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Updated: Sep 13, 2026
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Hortonworks Apache-Hadoop-Developer Exam Overview:
| Certification Vendor: | Hortonworks |
|---|---|
| Exam Name: | Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer) |
| Exam Number: | HADOOP-PR000007 / HDPCD / Apache-Hadoop-Developer |
| Available Languages: | English |
| Passing Score: | 70% |
| Related Certifications: | Hortonworks Certified Associate (HCA) HDP Certified Administrator (HDPCA) |
| Exam Price: | $250 USD |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | 8–12 performance-based tasks / approx. 110 multiple-choice |
| Exam Format: | Scenario-based tasks, Performance-based hands-on tasks, Multiple-choice questions |
| Certificate Validity Period: | 2 years |
| Recommended Training: | Apache Pig & Hive Official Documentation Hortonworks Official Developer Training |
| Exam Registration: | Hortonworks Certification Portal |
| Sample Questions: | Hortonworks Apache-Hadoop-Developer Sample Questions |
| Exam Way: | Online proctored exam on a remote HDP 2.2 / 2.4 cluster |
| Pre Condition: | Recommended: 6+ months hands-on experience with HDP, Pig, Hive, Sqoop, Flume; no mandatory prerequisites |
| Official Syllabus URL: | https://hortonworks.com/services/training-certification/ (program retired) |
Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Ingestion | 25% | - Ingest streaming data with Flume - Load data into HDFS from external sources - Import/export data using Sqoop |
| Topic 2: Hadoop Fundamentals & Architecture | 20% | - YARN architecture and job execution - HDFS operations and file management - MapReduce concepts and job lifecycle |
| Topic 3: Apache Hive Development | 25% | - Use Hive functions, views, and metastore - Create and manage Hive tables, partitions, and buckets - Write and optimize HiveQL queries |
| Topic 4: Apache Pig Development | 30% | - Data transformation, filtering, joining, and aggregation - Debug and tune Pig jobs - Write and optimize Pig Latin scripts |
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
Which one of the following classes would a Pig command use to store data in a table defined in HCatalog?
- A. org.apache.hcatalog.pig.HCatOutputFormat
- B. No special class is needed for a Pig script to store data in an HCatalog table
- C. Pig scripts cannot use an HCatalog table
- D. org.apache.hcatalog.pig.HCatStorer
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. Disk I/O and network I/O
- B. Processor and network I/O
- C. Processor and RAM
- D. Processor and disk I/O
You have the following key-value pairs as output from your Map task:
(the, 1) (fox, 1) (faster, 1) (than, 1) (the, 1) (dog, 1)
How many keys will be passed to the Reducer's reduce method?
- A. One
- B. Five
- C. Six
- D. Two
- E. Four
- F. Three
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What is the term for the process of moving map outputs to the reducers?
- A. Partitioning
- B. Combining
- C. Shuffling and sorting
- D. Reducing
What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your workload across you cluster?
- A. You will longer be able to take advantage of a Combiner.
- B. By using multiple reducers with the default HashPartitioner, output files may not be in globally sorted order.
- C. There are no concerns with this approach. It is always advisable to use multiple reduces.
- D. You will not be able to compress the intermediate data.
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