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NEW QUESTION: 1
An administrator has installed a View security server and needs to verify that the installation was successful.
In addition to the security server, which three services should be installed? (Choose three.)
A. VMware View Framework
B. VMware View Framework Gateway
C. VMware View PCoIP Secure Gateway
D. VMware View Security Framework
E. VMware View Security Gateway
Answer: A,C,E

NEW QUESTION: 2
新しい訪問者が、 "ウェブサイトの追跡"に設定されているPardotキャンペーンのあるページに表示されます。 それから訪問者はいっぱいになります。
Pardotキャンペーンを「お問い合わせ」に設定したフォームを作成します。 フォームを送信してコンバージョンしたPardotキャンペーンは、どの訪問者に関連付けられますか。
A. 「お問い合わせ」
B. 「ウェブサイトトラッキング」と「お問い合わせ」の両方
C. 訪問者が不明なため、キャンペーンは割り当てられません。
D. 「ウェブサイトの追跡」
Answer: A

NEW QUESTION: 3
To process input key-value pairs, your mapper needs to load a 512 MB data file in memory. What is the best way to accomplish this?
A. Place the data file in theDistributedCacheand read the data into memory in the map method of the mapper.
B. Serialize the data file, insert it in the Jobconf object, and read the data into memory in the configure method of the mapper.
C. Place the data file in theDistributedCacheand read the data into memory in the configure method of the mapper.
D. Place the datafile in the DataCache and read the data into memory in the configure method ofthe mapper.
Answer: A
Explanation:
Hadoop has a distributed cache mechanism to make available file locally that may be needed by Map/Reduce jobs
Use Case
Lets understand our Use Case a bit more in details so that we can follow-up the code snippets. We have a Key-Value file that we need to use in our Map jobs. For simplicity, lets say we need to replace all keywords that we encounter during parsing, with some other value.
So what we need is
A key-values files (Lets use a Properties files) The Mapper code that uses the code
Write the Mapper code that uses it
view sourceprint?
01.
public class DistributedCacheMapper extends Mapper<LongWritable, Text, Text, Text> {
02.
03.
Properties cache;
04.
05.
@Override
06.
protected void setup(Context context) throws IOException, InterruptedException {
07.
super.setup(context);
08.
Path[] localCacheFiles = DistributedCache.getLocalCacheFiles(context.getConfiguration());
09.
10.
if(localCacheFiles != null) {
11.
// expecting only single file here
12.
for (int i = 0; i < localCacheFiles.length; i++) {
13.
Path localCacheFile = localCacheFiles[i];
14.
cache = new Properties();
15.
cache.load(new FileReader(localCacheFile.toString()));
16.
}
17.
} else {
18.
// do your error handling here
19.
}
20.
21.
}
22.
23.
@Override
24.
public void map(LongWritable key, Text value, Context context) throws IOException,
InterruptedException {
25.
// use the cache here
26.
// if value contains some attribute, cache.get(<value>)
27.
// do some action or replace with something else
28.
}
29.
30.
}
Note:
* Distribute application-specific large, read-only files efficiently.
DistributedCache is a facility provided by the Map-Reduce framework to cache files (text, archives, jars etc.) needed by applications.
Applications specify the files, via urls (hdfs:// or http://) to be cached via the JobConf. The DistributedCache assumes that the files specified via hdfs:// urls are already present on the FileSystem at the path specified by the url.
Reference:Using Hadoop Distributed Cache