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ExamCode: Apache-Hadoop-Developer ExamName: Hadoop 2.0 Certification exam for Pig and Hive Developer Vendor Name: Hortonworks Edition = DEMO Question: 1 Identify the MapReduce v2 (MRv2 / YARN) daemon responsible for launching application containers and monitoring application resource usage? A. ResourceManager B. NodeManager C. ApplicationMaster D. ApplicationMasterService E. TaskTracker F. JobTracker Reference: Apache Hadoop YARN - Concepts & Applications Question: 2 Answer: B You want to run Hadoop jobs on your development workstation for testing before you submit them to your production cluster. Which mode of operation in Hadoop allows you to most closely simulate a production cluster while using a single machine? A. Run all the nodes in your production cluster as virtual machines on your development workstation. B. Run the hadoop command with the -jt local and the -fs file:///options. C. Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine. D. Run simldooop, the Apache open-source software for simulating Hadoop clusters. Question: 3 Answer: C
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. Six B. Five C. Four D. Two E. One F. Three Answer: B Only one key value pair will be passed from the two (the, 1) key value pairs. Question: 4 Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data? A. HBase B. Hue C. Pig D. Hive E. Oozie F. Flume G. Sqoop Answer: A Use Apache HBase when you need random, realtime read/write access to your Big Data. Note: This project's goal is the hosting of very large tables -- billions of rows X millions of columns - - atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google's Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, Apache HBase provides Bigtable-like capabilities on top of Hadoop and HDFS. Features Linear and modular scalability. Strictly consistent reads and writes. Automatic and configurable sharding of tables Automatic failover support between RegionServers. Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables. Easy to use Java API for client access. Block cache and Bloom Filters for real-time queries. Query predicate push down via server side Filters Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding
options Extensible jruby-based (JIRB) shell Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX Reference: http://hbase.apache.org/ (when would I use HBase? First sentence) Question: 5 Which one of the following statements describes a Pig bag. tuple, and map, respectively? A. Unordered collection of maps, ordered collection of tuples, ordered set of key/value pairs B. Unordered collection of tuples, ordered set of fields, set of key value pairs C. Ordered set of fields, ordered collection of tuples, ordered collection of maps D. Ordered collection of maps, ordered collection of bags, and unordered set of key/value pairs Question: 6 Answer: B Which HDFS command copies an HDFS file named foo to the local filesystem as localfoo? A. hadoop fs -get foo LocalFoo B. hadoop -cp foo LocalFoo C. hadoop fs -Is foo D. hadoop fs -put foo LocalFoo Question: 7 Answer: A You are developing a MapReduce job for sales reporting. The mapper will process input keys representing the year (IntWritable) and input values representing product indentifies (Text). Indentify what determines the data types used by the Mapper for a given job. A. The key and value types specified in the JobConf.setMapInputKeyClass and JobConf.setMapInputValuesClass methods B. The data types specified in HADOOP_MAP_DATATYPES environment variable C. The mapper-specification.xml file submitted with the job determine the mapper's input key and value types. D. The InputFormat used by the job determines the mapper's input key and value types. Answer: D
The input types fed to the mapper are controlled by the InputFormat used. The default input format, "TextInputFormat," will load data in as (LongWritable, Text) pairs. The long value is the byte offset of the line in the file. The Text object holds the string contents of the line of the file. Note: The data types emitted by the reducer are identified by setoutputkeyclass() andsetoutputvalueclass(). The data types emitted by the reducer are identified by setoutputkeyclass() and setoutputvalueclass(). By default, it is assumed that these are the output types of the mapper as well. If this is not the case, the methods setmapoutputkeyclass() and setmapoutputvalueclass() methods of the JobConf class will override these. Reference: Yahoo! Hadoop Tutorial, THE DRIVER METHOD Question: 8 All keys used for intermediate output from mappers must: A. Implement a splittable compression algorithm. B. Be a subclass of FileInputFormat. C. Implement WritableComparable. D. Override issplitable. E. Implement a comparator for speedy sorting. Answer: C The MapReduce framework operates exclusively on <key, value> pairs, that is, the framework views the input to the job as a set of <key, value> pairs and produces a set of <key, value> pairs as the output of the job, conceivably of different types. The key and value classes have to be serializable by the framework and hence need to implement the Writable interface. Additionally, the key classes have to implement the WritableComparable interface to facilitate sorting by the framework. Reference: MapReduce Tutorial Question: 9 Review the following data and Pig code:
What command to define B would produce the output (M,62,95l02) when invoking the DUMP operator on B? A. B = FILTER A BY (zip = = '95102' AND gender = = M"); B. B= FOREACH A BY (gender = = 'M' AND zip = = '95102'); C. B = JOIN A BY (gender = = 'M' AND zip = = '95102'); D. B= GROUP A BY (zip = = '95102' AND gender = = 'M'); Question: 10 Answer: A Assuming the following Hive query executes successfully: Which one of the following statements describes the result set? A. A bigram of the top 80 sentences that contain the substring "you are" in the lines column of the input data A1 table. B. An 80-value ngram of sentences that contain the words "you" or "are" in the lines column of the inputdata table. C. A trigram of the top 80 sentences that contain "you are" followed by a null space in the lines column of the inputdata table. D. A frequency distribution of the top 80 words that follow the subsequence "you are" in the lines column of the inputdata table. Answer: D
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