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C. There is a CPU intensive step that occurs between the map and reduce steps. It maintains configuration data, performs synchronization, naming, and grouping. Ans. C. Avro is a java library that create splittable files, A. D. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values. Ans. D. Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper. It can easily store and process a large amount of data compared to RDBMS. One key and a list of some values associated with that key. No, because the sum operation in the reducer is incompatible with the operation of a Combiner. Apache Sqoop is a tool particularly used for transferring massive data between Apache Hadoop and external datastores such as relational database management, enterprise data warehouses, etc. These sequences can be combined with other actions including forks, decision points, and path joins. Ans. Update the network addresses in the dfs.exclude and mapred.exclude, Update the Namenode: $ Hadoop dfsadmin -refreshNodes, Update the JobTracker: Hadoop mradmin -refreshNodes, Cross-check the Web UI it will show “Decommissioning in Progress”. : Storage unit– HDFS (NameNode, DataNode) Processing framework– YARN (ResourceManager, NodeManager) 4. Ans. Being a framework, Hadoop is made up of several modules that are supported by a large ecosystem of technologies. It interprets the results of how a record should be processed by allowing Hive to read and write from a table. This complexity has several downsides: increased risk of bugs and performance degradation. Dear Readers, Welcome to Hadoop Objective Questions and Answers have been designed specially to get you acquainted with the nature of questions you may encounter during your Job interview for the subject of Hadoop Multiple choice Questions.These Objective type Hadoop are very important for campus placement test and job … Accesses data from HBase tables using APIs and MapReduce. In order to give a balance to a certain threshold among data nodes, use the Balancer tool. This tool tries to subsequently even out the block data distribution across the cluster. Each value must be same type. A. So, check all the parts and learn the new concepts of the Hadoop. By default, the HDFS block size is 128MB for Hadoop 2.x. C. It depends when the developer reads the configuration file. C. The default input format is controlled by each individual mapper and each line needs to be parsed indivudually. A. Map or reduce tasks that are stuck in an infinite loop. Hive can be used for real time queries. D. A distributed filesystem makes random access faster because of the presence of a dedicated node serving file metadata. 1. Ans. ( B) a) ALWAYS True b) True only for Apache Hadoop c) True only for Apache and Cloudera Hadoop d) ALWAYS False 13. Ans. A. MapReduce is a programming model used for processing and generating large datasets on the clusters with parallel and distributed algorithms. In-Memory: The natural storage mechanism of RapidMiner is in-memory data storage, highly optimized for data access usually performed for analytical tasks. Q19) What is the difference between active and passive NameNodes? A. The below-provided is a free online quiz related to the Hadoop topic. Following is the key difference between Hadoop and RDBMS: An RDBMS works well with structured data. C. Reduce-side join is a set of API to merge data from different sources. Pig offers various built-in operators for data operations like filters, joins, sorting, ordering, etc., while to perform these same functions in MapReduce is an enormous task. Pig programs are executed as MapReduce jobs via the Pig interpreter. c) HBase. 1. Q8) How can you skip the bad records in Hadoop? Practice Hadoop MCQs Online Quiz Mock Test For Objective Interview. Q17) How to decommission (removing) the nodes in the Hadoop cluster? Hadoop job client submits the job jar/executable and configuration to the ResourceManager. The most common programming language is Java, but scripting languages are also supported via Hadoop streaming. ResourceManager then distributes the software/configuration to the slaves. The methods used for restarting the NameNodes are the following: These script files are stored in the sbin directory inside the Hadoop directory store. Ans. Q2) Explain Big data and its characteristics. b) True only for Apache Hadoop. Checkpoint Node is the new implementation of secondary NameNode in Hadoop. The most common problem with map-side joins is lack of the avaialble map slots since map-side joins require a lot of mappers. B. Best Hadoop Objective type Questions and Answers. E. MapReduce jobs that are causing excessive memory swaps. It is a file-level computer data storage server connected to a computer network, provides network access to a heterogeneous group of clients. RecordReader in Hadoop uses the data from the InputSplit as input and converts it into Key-value pairs for Mapper. A. It is a distributed collection of objects, and each dataset in RDD is further distributed into logical partitions and computed on several nodes of the cluster. In addition to this, the applicants can go through about the Instructions, how to check the Web Services Online test Results. In Hadoop 2.x, we have both Active and passive NameNodes. The best performance expectation one can have is measured in seconds. B. By default, Hive Metastore uses Derby database. That will completely disable the reduce step. Hadoop is open source. As the opportunities for Hadoop are unlimited, the competition for aspirants preparing for the interviews is also high. Disabling the reduce step speeds up data processing. C. The TaskTracker spawns a new Mapper to process each key-value pair. Q2) Explain Big data and its characteristics. These free quiz questions will test your knowledge of Hadoop. Big Data refers to a large amount of data that exceeds the processing capacity of conventional database systems and requires a special parallel processing mechanism. One key and a list of all values associated with that key. How can we make the most of our efforts? Below is some multiple choice Questions corresponding to them are the choice of answers. Both techniques have about the the same performance expectations. Selects high volume data streams in real-time. Any programming language that can comply with Map Reduce concept can be supported. This process is called Speculative Execution in Hadoop. Hadoop is an open-source programming framework that makes it easier to process and store extremely large data sets over multiple distributed computing clusters. It executes Hadoop jobs in Apache Spark, MapReduce, etc. There needs to be at least one reduce step in Map-Reduce abstraction. Ans. Developers should never design Map-Reduce jobs without reducers. RDD(Resilient Distributed Datasets) is a fundamental data structure of Spark. On this page, we have collected the most frequently asked questions along with their solutions that will help you to excel in the interview. ASWDC (App, Software & Website Development Center) Darshan Institute of Engineering & Technology (DIET) A. Hadoop fsck command is used for checking the HDFS file system. There are different arguments that can be passed with this command to emit different results. B. Pig provides additional capabilities that allow certain types of data manipulation not possible with MapReduce. A. Binary data can be used directly by a map-reduce job. The most common problem with map-side joins is introducing a high level of code complexity. B. Build a new class that extends Partitioner Class. This Google Analytics exam involves 15 MCQs that are similar to those expected in the real exam. Individuals can practice the Big Data Hadoop MCQ Online Test from the below sections. RDBMS supports OLTP(Online Transactional Processing), Hadoop supports OLAP(Online Analytical Processing). Pig is a subset fo the Hadoop API for data processing, B. Ans. Yes. The new NameNode will start serving the client once it has completed loading the last checkpoint FsImage and enough block reports from the DataNodes. Copyright © 2020 Mindmajix Technologies Inc. All Rights Reserved, In This Interview Questions, You Will Learn. D. Write a custom FileInputFormat and override the method isSplitable to always return false. Question2: Should I use a free analytics program for my website? A. Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper. A. ASequenceFilecontains a binaryencoding ofan arbitrary numberof homogeneous writable objects. No. The MapReduce Partitioner manages the partitioning of the key of the intermediate mapper output. The process of translating objects or data structures state into binary or textual form is called Avro Serialization. Learn Hadoop Multiple Choice Questions and Answers with explanations. C. A developer can always set the number of the reducers to zero. Take Hadoop Quiz To test your Knowledge. These Objective type Hadoop are very important for campus placement test and job interviews. A - It is lost for ever. www.gtu-mcq.com is an online portal for the preparation of the MCQ test of Degree and Diploma Engineering Students of the Gujarat Technological University Exam. From the below, the contenders can check the Big Data Hadoop Multiple Choice Questions and Answers. C. The distributed cache is a component that caches java objects. Each key must be the same type. D. Input file splits may cross line breaks. IdentityMapper.class is used as a default value when JobConf.setMapperClass is not set. The distributed cache is special component on datanode that will cache frequently used data for faster client response. Connect with her via LinkedIn and Twitter . Benefits Of Cloudera Hadoop Certification | Hadoop developer, RDBMS cannot store and process a large amount of data. Characteristics of Big Data: Volume - It represents the amount of data that is increasing at an exponential rate i.e. B. Writables are interfaces in Hadoop. It is used during map step. Ans. A. Steps involved in Hadoop job submission: Ans. Q31) What is the command used for printing the topology? Q20) How will you resolve the NameNode failure issue? 1. Ans. Q30) What is the purpose of dfsadmin tool? Apache HBase is multidimensional and a column-oriented key datastore runs on top of HDFS (Hadoop Distributed File System). 13. A Sequence Filecontains a binary encoding of an arbitrary number of homo geneous writable objects. A. A. Writable data types are specifically optimized for network transmissions, B. Writable data types are specifically optimized for file system storage, C. Writable data types are specifically optimized for map-reduce processing, D. Writable data types are specifically optimized for data retrieval. A. customizable courses, self paced videos, on-the-job support, and job assistance. Q37) How a client application interacts with the NameNode? It caches read-only text files, jar files, archives, etc. This set of Multiple Choice Questions & Answers (MCQs) focuses on “Big-Data”. Here, we are presenting those MCQs in a different style. D. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The Hadoop administrator has to set the number of the reducer slot to zero on all slave nodes. MapReduce Programming model is language independent, Distributed programming complexity is hidden, Manages all the inter-process communication, The application runs in one or more containers, Job’s input and output locations in the distributed file system, Class containing the map function and reduce function, JAR file containing the reducer, driver, and mapper classes. A serializable object which executes a simple and efficient serialization protocol, based on DataInput and DataOutput. For aggregation, we need the output from all the mapper functions, which is not possible during the map phase as map tasks will be running in different nodes, where data blocks are present. Hadoop will be a good choice in environments when there are needs for big data processing on which the data being processed does not have dependable relationships. She spends most of her time researching on technology, and startups. C. A Sequence Filecontains a binary encoding of an arbitrary number of Writable Comparable objects, in sorted order. C. Map files are generated by Map-Reduce after the reduce step. Hope these questions are helpful for you. The Various HDFS Commands are listed bellow. Check out the Big Data Hadoop Certification Training course and get certified today. ♣ Tip: Now, while explaining Hadoop, you should also explain the main components of Hadoop, i.e. B. This Big Data Analytics Online Test is helpful to learn the various questions and answers. top 100 hadoop interview questions answers pdf, real time hadoop interview questions gathered from experts, top 100 big data interview questions, hadoop online quiz questions, big data mcqs, hadoop objective type questions and answers Generally, the daemon is nothing but a process that runs in the background. B. Reduce-side join is a technique for merging data from different sources based on a specific key. ( B) a) ALWAYS True. The reduce method is called as soon as the intermediate key-value pairs start to arrive. It allocates the resources (containers) to various running applications based on resource availability and configured shared policy. D. ASequenceFilecontains a binary encoding of an arbitrary number key-value pairs. Datameer - Datameer Analytics Solution (DAS) is a Hadoop-based solution for big data analytics that includes data source integration, storage, an analytics engine and visualization. Objective. Q35) What is the main functionality of NameNode? Schema of the data is known in RDBMS and it always depends on the structured data. A. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. D. It is not possible to create a map-reduce job without at least one reduce step. It provides multiple namespaces in the cluster to improve scalability and isolation. A. This data can be either structured or unstructured data. They are often used in high-performance map-reduce jobs, B. Sequence files are a type of the file in the Hadoop framework that allow data to be sorted, C. Sequence files are intermediate files that are created by Hadoop after the map step. 1. Who was written Hadoop? D. A DataNode is disconnectedfrom the cluster. Consider the replication factor is 3 for data blocks on HDFS it means for every block of data two copies are stored on the same rack, while the third copy is stored on a different rack. SerDe is a combination of Serializer and Deserializer. Q4) What is YARN and explain its components? This and other engines are outlined below. Each value must be sametype. It offers extensive storage for any type of data and can handle endless parallel tasks. A line that crosses file splits is read by the RecordReaders of both splits containing the brokenline. Yet Another Resource Negotiator (YARN) is one of the core components of Hadoop and is responsible for managing resources for the various applications operating in a Hadoop cluster, and also schedules tasks on different cluster nodes. This can lead to very slow performance on large datasets. Q23) How to keep an HDFS cluster balanced? I hope these questions will be helpful for your Hadoop job and in case if you come across any difficult question in an interview and unable to find the best answer please mention it in the comments section below. A line that crosses file splits is read by the RecordReader of the split that contains the beginningof thebroken line. Q34) List the various site-specific configuration files available in Hadoop? Big Data refers to a large amount of data that exceeds the processing capacity of conventional database systems and requires a special parallel processing mechanism.This data can be either structured or unstructured data. B. Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. A. Sequence files are binary format files that are compressed and are splitable. Ans. Hadoop MCQs – Big Data Science. Introduction: Hadoop Ecosystem is a platform or a suite which provides various services to solve the big data problems. If bad blocks are detected it will be fixed before any client reads. Ans. It is a highly reliable, distributed, and configurable tool that is specially designed to transfer streaming data to HDFS. B. A. Map files are stored on the namenode and capture the metadata for all blocks on a particular rack. It is a "PL-SQL" interface for data processing in Hadoop cluster. But, before starting, I would like to draw your attention to the Hadoop revolution in the market. Ans. Datameer Analytics Solution (DAS) is a Hadoop-based solution for big data analytics that includes data source integration, storage, an analytics engine and visualization. The job configuration requires the following: Ans. Ex: replication factors, block location, etc. In Apache Hadoop, if nodes do not fix or diagnose the slow-running tasks, the master node can redundantly perform another instance of the same task on another node as a backup (the backup task is called a Speculative task). Pig is a part of the Apache Hadoop project that provides C-like scripting languge interface for data processing, C. Pig is a part of the Apache Hadoop project. It reads, writes, and manages large datasets that are residing in distributed storage and queries through SQL syntax. A line that crosses file splits is read by the RecordReader of the split that contains the end of the brokenline. D. The JobTracker spawns a new Mapper to process all records in a single file. D. Pig provides the additional capability of allowing you to control the flow of multiple MapReduce jobs. MapReduce framework is used to write applications for processing large data in parallel on large clusters of commodity hardware. I find tagging to be a time intensive process and requires a … Data represented in a distributed filesystem is already sorted. C. Input file splits may cross line breaks. b) FALSE. In DataNodes, RAID is not necessary as storage is achieved by replication between the Nodes. Rack Awareness is the algorithm used for improving the network traffic while reading/writing HDFS files to Hadoop cluster by NameNode. B. The data needs to be preprocessed before using the default input format. This will disable the reduce step. This Hadoop Test contains around 20 questions of multiple choice with 4 options. D. Hadoop can freely use binary files with map-reduce jobs so long as the files have headers, A . The language used in this platform is called Pig Latin. D. A Sequence Filecontains a binary encoding of an arbitrary number key-value pairs. Big Data Analytics Online Practice Test cover Hadoop MCQs and build-up the confidence levels in the most common framework of Bigdata. Kudu is specifically designed for use cases that require fast analytics on fast (rapidly changing) data. What are HDFS and YARN? A Sequence Filecontains a binary encoding of an arbitrary number of hetero geneous writable objects. D. The distributed cache is a component that allows developers to deploy jars for Map-Reduce processing. Hadoop is open source. You can see the correct answer by clicking view answer link. Which of the following are the core components of Hadoop? RAID (redundant array of independent disks) is a data storage virtualization technology used for improving performance and data redundancy by combining multiple disk drives into a single entity. So, it is not possible for multiple users or processes to access it at the same time. A. Identity Mapper is a default Mapper class which automatically works when no Mapper is specified in the MapReduce driver class. The Web Services test attendees can find more improvement after participating in this Web Services mock test. ( D) a) HDFS b) Map Reduce c) HBase d) Both (a) and (b) 12. A. Developer can specify other input formats as appropriate if xml is not the correct input. The reduce method is called only after all intermediate data has been copied and sorted. The best performance expectation one can have is measured in milliseconds. Streaming data is gathered from multiple sources into Hadoop for analysis. www.gtu-mcq.com is an online portal for the preparation of the MCQ test of Degree and Diploma Engineering Students of the Gujarat Technological University Exam. Madhuri is a Senior Content Creator at MindMajix. 11. You have to select the right answer to a question. Each key must be the same type. C. Only Java supported since Hadoop was written in Java. These MapReduce sequences can be combined with forks and path joins. We cannot perform Aggregation in mapping because it requires sorting of data, which occurs only at the Reducer side. It receives inputs from the Map class and passes the output key-value pairs to the reducer class. Binary data should be converted to a Hadoop compatible format prior to loading. According to Forbes, 90% of global organizations report their investments in Big Data analytics, which clearly shows that the career for Hadoop professionals is very promising right now and the upward trend will keep progressing with time. Dear Readers, Welcome to Hadoop Objective Questions and Answers have been designed specially to get you acquainted with the nature of questions you may encounter during your Job interview for the subject of Hadoop Multiple choice Questions. In Hadoop 1.x, NameNode is the single point of failure. It displays the tree of racks and DataNodes attached to the tracks. A. HDFS Federation enhances the present HDFS architecture through a clear separation of namespace and storage by enabling a generic block storage layer. Q22) List the different types of Hadoop schedulers. Q28) What is the main purpose of the Hadoop fsck command? Hadoop follows the schema on reading policy, Hadoop is a free and open-source framework, A small block size of data (like 512 bytes), Reads data sequentially after single seek. The MapReduce reducer has three phases: Ans. B. Map files are the files that show how the data is distributed in the Hadoop cluster. Developers are cautioned to rarely use map-side joins. A line that crosses file splits is read by the RecordReader of the split that contains the end of the broken line. NAS is a high-end storage device which includes a high cost. Hadoop is a framework that enables processing of large data sets which reside in the form of clusters. There are only a very few job parameters that can be set using Java API. Hadoop works better for large amounts of data. They are: Ans. They show the task distribution during job execution. B. Writable is a java interface that needs to be implemented for HDFS writes. So your best options are to use Flink either with Hadoop or Flink tables or use Spark ML (machine language) library with data stored in Hadoop or elsewhere and then store the results either in Spark or Hadoop.
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