Cloudera Hadoop Developer Certification Questions and Answer (Dumps and Practice Questions)
Question :
You have defined flume agent as a1, with following configuration
a1.channels = c1
a1.sinks = k1
a1.sinks.k1.type = hdfs
a1.sinks.k1.channel = c1
a1.sinks.k1.hdfs.path = /flume/events/%y-%m-%d/%H%M/%S
a1.sinks.k1.hdfs.filePrefix = events-
a1.sinks.k1.hdfs.round = true
a1.sinks.k1.hdfs.roundValue = 10
a1.sinks.k1.hdfs.roundUnit = minute
an event with timestamp 11:54:34 AM, June 12, 2012 will cause the hdfs path to become
1. /flume/events/2012-06-12/1150/00
2. /flume/events/2012-06-12/1200/00
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4. /flume/events/2012-06-12/1160/00
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The population in year 2001 = 2 * ((150*150 + 100*100) power 1/2) = 361
Explanation: The above configuration will round down the timestamp to the last 10th minute as round value set tp 10 and round unit is minute.
Question :
You have defined flume agent as a1, with following configuration
a1.channels = c1
a1.sinks = k1
a1.sinks.k1.type = hdfs
a1.sinks.k1.channel = c1
a1.sinks.k1.hdfs.path = /flume/events/%y-%m-%d/%H%M/%S
a1.sinks.k1.hdfs.filePrefix = events-
a1.sinks.k1.hdfs.round = true
a1.sinks.k1.hdfs.roundValue = 20
a1.sinks.k1.hdfs.roundUnit = minute
an event with timestamp 11:51:34 AM, June 12, 2012 and another event happens as 11:54:34 AM, June 12, 2012
So in which of the path the file will be stored
1. /flume/events/2012-06-12/1140/00
2. /flume/events/2012-06-12/1200/00
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4. /flume/events/2012-06-12/1160/00
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Explanation: The above configuration will round down the timestamp to the last 20th minute as round value set tp 20 and round unit is minute.
1. 1
2. 2
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Explanation: Reducer groups by key within the partition, hence it needs to use Partioner, Key Comparator as well as Group Comparator to implement Secondary Sort.
From the all 4 option best fit comparator is 2nd one which compares the first part (year) in the reducer it will be in the same group. And letter on on the
secomd part you can make sorting using KeyComprator.
We must now ensure that all the values for the same natural key are passed in one call to the Reducer
Achieved by defining a Grouping Comparator class
Determines which keys and values are passed in a single call to the Reducer
Looks at just the natural key
Grouping comparators can be used in a secondary sort to ensure that only the natural key is used for partitioning and grouping
Question :
There are two input files as belwo to MapReduce Join job.
input/A
A.a11 A.a12
A.a21 A.a22
B.a21 A.a32
A.a31 A.a32
B.a31 A.a32
input/B
A.a11 B.a12
A.a11 B.a13
B.a11 B.a12
B.a21 B.a22
A.a31 B.a32
B.a31 B.a32
After running the MapReduce join code snippet(Left Hand Side)
What would be the first line of the output
1. A.a11 A.a12 B.a12
2. A.a11 A.a12 A.a11 B.a13
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4. B.a21 A.a32 B.a21 B.a22
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Related Questions
Question : Select the correct statement ?
1. Block size is usually 64 MB or 128 MB
2. Blocks are replicated across multiple machine
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4. All of the above
Question : Which is the master node for tracking the files block in HDFS ?
1. JOBTracker
2. DataNode
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4. DataMasteNode
Question : Select the correct options
1. NameNode store the metadata for the files
2. DataNode holds the actual blocks
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4. All of the above
5. 1 and 2 are correct
Question : Select the correct statement for the NameNode ?
1. NameNode daemon must be running at all the times
2. NameNode holds all its metadata in RAM for fast access.
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4. 1,2 and 3 are correct
5. 1 and 2 are correct
Question : If NameNode stops, the cluster becomes inaccessible ?
1. True
2. Flase
Question : Secondary NameNode is a backup for NameNode ?
1. True
2. False