Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
Certification Provider: Hortonworks
Corresponding Certification: HCAHD
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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Analysis with Hive | - Hive query development
|
| Topic 2: Data Processing | - End-to-end Hadoop workflows
|
| Topic 3: Data Transformation with Pig | - Pig Latin programming
|
| Topic 4: Data Ingestion | - Import data into Hadoop
|
Your Hortonworks Apache-Hadoop-Developer Questions, Answered
The Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer blueprint divides into 4 domains — including Data Ingestion, Data Processing, Data Transformation with Pig. Those weights tell you where the points live; plan revision time in the same proportions. The full subtopic list appears above.
No mandatory prerequisite exam. Candidates are expected to have practical experience with Hortonworks Data Platform, Pig, Hive, Sqoop and Flume. Eligibility rules change occasionally, so confirm them on the official page (official Apache-Hadoop-Developer exam page) before booking.
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The Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer is Hortonworks's official exam for the HCAHD credential (Professional level). In the job market it works as portable proof of skill — more interviews, better offers. It pairs naturally with HDP Certified Developer (HDPCD), HDP Certified Administrator (HDPCA), HDP Certified Java Developer.
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Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
You want to perform analysis on a large collection of images. You want to store this data in HDFS and process it with MapReduce but you also want to give your data analysts and data scientists the ability to process the data directly from HDFS with an interpreted high-level programming language like Python. Which format should you use to store this data in HDFS?
- A. SequenceFiles
- B. CSV
- C. XML
- D. HTML
- E. Avro
- F. JSON
Correct Answer: E 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
Assuming default settings, which best describes the order of data provided to a reducer's reduce method:
- A. The keys given to a reducer aren't in a predictable order, but the values associated with those keys always are.
- B. Neither keys nor values are in any predictable order.
- C. The keys given to a reducer are in sorted order but the values associated with each key are in no predictable order
- D. Both the keys and values passed to a reducer always appear in sorted order.
Correct Answer: C 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?
- A. Combiner <Text, IntWritable, Text, IntWritable>
- B. Mapper <Text, IntWritable, Text, IntWritable>
- C. Combiner <Text, Text, IntWritable, IntWritable>
- D. Reducer <Text, IntWritable, Text, IntWritable>
- E. Reducer <Text, Text, IntWritable, IntWritable>
Correct Answer: D 🗳️
You need to run the same job many times with minor variations. Rather than hardcoding all job configuration options in your drive code, you've decided to have your Driver subclass org.apache.hadoop.conf.Configured and implement the org.apache.hadoop.util.Tool interface.
Indentify which invocation correctly passes.mapred.job.name with a value of Example to Hadoop?
- A. hadoop MyDrive -D mapred.job.name=Example input output
- B. hadoop setproperty mapred.job.name=Example MyDriver input output
- C. hadoop setproperty ("mapred.job.name=Example") MyDriver input output
- D. hadoop "mapred.job.name=Example" MyDriver input output
- E. hadoop MyDriver mapred.job.name=Example input output
Correct Answer: A 🗳️
Explanation: Only visible for PremiumVCEDump members. You can sign-up / login (it's free).
Which one of the following statements is false about HCatalog?
- A. Stores HDFS data in a database for performing SQL-like ad-hoc queries
- B. Exists as a subproject of Hive
- C. Designed to be used by other programs such as Pig, Hive and MapReduce
- D. Provides a shared schema mechanism
Correct Answer: A 🗳️
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