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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Hadoop Ecosystem Fundamentals | - HDFS Architecture and Data Storage Concepts
|
| Topic 2: Apache Hive | - HiveQL Query Language
|
| Topic 3: Apache Pig | - Pig execution model
|
| Topic 4: Data Processing and Integration | - Data ingestion and ETL workflows
|
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
You want to understand more about how users browse your public website, such as which pages they visit prior to placing an order. You have a farm of 200 web servers hosting your website. How will you gather this data for your analysis?
- A. Channel these clickstreams inot Hadoop using Hadoop Streaming.
- B. Ingest the server web logs into HDFS using Flume.
- C. Import all users' clicks from your OLTP databases into Hadoop, using Sqoop.
- D. Write a MapReduce job, with the web servers for mappers, and the Hadoop cluster nodes for reduces.
- E. Sample the weblogs from the web servers, copying them into Hadoop using curl.
Correct Answer: B 🗳️
Which two of the following statements are true about Pig's approach toward data? Choose 2 answers
- A. Accepts any data: structured or unstructured
- B. Accepts tab-delimited text data only
- C. Accepts only data that is defined by metadata tables stored in a database
- D. Accepts data whether it has metadata or not
- E. Accepts only data that has a key/value pair structure
Correct Answer: A,D 🗳️
Which process describes the lifecycle of a Mapper?
- A. The TaskTracker spawns a new Mapper to process each key-value pair.
- B. The TaskTracker spawns a new Mapper to process all records in a single input split.
- C. The JobTracker calls the TaskTracker's configure () method, then its map () method and finally its close () method.
- D. The JobTracker spawns a new Mapper to process all records in a single file.
Correct Answer: B 🗳️
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Your client application submits a MapReduce job to your Hadoop cluster. Identify the Hadoop daemon on which the Hadoop framework will look for an available slot schedule a MapReduce operation.
- A. Secondary NameNode
- B. DataNode
- C. NameNode
- D. JobTracker
- E. TaskTracker
Correct Answer: D 🗳️
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MapReduce v2 (MRv2/YARN) is designed to address which two issues?
- A. Single point of failure in the NameNode.
- B. HDFS latency.
- C. Ability to run frameworks other than MapReduce, such as MPI.
- D. Reduce complexity of the MapReduce APIs.
- E. Resource pressure on the JobTracker.
- F. Standardize on a single MapReduce API.
Correct Answer: A,E 🗳️
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