Exam Name: Hortonworks Data Platform Certified Developer
Certification Provider: Hortonworks
Corresponding Certification: HDP Certified Developer
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Instant Download Hortonworks : HDPCD Questions & Answers as PDF & Test Engine
Updated: Sep 05, 2026
No. of Questions: 110 Questions & Answers with Testing Engine
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- Total Questions: 110
- Updated on: Sep 05, 2026
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- Total Questions: 110
- Updated on: Sep 05, 2026
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PDF Practice Q&A's
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- Total Questions: 110
- Updated on: Sep 05, 2026
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Hortonworks Data Platform Certified Developer can feel demanding because it measures both knowledge recall and practical decision-making. With 110 HDPCD practice questions from Actual4dump, you can turn a broad syllabus into repeated, manageable review sessions.
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Hortonworks HDPCD Exam Overview:
| Certification Vendor: | Hortonworks |
|---|---|
| Exam Name: | Hortonworks Data Platform Certified Developer |
| Exam Number: | HDPCD |
| Available Languages: | English |
| Exam Price: | 250 USD |
| Exam Format: | Performance-based, hands-on tasks on a live HDP cluster |
| Related Certifications: | Hortonworks Certified Administrator (HDPCA) HDP Certified Java Developer (HDPCD:Java) Hortonworks Certified Associate (HCA) |
| Passing Score: | Varies (based on number of tasks; passing criteria appears in exam instructions) |
| Exam Duration: | 120 minutes |
| Real Exam Qty: | N/A (performance-based tasks, typically 7–10 tasks) |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online (remote proctored) using a live HDP cluster |
| Pre Condition: | Experience with Hadoop, HDFS, Pig, Hive, Sqoop, Flume; ability to perform practical tasks on HDP cluster |
| Official Syllabus URL: | https://hortonworks.com/training/class/hdp-certified-developer-hdpcd-exam/ |
Hortonworks HDPCD Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Transformation | - Write and execute Hive queries - Write and execute Pig scripts |
| Data Ingestion | - Import data into HDFS using tools like Sqoop/Flume |
| Data Analysis | - Analyze data using Hadoop ecosystem tools |
FAQs for Hortonworks Data Platform Certified Developer Candidates
The HDPCD exam leads to the HDP Certified Developer certification from Hortonworks. It is positioned at the Professional level. The exam validates the knowledge and skills expected of candidates preparing for Hortonworks Data Platform Certified Developer.
Related certifications include:
- Hortonworks Certified Administrator (HDPCA)
- Hortonworks Certified Associate (HCA)
- HDP Certified Java Developer (HDPCD:Java)
The HDPCD exam includes N/A (performance-based tasks, typically 7–10 tasks) questions and allows 120 minutes. Before test day, divide the available time by the number of questions in a timed practice set to establish a steady per-question pace. If a difficult item starts consuming too much time, mark it for review and move forward instead of losing momentum. A full timed practice session can help you decide when to move on, when to return, and how much buffer to reserve for a final check.
The passing score for HDPCD is Varies (based on number of tasks; passing criteria appears in exam instructions), and the official exam fee is 250 USD. Because a retake requires paying the exam fee again, use timed practice results as a readiness check before scheduling your next attempt. If your performance remains inconsistent, continue reviewing weak domains and repeat a timed session before booking the exam.
Experience with Hadoop, HDFS, Pig, Hive, Sqoop, Flume; ability to perform practical tasks on HDP cluster
Eligibility rules can change, so confirm the current requirements on the official exam page before registering.
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If you purchase the corresponding HDPCD preparation material and do not pass that exam within 60 days of purchase, you may apply for a full refund under the 100% Money Back Guarantee. The request requires a scanned exam enrollment slip and the official Score Report PDF, submitted within two days after the exam. Eligible requests are processed within seven days.
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The current HDPCD outline is organized into 3 top-level domains. The first listed areas include:
- Data Transformation
- Data Analysis
- Data Ingestion
Review the Exam Topics section above for the complete outline and any nested subtopics.
Hortonworks Data Platform Certified 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. JSON
- B. Avro
- C. XML
- D. SequenceFiles
- E. CSV
- F. HTML
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You need to move a file titled "weblogs" into HDFS. When you try to copy the file, you can't. You know you have ample space on your DataNodes. Which action should you take to relieve this situation and store more files in HDFS?
- A. Increase the number of disks (or size) for the NameNode.
- B. Increase the block size on your remaining files.
- C. Decrease the block size on all current files in HDFS.
- D. Decrease the block size on your remaining files.
- E. Increase the amount of memory for the NameNode.
- F. Increase the block size on all current files in HDFS.
A combiner reduces:
- A. The amount of intermediate data that must be transferred between the mapper and reducer.
- B. The number of input files a mapper must process.
- C. The number of output files a reducer must produce.
- D. The number of values across different keys in the iterator supplied to a single reduce method call.
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In the reducer, the MapReduce API provides you with an iterator over Writable values. What does calling the next () method return?
- A. It returns a reference to the same Writable object if the next value is the same as the previous value, or a new Writable object otherwise.
- B. It returns a reference to a different Writable object time.
- C. It returns a reference to the same Writable object each time, but populated with different data.
- D. It returns a reference to a Writable object from an object pool.
- E. It returns a reference to a Writable object. The API leaves unspecified whether this is a reused object or a new object.
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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 amount of free disk space on the TaskTracker node.
- B. The average system load on the TaskTracker node over the past fifteen (15) minutes.
- C. The amount of RAM installed on the TaskTracker node.
- D. The number and speed of CPU cores on the TaskTracker node.
- E. The location of the InsputSplit to be processed in relation to the location of the node.
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