.10.2 Et0/0 172.16.1.84
06 0087 0087 1
Et1/0 172.16.10.2 Et0/0 172.16.1.84 06 0050 0050 1
Et1/0 172.16.10.2 Et0/0 172.16.1.85 06 0089 0089 1
Et1/0 172.16.10.2 Et0/0 172.16.1.85 06 0050 0050 1
Et1/0 172.16.10.2 Et0/0 172.16.1.86 06 00B3 00B3 1
Et1/0 172.16.10.2 Et0/0 172.16.1.86 06 0185 0185 2
http://www.cisco.com/c/en/us/products/collateral/ios-nx-os-software/ios- netflow/prod_white_paper0900aecd80406232.html

NEW QUESTION: 2
You have a computer named Computer1 that runs Windows 10 Enterprise. You add a 1 TB hard drive and create a new volume that has the drive letter D.
You need to limit the amount of space that each user can consume on D: to 200 GB. Members of the Administrators group should have no limit.
Which three actions should you perform? Each correct answer presents part of the solution.
A. Enable the Deny disk space to users exceeding quota limit setting.
B. Set a default quota limit.
C. Enable the Enable Quota Management setting.
D. Run convert D: /FS:NTFS.
E. Add a quota entry.
F. Runfsutil quota violations D:
Answer: A,B,C
Explanation:
To limit the amount of space that each user can consume, you should enable the Enable Quota Management setting, and then enter the appropriate values in the Limit Disk Space To text box and the Set Warning Level To text box, and then select the Deny Disk Space To Users Exceeding Quota Limit check box to enforce identical quota limits for all users.
References:

NEW QUESTION: 3
You are designing a solution that will ingest data from an Azure loT Edge device, preprocess the data in Azure Machine Learning, and then move the data to Azure HDInsight for further processing.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Export Data
The Export data to Hive option in the Export Data module in Azure Machine Learning Studio. This option is useful when you are working with very large datasets, and want to save your machine learning experiment data to a Hadoop cluster or HDInsight distributed storage.
Box 2: Apache Hive
Apache Hive is a data warehouse system for Apache Hadoop. Hive enables data summarization, querying, and analysis of data. Hive queries are written in HiveQL, which is a query language similar to SQL.
Box 3: Azure Data Lake
Default storage for the HDFS file system of HDInsight clusters can be associated with either an Azure Storage account or an Azure Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-to-hive-query
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/hdinsight-use-hive

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