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NEW QUESTION: 1
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 datafile in the DataCache and read the data into memory in the configure method ofthe 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 map method of the mapper.
D. Place the data file in theDistributedCacheand read the data into memory in the configure method of the mapper.
Answer: C
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

NEW QUESTION: 2
회사는 선입 선출 (FIFO) 방법을 사용하는 프로세스 비용 시스템을 사용합니다. 제품은 완료하기 위해 부서 1과 부서 2를 모두 통과합니다.
부서 1에서 완료되면 장치가 부서 2에 들어갑니다. 단위가 전환 비용과 관련하여 완료 단계 25 %에 도달하면 부서 2에 추가 직접 재료가 추가됩니다. 전환 비용은 부서 2에 비례하여 추가됩니다.
이번 달 2 부서의 생산 활동은 다음과 같습니다.

이번 달에 부서 2에 직접 재료에 대한 동등한 단위가 몇 개나 추가 되었습니까?
A. 70,000 대
B. 85,000 대.
C. 95.000 단위.
D. 80,000 대
Answer: A
Explanation:
Beginning inventory is 40% complete. Hence, direct materials have already been added. Ending inventory has not reached the 25% stage of completion, so direct materials have not yet been added to these units. Thus, the equivalent units for direct materials calculated on a FIFO basis are equal to the units started and completed in the current period 85.000 units completed - 15,000 units in BWIP = 70,000 units started and completed). A manufacturing company employs a process cost system. The company's product passes through both Department 1 and Department 2 in order to be completed. Conversion costs are incurred uniformly throughout the process in Department 2. The direct material is added in Department 2 when conversion is 80% complete. This direct material is a preservative that not change the volume. Spoiled units are discovered at the final inspection and are recognized then for sting purposes. The physical flow of units for the current month is presented below.

NEW QUESTION: 3
You notice a performance change in your production Oracle 12c database. You want to know which change caused this performance difference.
Which method or feature should you use?
A. AWR Compare Period report
B. Compare Period ADDM report
C. Active Session History (ASH) report
D. Taking a new snapshot and comparing it with a preserved snapshot
Answer: A
Explanation:
Explanation/Reference:
Explanation:
The awrddrpt.sql report is the Automated Workload Repository Compare Period Report. The awrddrpt.sql script is located in the $ORACLE_HOME/rdbms/admin directory.
Incorrect:
Not A: Compare Period ADDM
Use this report to perform a high-level comparison of one workload replay to its capture or to another replay of the same capture. Only workload replays that contain at least 5 minutes of database time can be compared using this report.