CCD-410 Exam Questions
57 real CCD-410 exam questions with expert-verified answers and explanations. Page 1 of 2.
- Question #1Hadoop Ecosystem Fundamentals
MapReduce v2 (MRv2/YARN) is designed to address which two issues?
YARNMapReduce v2JobTrackerresource management - Question #2Developing with Apache Spark Core
You need to run the same job many times with minor variations. Rather than hardcoding all job configuration options in your drive code, you've decided to have your Driver subclass...
Tool interfacejob configurationhadoop CLI-D flag - Question #3Developing with Apache Spark Core
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 (Te...
InputFormatmapper input typesMapReduce APIdata types - Question #4Hadoop Ecosystem Fundamentals
Identify the MapReduce v2 (MRv2 / YARN) daemon responsible for launching application containers and monitoring application resource usage?
YARNNodeManagerapplication containersresource monitoring - Question #5
Which best describes how TextInputFormat processes input files and line breaks?
- Question #6Developing with Apache Spark Core
For each input key-value pair, mappers can emit:
mapper outputintermediate key-value pairsMapReduce APIemit - Question #7Developing with Apache Spark Core
In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?
reducervalue orderingshuffle phaseMapReduce behavior - Question #8
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 in...
- Question #9Developing with Apache Spark Core
You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a li...
combinerassociative operationsreducer reuseword count - Question #10Hadoop Ecosystem Fundamentals
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 MapReduc...
JobTrackertask schedulingMapReduce v1daemon roles - Question #11Hadoop Ecosystem Fundamentals
Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?
HBasedistributed data storerandom accessHadoop ecosystem - Question #12Hadoop Ecosystem Fundamentals
You use the hadoop fs -put command to write a 300 MB file using and HDFS block size of 64 MB. Just after this command has finished writing 200 MB of this file, what would another u...
HDFSblock sizefile write visibilityconcurrent access - Question #13Hadoop Ecosystem Fundamentals
Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and generate Java classes to interact with that imported data?
SqoopRDBMS importHDFSJava class generation - Question #14Developing with Apache Spark Core
You have a directory named jobdata in HDFS that contains four files: _first.txt, second.txt, .third.txt and #data.txt. How many files will be processed by the FileInputFormat.setIn...
FileInputFormathidden filesunderscore prefixinput path filtering - Question #15Developing with Apache Spark Core
You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat: the mapper applies a regular expression over input values and emits key- values...
reducerszero reducersoutput filesTextInputFormat - Question #16Performance Tuning and Troubleshooting
A combiner reduces:
combinerintermediate datashuffle reductionMapReduce optimization - Question #18Hadoop Ecosystem Fundamentals
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate daemons? Select two.
YARNJobTrackerresource managementjob scheduling - Question #19Hadoop Ecosystem Fundamentals
What types of algorithms are difficult to express in MapReduce v1 (MRv1)?
MapReduce limitationsglobal stateiterative algorithmsMRv1 - Question #20Developing with Apache Spark Core
In the reducer, the MapReduce API provides you with an iterator over Writable values. What does calling the next () method return?
reducer iteratorWritable reusenext() methodobject reference - Question #21Data Warehousing and Querying Tools (Hive, Impala)
Table metadata in Hive is:
HiveMetastoretable metadataschema storage - Question #22Developing with Apache Spark Core
Analyze each scenario below and indentify which best describes the behavior of the default partitioner?
partitionerhash partitioningmodulokey distribution - Question #23
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 relie...
- Question #24Performance Tuning and Troubleshooting
In a large MapReduce job with m mappers and n reducers, how many distinct copy operations will there be in the sort/shuffle phase?
shuffle phasecopy operationsmappersreducers - Question #25Hadoop Ecosystem Fundamentals
Workflows expressed in Oozie can contain:
Oozieworkflow schedulingMapReducePig - Question #26Developing with Apache Spark Core
Which best describes what the map method accepts and emits?
map functionkey-value pairsinput/output contractMapReduce - Question #27Developing with Apache Spark Core
When can a reduce class also serve as a combiner without affecting the output of a MapReduce program?
combinerreducertype compatibilityMapReduce - Question #28Hadoop Ecosystem Fundamentals
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 dat...
AvroHDFS storage formatsdata serializationSequenceFile - Question #29
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 clos...
- Question #30Hadoop Ecosystem Fundamentals
Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determi...
HDFS block sizeTextInputFormatmapper countinput splits - Question #31Hadoop Ecosystem Fundamentals
What is a SequenceFile?
SequenceFilebinary formatkey-value storageHDFS - Question #32Developing with Apache Spark Core
When is the earliest point at which the reduce method of a given Reducer can be called?
reducer lifecycleMapReduce executionmap phasereduce phase - Question #33Hadoop Ecosystem Fundamentals
Which describes how a client reads a file from HDFS?
HDFS readNameNodeDataNodeblock location - Question #36Developing with Apache Spark Core
How are keys and values presented and passed to the reducers during a standard sort and shuffle phase of MapReduce?
shuffle and sortkey sortingreducer input orderMapReduce - Question #37Developing with Apache Spark Core
Assuming default settings, which best describes the order of data provided to a reducer's reduce method:
reducer orderingkey sortvalue orderingdefault settings - Question #38Performance Tuning and Troubleshooting
You wrote a map function that throws a runtime exception when it encounters a control character in input data. The input supplied to your mapper contains twelve such characters tot...
task failuremapred.max.map.attemptsexception handlingtask retry - Question #39Developing with Apache Spark Core
You want to populate an associative array in order to perform a map-side join. You've decided to put this information in a text file, place that file into the DistributedCache and...
DistributedCachemap-side joinMapper lifecycleconfigure method - Question #40Performance Tuning and Troubleshooting
You've written a MapReduce job that will process 500 million input records and generated 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will...
combinerintermediate data reductionnetwork bottleneckPartitioner - Question #41Developing with Apache Spark Core
Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated files in HDFS.
reduce-side joinrelational joinMapReducelarge tables - Question #42Developing with Apache Spark Core
You have just executed a MapReduce job. Where is intermediate data written to after being emitted from the Mapper's map method?
intermediate dataspill to disklocal file systemmapper output - Question #43
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 we...
- Question #44Developing with Apache Spark Core
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...
reducer keyskey groupingunique keysMapReduce output - Question #46Performance Tuning and Troubleshooting
What is the disadvantage of using multiple reducers with the default HashPartitioner and distributing your workload across you cluster?
HashPartitionermultiple reducersglobal sortoutput ordering - Question #47
Given a directory of files with the following structure: line number, tab character, string: Example: 1 abialkjfjkaoasdfjksdlkjhqweroij 2 kadfjhuwqounahagtnbvaswslmnbfgy 3 kjfteiom...
- Question #48Hadoop Ecosystem Fundamentals
You need to perform statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archiv...
libjarsjob submissiondependency managementclasspath - Question #49Performance Tuning and Troubleshooting
The Hadoop framework provides a mechanism for coping with machine issues such as faulty configuration or impending hardware failure. MapReduce detects that one or a number of machi...
speculative executionfault toleranceslow tasksMapReduce - Question #50Developing with Apache Spark Core
For each intermediate key, each reducer task can emit:
reducer outputkey-value typestype constraintsMapReduce - Question #51Hadoop Ecosystem Fundamentals
What data does a Reducer reduce method process?
MapReduceReducerkey groupingreduce method - Question #52Hadoop Ecosystem Fundamentals
All keys used for intermediate output from mappers must:
MapReduceWritableComparableintermediate keysserialization - Question #53Hadoop Ecosystem Fundamentals
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...
MapReduce v1data localityJobTrackerTaskTracker - Question #54Hadoop Ecosystem Fundamentals
Indentify which best defines a SequenceFile?
SequenceFilebinary formatkey-value pairsHDFS file formats