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NEW QUESTION: 1
Refer to the Exhibit.

A company operates a FIFO system of inventory valuation. Opening inventory at the beginning of the period was 200 units @ £2.80 each. During the period the following movements of inventory were recorded.
The value of the closing inventory at the end of the period and amount charged to the income statement were:
A. Closing inventory £360.00 Income statement £1695.00
B. Closing inventory £360.00 Income statement £2255.00
C. Closing inventory £360.00 Income statement £1895.00
D. Closing inventory £357.50 Income statement £1897.50
Answer: D

NEW QUESTION: 2
A new MPLS network link has been established between a company and its business partner.
The link provides logical isolation in order to prevent access from other business partners. Which of the following should be applied in order to achieve confidentiality and integrity of all data across the link?
A. SSL/TLS for all application flows.
B. MPLS should be run in IPVPN mode.
C. HTTPS and SSH for all application flows.
D. IPSec VPN tunnels on top of the MPLS link.
Answer: D

NEW QUESTION: 3
A router is running three routing processes: RIP, OSPF, and EIGRP, each configured with default characteristics. Each process learns a route to the same remote network.
If there are no static routes to the destination and none of the routes were redistributed, which route will be placed in the IP routing table?
A. the route learned through OSPF
B. the route learned through RIP
C. the route learned through EIGRP
D. all three routes with the router load balancing
E. the route with the lowest metric
Answer: C
Explanation:
Reference:
http://www.cisco.com/en/US/tech/tk365/technologies_tech_note09186a0080094195.shtml
Administrative distance is the feature that routers use in order to select the best path.
Administrative distance defines the reliability of a routing protocol. Each routing protocol is prioritized in order of most to least reliable (believable) with the help of an administrative distance value. Lowest Administrative distance will be chosen first.

NEW QUESTION: 4
To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory. What is the best way to accomplish this?
A. Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.
B. Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.
C. Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper.
D. Place the data file in the DataCache and read the data into memory in the configure method of the mapper.
Answer: B
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