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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Apache Pig Development | 40% | - Integration with HCatalog and Hive - Pig Latin syntax, data loading, and storage - Data transformation, filtering, grouping, and joining - User-defined functions (UDFs) and optimization |
| Apache Hive Development | 35% | - HiveQL queries, joins, aggregations, and partitioning - Hive architecture, metastore, and table management - Performance tuning and indexing - Data types, serialization, and file formats |
| Data Ingestion & Ecosystem Integration | 5% | - Workflow orchestration with Oozie - Sqoop and Flume usage basics |
| Hadoop Fundamentals & HDFS | 20% | - Hadoop 2.0 architecture & YARN - HDFS file operations, permissions, and data management |
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
1. Given the following Pig commands:
Which one of the following statements is true?
A) The $1 variable represents the second column of data in 'my.log'
B) The severe relation is not valid
C) The grouped relation is not valid
D) The $1 variable represents the first column of data in 'my.log'
2. In a MapReduce job with 500 map tasks, how many map task attempts will there be?
A) Between 500 and 1000.
B) It depends on the number of reduces in the job.
C) Exactly 500.
D) At most 500.
E) At least 500.
3. On a cluster running MapReduce v1 (MRv1), a TaskTracker heartbeats into the JobTracker on your
cluster, and alerts the JobTracker it has an open map task slot.
What determines how the JobTracker assigns each map task to a TaskTracker?
A) The location of the InsputSplit to be processed in relation to the location of the node.
B) The amount of free disk space on the TaskTracker node.
C) The amount of RAM installed on the TaskTracker node.
D) The average system load on the TaskTracker node over the past fifteen (15) minutes.
E) The number and speed of CPU cores on the TaskTracker node.
4. You need to create a job that does frequency analysis on input data. You will do this by writing a Mapper
that uses TextInputFormat and splits each value (a line of text from an input file) into individual characters.
For each one of these characters, you will emit the character as a key and an InputWritable as the value.
As this will produce proportionally more intermediate data than input data, which two resources should
you expect to be bottlenecks?
A) Processor and RAM
B) Processor and disk I/O
C) Processor and network I/O
D) Disk I/O and network I/O
5. Review the following data and Pig code:
What command to define B would produce the output (M,62,95l02) when invoking the DUMP operator on
B?
A) B= GROUP A BY (zip = = '95102' AND gender = = 'M');
B) B = FILTER A BY (zip = = '95102' AND gender = = M");
C) B= FOREACH A BY (gender = = 'M' AND zip = = '95102');
D) B = JOIN A BY (gender = = 'M' AND zip = = '95102');
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: E | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: B |





