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NEW QUESTION: 1
IPアドレス10.10.10.10のユーザーは、Cisco ASAを介してIPアドレス209.165.200.225のHTTP Webサイトにアクセスできません。問題のトラブルシューティングに役立つ2つの機能とコマンドはどれですか？ （2つ選択してください。）
A. レベル1でロギングを有効にし、コマンドlogging enable、logging buffered 1およびshow logging | showコマンドを使用してsyslogを確認します。 10.10.10.10を含む
B. syslogまたはキャプチャを使用してユーザートラフィックがファイアウォールに到達することを確認した後、tcp 10.10.10.10 1234 209.165.200.225 80内でpacket tracerコマンドpacket-tracer inputを使用します。
C. udp 0.10.10.10 1234192.168.1.3 161内でパケットトレーサーコマンドpacket-tracer inputを使用して、ファイアウォールがユーザーのトラフィックで何をしているかを確認します。
D. コマンドshow running-config access-list |を使用して、ファイアウォールのアクセスリストがユーザーをブロックしているかどうかを確認します。 10.10.10.10を含む
E. match ip host 10.10.10.10 any内のコマンドキャプチャcapinインターフェイスを使用してユーザートラフィックをキャプチャします
Answer: B,E

NEW QUESTION: 2
You want an administrator that is excluded from the route map to make compensation recommendations. What feature allows this?
Please choose the correct answer.
Response:
A. Executive review
B. Ad hoc reporting
C. Compensation profile
D. New compensation worksheet
Answer: A

NEW QUESTION: 3
An architect must optimize the performance of the home page of a client's website.
The client requires that search engines index the home page content.
The home page must NOT be cacheable because it displays a list of recently shared articles.
This list is generated by using an AEM component that performs a real-time look-up to an API from a third-party company.
Which solution should the architect choose?
A. Replace the real-time API access with a scheduled job inside AEM that runs every 15 minutes to update the data and trigger a dispatcher cache flush
B. Cache the rest of the home page and deliver the recently shared article list using AJAX
C. Cache the home page using the Dispatcher and implement a cron job to remove the cached file every 15 minutes
D. Replace the AEM component's server-side logic with a JavaScript widget provided by the third p
Answer: D

NEW QUESTION: 4
Which MapReduce daemon instantiates user code, and executes map and reduce tasks on a cluster running MapReduce v1 (MRv1)?
A. TaskTracker
B. DataNode
C. ApplicationMaster
D. NodeManager
E. NameNode
F. JobTracker
G. ResourceManager
Answer: A
Explanation:
A TaskTracker is a slave node daemon in the cluster that accepts tasks (Map, Reduce and Shuffle operations) from a JobTracker. There is only One Task Tracker process run on any hadoop slave node. Task Tracker runs on its own JVM process. Every TaskTracker is configured with a set ofslots, these indicate the number of tasks that it can accept. The TaskTracker starts a separate JVM processes to do the actual work (called as Task Instance) this is to ensure that process failure does not take down the task tracker. The TaskTracker monitors these task instances, capturing the output and exit codes. When the Task instances finish, successfully or not, the task tracker notifies the JobTracker. The TaskTrackers also send out heartbeat messages to the JobTracker, usually every few minutes, to reassure the JobTracker thatit is still alive. Thesemessage also inform the JobTracker of the number of available slots, so the JobTracker can stay up to date with where in the cluster work can be delegated.
Note: How many Daemon processes run on a Hadoop system?
Hadoop is comprised of five separate daemons. Each of these daemon run in its own JVM. Following 3 Daemons run on Masternodes NameNode - This daemon stores and maintains the metadata for HDFS.
Secondary NameNode - Performs housekeeping functions for the NameNode.
JobTracker - Manages MapReduce jobs, distributes individual tasks to machines running the Task
Tracker.
Following 2 Daemons run on each Slave nodes
DataNode - Stores actual HDFS data blocks.
TaskTracker - Responsible for instantiating and monitoring individual Map and Reduce tasks.
Reference: 24 Interview Questions & Answers for Hadoop MapReduce developers, What is a
Task Tracker in Hadoop? How many instances of TaskTracker run on a Hadoop Cluster