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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Hadoop Fundamentals & Architecture | 20% | - HDFS operations and file management - YARN architecture and job execution - MapReduce concepts and job lifecycle |
| Topic 2: Data Ingestion | 25% | - Load data into HDFS from external sources - Import/export data using Sqoop - Ingest streaming data with Flume |
| Topic 3: Apache Pig Development | 30% | - Data transformation, filtering, joining, and aggregation - Debug and tune Pig jobs - Write and optimize Pig Latin scripts |
| Topic 4: Apache Hive Development | 25% | - Write and optimize HiveQL queries - Use Hive functions, views, and metastore - Create and manage Hive tables, partitions, and buckets |
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
Question 1
Which describes how a client reads a file from HDFS?
A. The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then from the NameNode to the client.
B. The client queries the NameNode for the block location(s). The NameNode returns the block location(s) to the client. The client reads the data directory off the DataNode(s).
C. The client contacts the NameNode for the block location(s). The NameNode then queries the DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects the client to the DataNode that holds the requested data block(s). The client then reads the data directly off the DataNode.
D. The client queries all DataNodes in parallel. The DataNode that contains the requested data responds directly to the client. The client reads the data directly off the DataNode.
Question 2
MapReduce v2 (MRv2/YARN) is designed to address which two issues?
A. Reduce complexity of the MapReduce APIs.
B. HDFS latency.
C. Single point of failure in the NameNode.
D. Standardize on a single MapReduce API.
E. Resource pressure on the JobTracker.
F. Ability to run frameworks other than MapReduce, such as MPI.
Question 3
Given the following Pig commands:
Which one of the following statements is true?
A. The grouped relation is not valid
B. The $1 variable represents the first column of data in 'my.log'
C. The severe relation is not valid
D. The $1 variable represents the second column of data in 'my.log'
Question 4
Examine the following Hive statements:
Assuming the statements above execute successfully, which one of the following statements is true?
A. The contents of File1 are parsed as comma-delimited rows and stored in a database
B. The contents of File1 are parsed as comma-delimited rows and loaded into /user/joe/x/
C. Hive reformats File1 into a structure that Hive can access and moves into to/user/joe/x/
D. The file named File1 is moved to to/user/joe/x/
Question 5
Given a directory of files with the following structure: line number, tab character, string:
Example:
1abialkjfjkaoasdfjksdlkjhqweroij
2kadfjhuwqounahagtnbvaswslmnbfgy
3kjfteiomndscxeqalkzhtopedkfsikj
You want to send each line as one record to your Mapper. Which InputFormat should you use to complete the line: conf.setInputFormat (____.class) ; ?
A. SequenceFileInputFormat
B. BDBInputFormat
C. SequenceFileAsTextInputFormat
D. KeyValueFileInputFormat
Solutions:
| Question 1 Answer: B | Question 2 Answer: C,E | Question 3 Answer: D | Question 4 Answer: D | Question 5 Answer: D |
