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NEW QUESTION: 1
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. Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.
B. Place the data file in the DataCache and read the data into memory in the configure 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. Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.
Answer: A
Explanation:
Explanation/Reference:
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

NEW QUESTION: 2
You have a Power BI model for sales data. You create a measure to calculate the year-to-date sales.
You need to compare the year-to-date sales with the previous year for the same time period.
Which DAX function should you use?
A. ENDOFYEAR
B. DATEADD
C. TOTALYTD
D. DATESYTD
Answer: D
Explanation:
https://powerpivotpro.com/2016/01/year-to-date-in-previousprior-year/

NEW QUESTION: 3
HOTSPOT


Answer:
Explanation:

NEW QUESTION: 4
Which of the following layer data stores a layer comp for each layer?
Each correct answer represents a part of the solution. Choose three.
A. Layer visibility
B. Layer Mask
C. Layer's appearance
D. Layer position
Answer: A,C,D
Explanation:
Explanation/Reference:
Answer options C, A, and B are correct.
You can use the Layer Comps panel to store comps of an image. Each layer comp is a snapshot of the Layers panel in a specified state. A layer comp stores three types of layer data for each layer:
Layer visibility

Layer position (The position of layer content in the image)

Layer's appearance (style and blending mode)

If you have created layer groups for an image, each layer comp can contain some, all, or none of those layer groups.
Answer option D is incorrect. Layer masks are resolution-dependent bitmap images that are edited with the painting or selection tools.