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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Apache Hive Development | 25% | - Use Hive functions, views, and metastore - Create and manage Hive tables, partitions, and buckets - Write and optimize HiveQL queries |
| Data Ingestion | 25% | - Import/export data using Sqoop - Load data into HDFS from external sources - Ingest streaming data with Flume |
| Hadoop Fundamentals & Architecture | 20% | - YARN architecture and job execution - MapReduce concepts and job lifecycle - HDFS operations and file management |
| Apache Pig Development | 30% | - Debug and tune Pig jobs - Write and optimize Pig Latin scripts - Data transformation, filtering, joining, and aggregation |
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
What is the term for the process of moving map outputs to the reducers?
- A. Combining
- B. Reducing
- C. Partitioning
- D. Shuffling and sorting
Analyze each scenario below and indentify which best describes the behavior of the default partitioner?
- A. The default partitioner assigns key-values pairs to reduces based on an internal random number generator.
- B. The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.
- C. The default partitioner computes the hash of the key and divides that valule modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.
- D. The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key-value pair.
- E. The default partitioner implements a round-robin strategy, shuffling the key-value pairs to each reducer in turn. This ensures an event partition of the key space.
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Determine which best describes when the reduce method is first called in a MapReduce job?
- A. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called as soon as the intermediate key-value pairs start to arrive.
- B. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called only after all intermediate data has been copied and sorted.
- C. Reduce methods and map methods all start at the beginning of a job, in order to provide optimal performance for map-only or reduce-only jobs.
- D. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The programmer can configure in the job what percentage of the intermediate data should arrive before the reduce method begins.
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All keys used for intermediate output from mappers must:
- A. Override isSplitable.
- B. Implement a splittable compression algorithm.
- C. Be a subclass of FileInputFormat.
- D. Implement WritableComparable.
- E. Implement a comparator for speedy sorting.
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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 network I/O
- B. Processor and RAM
- C. Processor and disk I/O
- D. Disk I/O and network I/O
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