Cloudera Hadoop Developer Certification Questions and Answer (Dumps and Practice Questions)
Question :
Let's assume you have following files in the hdfs directory called merge.
Test1.txt
hadoopexam.com Hadoop Training 1
Test2.txt
www.hadoopexam.com Hadoop YARN Training
Test3.txt
http://hadoopexam.com Amazon WebService Training
Now you run the following command
hadoop fs -getmerge merge/ output1.txt
What is the content in the output1.txt file
1.
hadoopexam.com Hadoop Training 1
www.hadoopexam.com Hadoop YARN Training
http://hadoopexam.com Amazon WebService Training
2.
www.hadoopexam.com Hadoop YARN Training
hadoopexam.com Hadoop Training 1
http://hadoopexam.com Amazon WebService Training
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It could be any random order
4.
www.hadoopexam.com Hadoop YARN Traininghadoopexam.com Hadoop Training 1http://hadoopexam.com Amazon WebService Training
Correct Answer : Get Lastest Questions and Answer :
getmerge
Usage: hadoop fs -getmerge (src) (localdst) [addnl]
Takes a source directory and a destination file as input and concatenates files in src into the destination local file. Optionally addnl can be set to enable adding a newline character at the end of each file.
Question :
Let's assume you have following files in the hdfs directory called merge.
Test1.txt
hadoopexam.com Hadoop Training 1
Test2.txt
www.hadoopexam.com Hadoop YARN Training
Test3.txt
http://hadoopexam.com Amazon WebService Training
Now you run the following command
hadoop fs -getmerge -nl merge/ output2.txt
What is the content in the output2.txt file
1.
hadoopexam.com Hadoop Training 1
www.hadoopexam.com Hadoop YARN Training
http://hadoopexam.com Amazon WebService Training
2.
hadoopexam.com Hadoop Training 1
www.hadoopexam.com Hadoop YARN Training
http://hadoopexam.com Amazon WebService Training
3. Access Mostly Uused Products by 50000+ Subscribers
4. www.hadoopexam.com Hadoop YARN Traininghadoopexam.com Hadoop Training 1http://hadoopexam.com Amazon WebService Training
Correct Answer : Get Lastest Questions and Answer :
getmerge
Usage: hadoop fs -getmerge (src) (localdst) [addnl]
Takes a source directory and a destination file as input and concatenates files in src into the destination local file. Optionally addnl can be set to enable adding a newline character at the end of each file.
"nl" option will add additional new line after each line in the file.
Question :
In the regular WordCount MapReduce example, you have following driver code
public class WordCount extends Configured implements Tool {
public static void main(String args[]) throws Exception {
int res = ToolRunner.run(new WordCount(), args);
System.exit(res);
}
public int run(String[] args) throws Exception {
Path inputPath = new Path("shakespeare1");
Path outputPath = new Path(""+System.currentTimeMillis());
Configuration conf = getConf();
Job job = new Job(conf, this.getClass().toString());
FileInputFormat.setInputPaths(job, inputPath);
FileOutputFormat.setOutputPath(job, outputPath);
job.setJobName("WordCount");
job.setJarByClass(WordCount.class);
job.setJarByClass(WordCount.class);
job.setJobName("Word Count");
job.setMapperClass(WordMapper.class);
job.setReducerClass(SumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setNumReduceTasks(2);
return job.waitForCompletion(true) ? 0 : 1;
}}
Now you run the below command on a single node cluste. Where wc.jar is jar file containing Driver,Mapper and Reducer class.
hadoop jar wc.jar WordCount
Select the correct statement from below.
1. It will run 2 Mapper and 2 Reducer
2. It will run 2 Reducer, but number of Mapper is not known.
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4. There is not enough information to tell number of reducer.
Correct Answer : Get Lastest Questions and Answer :
As you can see in the driver code it has been defined that there would be job.setNumReduceTasks(2);
Total two reducer will be executed.
Related Questions
Question :
You have following data in a hive table
ID:INT,COLOR:TEXT,WIDTH:INT
1,green,190
2,blue,300
3,yellow,299
4,blue,199
5,green,199
6,yellow,299
7,green,799
Select the correct MapReduce program which can produce the output similar to below Hive Query.
Select color from table group by color Having SUM(WIDTH)>600;
1. 1
2. 2
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Question : You have following data in a hive table
ID:INT,COLOR:TEXT,WIDTH:INT
1,green,190
2,blue,300
3,yellow,299
4,blue,199
5,green,199
6,yellow,299
7,green,799
Select the correct MapReduce program which can produce the output similar to below Hive Query.
Select color from table group by color DESC Having SUM(WIDTH)>600;
1. 1
2. 2
3. Access Mostly Uused Products by 50000+ Subscribers
Question :
You have following data in a hive table
ID:INT,COLOR:TEXT,WIDTH:INT
1,green,190
2,blue,300
3,yellow,299
4,blue,199
5,green,199
6,yellow,299
7,green,799
Select the correct MapReduce program which can produce the output similar to below Hive Query.
Select color,sum(width) from table group by color order by color desc;
1. 1
2. 2
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Question :
You have following data in a hive table
ID:INT,COLOR:TEXT,WIDTH:INT
1,green,190
2,blue,300
3,yellow,299
4,blue,199
5,green,199
6,yellow,299
7,green,799
8,red,800
Select the correct MapReduce program which can produce the output similar to below Hive Query.
Select `(green|blue)?+.+` from table;
1. 1
2. 2
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4. 4
Question : You have following data in a Hive table, assuming based on the tag you want to join the data
colortable,1,pink,300
colortable,2,red,500
colortable,3,yellow,300
flowertable,1,rose
flowertable,2,amaryllis
flowertable,3,sunflower
flowertable,4,lily
flowertable,5,cosmos
And produce the output as below hive query.
Select color,flower from colortable join flowertable ON (colortable.id=flowertable.id)
Select the correct MapReduce program which produces the output as above query.
1. 1
2. 2
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Question :
1. 1
2. 2
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