Hadoop Online Training course in Hyderabad|Hadoop training in USA,UK,Canada

 

Hadoop Online Training course

Hadoop online training course trainer contact details : [email protected]

Hadoop Online Training course in Hyderabad by real time Experts with live project call at +91 9963552676 Online Hadoop Training classes with real time scenarios.Hadoop is framework for running applications on large clusters built of commodity hardware.Hadoop architecture provides both reliability and availability.

It is opensource distributed processing with highly scalable system.system. Hadoop key features are flexible,economical,scalable and reliable.Hadoop is highly scalable and efficient falut tolerent system.Hadoop follows programming design called “Map/Reduce”,where your application logic is spread across the large set of clusters. Hadoop follows a file system called HDFS means Hadoop distributed file system.

In HDFS ,each block is 64 MB in size.Data will be divided in blocks.Blocks will be replicated 3 times by default.one can change default replication by configuration settings in hadoop.In Hadoop distributed file system,data will be replicated multiple times to get high availability of the data which is available in servers.HDFS handles the node failures automatically and data will be replicated on available nodes.Pig,Hive and sqoop are the different types of the programming ways,in which we can access the hadoop file system.

Hadoop real benefit will be only knows when we work with TB’s of data,because RDBMS takes couple of hours when it is processing the Terabytes of data,hadoop will does same work in couple of minutes.Hadoop has master and slave architecture for both storage and processing.Main components of the HDFS is namenode,datanode and secondary name node.The main components of mapreduce is job tracker and task tracker.

Biggest code contributors of hadoop is “Hortonworks with approximately 19% and cloudera with 16% and 14% yahoo and remaining code contributions will be contributed by other companies such as microsoft ebay and mapr.Hadoop mainly used for log processing,search,recommendation system and image analysis.Currently hadoop is used by Facebook,amazon,ebay and so many big companies.

Online Hadoop Training in Hyderabad

Online Hadoop Training course in Hyderabad by Experienced Professional call +91 9963552676

Hadoop Online Training course in  Hyderabad

hadoop online training course that compiled best hadoop course curriculum from hadoop.apache.org and cloudera and Hortonworks platforms to cover in depth knowledge on hadoop course syllabus.we provide the best big data hadoop training material too after every class we deliver.

Hadoop Online Training course Pre-requisites

hadoop online training course also covers pre-requisites

  1. Basic Linux/Unix commands.
  2. Basic Core java for Map-reduce Programming in hadoop
  3. Basic SQL for Hadoop Hive Queries.

Hadoop Online Training Course Curriculum:

1.  Understanding Big Data and Hadoop

Hadoop Online Training Course Learning Objectives –  hadoop online training course,In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop Architecture, HDFS, Anatomy of File Write and Read, Rack Awareness.

We will discuss these below topics as part of Big Data,hadoop online training

hadoop online training course,Big Data, Limitations and Solutions of existing Data Analytics Architecture, Hadoop, Hadoop Features, Hadoop Ecosystem, Hadoop 2.x core components,

hadoop online training course,Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework, Anatomy of File Write and Read, Rack Awareness.

2.  Hadoop Online Training Coure MapReduce Framework – I

Hadoop Online Training Course Learning Objectives – In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will learn about YARN concepts in MapReduce.
We will discuss these below topics as part of MapReduce,hadoop online training
  1. MapReduce Use Cases,
  2. Traditional way Vs MapReduce way,
  3. Why MapReduce,
  4. Hadoop 2.x MapReduce Architecture,
  5. Hadoop 2.x MapReduce Components,
  6. YARN MR Application Execution Flow,
  7. YARN Workflow,
  8. Anatomy of MapReduce Program,
  9. Demo on MapReduce.

3.  Hadoop MapReduce Framework – II

Learning Objectives – In this module, you will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets.
We will discuss these below topics as part of MapReduce,hadoop online training
  1. Input Splits,
  2. Relation between Input Splits and HDFS Blocks,
  3. MapReduce Job Submission Flow,
  4. Demo of Input Splits,
  5. MapReduce: Combiner & Partitioner, Demo on de-identifying Health Care Data set, Demo on Weather Data set.

4.  Advance MapReduce

Learning Objectives – In this module, you will learn Advance MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format and how to deal with complex MapReduce programs.
We will discuss these below topics as part of MapReduce,hadoop online training
  1. Counters,
  2. Distributed Cache,
  3. MRunit,
  4. Reduce Join,
  5. Custom Input Format,
  6. Sequence Input Format.

5.  Pig

Learning Objectives – In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting.
 
We will discuss these below topics as part of Pig,hadoop online training
  1. About Pig,
  2. MapReduce Vs Pig,
  3. Pig Use Cases,
  4. Programming Structure in Pig,
  5. Pig Running Modes,
  6. Pig components,
  7. Pig Execution,
  8. Pig Latin Program,
  9. Data Models in Pig,
  10. Pig Data Types.
  11. Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDF, Pig Demo on Healthcare Data set.

6.  Hive

Learning Objectives – This module will help you in understanding Hive concepts, Loading and Querying Data in Hive and Hive UDF. 
We will discuss these below topics as part of Hive,hadoop online training
  1. Hive Background,
  2. Hive Use Case,
  3. About Hive,
  4. Hive Vs Pig,
  5. Hive Architecture and Components,
  6. Metastore in Hive,
  7. Limitations of Hive,
  8. Comparison with Traditional Database,
  9. Hive Data Types and Data Models,
  10. Partitions and Buckets,
  11. Hive Tables(Managed Tables and External Tables),
  12. Importing Data,
  13. Querying Data,
  14. Managing Outputs,
  15. Hive Script,
  16. Hive UDF,
  17. Hive Demo on Healthcare Data set.

7.  Advance Hive and HBase

Learning Objectives – In this module, you will understand Advance Hive concepts such as UDF, dynamic Partitioning. You will also acquire in-depth knowledge of HBase, Hbase Architecture and its components.
 
We will discuss these below topics as part of Hive,Hbase and hadoop online training
  1.  Hive QL:
  2. Joining Tables,
  3. Dynamic Partitioning,
  4. Custom Map/Reduce Scripts,
  5. Hive : Thrift Server, User Defined Functions.
HBase:
  1. Introduction to NoSQL Databases and HBase, HBase v/s RDBMS,
  2. HBase Components,
  3. HBase Architecture,
  4. HBase Cluster Deployment.

8.  Advance HBase

Learning Objectives – This module will cover Advance HBase concepts. We will see demos on Bulk Loading , Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.
 
We will discuss these below topics as part of HBase,hadoop online training 
  1.  HBase Data Model
  2. HBase Shell
  3. HBase Client API
  4. Data Loading Techniques
  5. ZooKeeper Data Model
  6. Zookeeper Service
  7. Zookeeper
  8. Demos on Bulk Loading
  9. Getting and Inserting Data
  10. Filters in HBase

9.  Oozie and Hadoop Project

oozie is workflow schedular system to manage apache hadoop jobs.oozie is scalable,reliable and extesible system.oozie is integrated with the rest of the hadoop stack supporting several types of hadoop jobs.Example:-java mapreduce,Streaming map-reduce,Pig,Hive,Sqoop.oozie coordinator jobs are recurrent oozie workflow jobs triggered by time and data availability.It is something like CronTab in Linux or File Polar in Java.Yahoo is running 200k Jobs per day using Oozie.
 
We will discuss these below topics as part of Oozie,hadoop online training 
  1. Flume and Sqoop Demo
  2. Oozie
  3. Oozie Components
  4. Oozie Workflow
  5. Scheduling with Oozie
  6. Demo on Oozie Workflow
  7. Oozie Co-ordinator
  8. Oozie Commands
  9. Oozie Web Console
  10. Hadoop Project Dem0

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Online Hadoop Training in Hyderabad - Job Postings data as per indeed website

                                      Job Postings data as per indeed website

we have been awarded continuously best big data hadoop training in hyderabad in Hyderabad.Hadoop Course fee is very nominal we are charging close to 300$ or less.Greater job market for Hadoop Skill set in the market as per job portal site

we not only provide the Big data hadoop training ,we also provide the placement too.we have various tieups with mnc’s like infosys,wipro and TCS across the abroad to provide the best talent in the hadoop training.

Online Hadoop Training in Hyderabad

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500 Hadoop Interview Questions will be covered as part of the Hadoop Online Training.

 

  1. What do the four V’s of Big Data denote?
  2. Compare Hadoop & Spark
  3. What are real-time industry applications of Hadoop?
  4. How is Hadoop different from other parallel computing systems?
  5. What is the use of RecordReader in Hadoop?
  6. How are large objects handled in Sqoop?
  7. How will you explain MapReduce and its need while programming with Apache Pig
  8. How will you explain co group in Pig?
  9. What is the difference between Hadoop
  10. Mention what is the difference between HDFS and NAS?
  11. Mention how Hadoop is different from other data processing tools?
  12. Mention what job does the conf class do?
  13. Mention what is the Hadoop MapReduce APIs contract for a key and value class?
  14. Mention what are the three modes in which Hadoop can be run?
  15. Mention what does the text input format do?
  16. How big data analysis helps businesses increase their revenue? Give example
  17. Name some companies that use Hadoop
  18. Differentiate between Structured and Unstructured data
  19. On what concept the Hadoop framework works?
  20. What are the main components of a Hadoop Application?
  21. What is Hadoop streaming?
  22. What is the best hardware configuration to run Hadoop?
  23. What are the most commonly defined input formats in Hadoop?
  24. What is Big Data?
  25. What is a block and block scanner in HDFS?
  26. Explain the difference between NameNode, Backup Node and Checkpoint NameNode
  27. Checkpoint Node
  28. BackupNode
  29. What is commodity hardware?
  30. What is the port number for NameNode, Task Tracker and Job Tracker?
  31. Explain about the process of inter cluster data copying
  32. How can you overwrite the replication factors in HDFS?
  33. Can the default “Hive Metastore” be used by multiple users (processes) at the same time?
  34. What is the default location where “Hive” stores table data?
  35. What is Apache HBase?
  36. Explain the major difference between HDFS block and InputSplit.
  37. What is distributed cache and what are its benefits?
  38. Explain the difference between NameNode, Checkpoint NameNode and BackupNode.
  39. What are the components of Apache HBase?
  40. What are the components of Region Server?
  41. Explain “WAL” in HBase?
  42. Mention the differences between “HBase” and “Relational Databases”?
  43. What is Apache Spark?
  44. Can you build “Spark” with any particular Hadoop version?
  45. Define RDD.
  46. What is Apache ZooKeeper and Apache Oozie?
  47. How do you configure an “Oozie” job in Hadoop?
  48. And many more Hadoop Online Training Interview Questions
  49. What is Hadoop Map Reduce
  50. How Hadoop MapReduce works?
  51. Explain what is shuffling in MapReduce ?
  52. Explain what is distributed Cache in MapReduce Framework ?
  53. Explain what is NameNode in Hadoop?
  54. Explain what is JobTracker in Hadoop? What are the actions followed by Hadoop?
  55. Explain what is heartbeat in HDFS?
  56. Explain what combiners is and when you should use a combiner in a MapReduce Job?
  57. What happens when a datanode fails ?
  58. Explain what is Speculative Execution?
  59. Explain what are the basic parameters of a Mapper?
  60. Explain what is the function of MapReducer partitioner?
  61. Explain what is difference between an Input Split and HDFS Block?
  62. Explain what happens in textinformat ?
  63. Mention what are the main configuration parameters that user need to specify to run Mapreduce Job ?
  64. Explain the difference between NAS and HDFS.
  65. Explain what happens if during the PUT operation, HDFS block is assigned a replication factor 1 instead of the default value 3
  66. What is the process to change the files at arbitrary locations in HDFS?
  67. Explain about the indexing process in HDFS.
  68. Why does one remove or add nodes in a Hadoop cluster frequently?
  69. What happens when two clients try to access the same file in the HDFS?
  70. How does NameNode tackle DataNode failures?
  71. What will you do when NameNode is down?
  72. What are the most common Input Formats in Hadoop?
  73. Define DataNode and how does NameNode tackle DataNode failures?
  74. What are the core methods of a Reducer?
  75. What is a checkpoint?
  76. Explain about the core components of Flume.
  77. Does Flume provide 100% reliability to the data flow?
  78. How can Flume be used with HBase?
  79. What is the standard location or path for Hadoop Sqoop scripts?
  80. How can you check all the tables present in a single database using Sqoop?
  81. Does Apache Flume provide support for third party plug-ins?
  82. Is it possible to leverage real time analysis on the big data collected by Flume directly? If yes, then explain how.
  83. Differentiate between FileSink and FileRollSink
  84. Can Apache Kafka be used without Zookeeper?
  85. Name a few companies that use Zookeeper
  86. Explain what is WebDAV in Hadoop?
  87. Explain what is sqoop in Hadoop ?
  88. Explain how JobTracker schedules a task ?
  89. Explain what is Sequencefileinputformat?
  90. Explain what does the conf.setMapper Class do ?
  91. Explain what is Hadoop?
  92. What are the additional benefits YARN brings in to Hadoop?
  93. How can native libraries be included in YARN jobs?
  94. What is the role of Zookeeper in HBase architecture?
  95. Explain about ZooKeeper in Kafka
  96. Explain how Zookeeper works
  97. List some examples of Zookeeper use cases
  98. How to use Apache Zookeeper command line interface?
  99. What are the different types of Znodes?
  100. What are watches?
  101. What problems can be addressed by using Zookeeper?
  102. What are different modes of execution in Apache Pig?
  103. Explain about co-group in Pig.
  104. Explain about the SMB Join in Hive.
  105. How can you connect an application, if you run Hive as a server?
  106. What does the overwrite keyword denote in Hive load statement?
  107. What is SerDe in Hive? How can you write your own custom SerDe?
  108. What are the stable versions of Hadoop?
  109. What is Apache Hadoop YARN?
  110. Is YARN a replacement of Hadoop MapReduce?
  111. Explain about the different channel types in Flume. Which channel type is faster?
  112. Which is the reliable channel in Flume to ensure that there is no data loss?
  113. Explain about the replication and multiplexing selectors in Flume.
  114. How multi-hop agent can be setup in Flume?
  115. What are the basic differences between relational database and HDFS?
  116. List the difference between Hadoop 1 and Hadoop 2.
  117. What are active and passive “NameNodes”?
  118. Mention how many InputSplits is made by a Hadoop Framework?
  119. Mention what is distributed cache in Hadoop?
  120. Explain how does Hadoop Classpath plays a vital role in stopping or starting in Hadoop daemons?
  121. How does the framework of Hadoop work or How hadoop works?
  122. Give me any three differences between NAS and HDFS?
  123. What do you mean my column families? What happens if the size of Column Family is alterated?
  124. What is the difference between HBase and Hive?
  125. What do you mean by the term speculative execution in hadoop?
  126. How is HDFS fault tolerant?
  127. Can NameNode and DataNode be a commodity hardware?
  128. Why do we use HDFS for applications having large data sets and not when there are a lot of small files?
  129. How do you define “block” in HDFS? What is the default block size in Hadoop 1 and in Hadoop 2? Can it be changed?
  130. What does ‘jps’ command do?
  131. How do you define “Rack Awareness” in Hadoop?
  132. What is Speculative Execution in Hadoop?
  133. What is the most complex problem the company is trying to solve using Apache Hadoop?
  134. Will I get an opportunity to attend big data conferences? Or will the organization incur any costs involved in taking advanced hadoop or big data certification?
  135. What are the challenges that you faced when implementing hadoop projects?
  136. How were you involved in data modelling, data ingestion, data transformation and data aggregation?
  137. What is your favourite tool in the hadoop ecosystem?
  138. In you previous project, did you maintain the hadoop cluster in-house or used hadoop in the cloud?
  139. Mention what is the difference between an RDBMS and Hadoop?
  140. Mention Hadoop core components?
  141. What is NameNode in Hadoop?
  142. Mention what are the data components used by Hadoop?
  143. Mention what is the data storage component used by Hadoop?
  144. Mention what are the most common input formats defined in Hadoop?
  145. In Hadoop what is InputSplit?
  146. For a Hadoop job, how will you write a custom partitioner?
  147. For a job in Hadoop, is it possible to change the number of mappers to be created?
  148. Explain what is a sequence file in Hadoop?
  149. What happens if you try to run a Hadoop job with an output directory that is already present?
  150. How can you debug Hadoop code?
  151. What is “speculative execution” in Hadoop?
  152. How can I restart “NameNode” or all the daemons in Hadoop?
  153. What is the difference between an “HDFS Block” and an “Input Split”?
  154. Name the three modes in which Hadoop can run.
  155. What is “MapReduce”? What is the syntax to run a “MapReduce” program?
  156. What are the main configuration parameters in a “MapReduce” program?
  157. State the reason why we can’t perform “aggregation” (addition) in mapper? Why do we need the “reducer” for this?
  158. What is the purpose of “RecordReader” in Hadoop?
  159. Explain “Distributed Cache” in a “MapReduce Framework”.
  160. How do “reducers” communicate with each other?
  161. What does a “MapReduce Partitioner” do?
  162. How will you write a custom partitioner?
  163. What is a “Combiner”?
  164. What do you know about “SequenceFileInputFormat”?
  165. What are the benefits of Apache Pig over MapReduce?
  166. What are different data types in Pig Latin?
  167. What are the different relational operations in “Pig Latin” you worked with?
  168. What is a UDF?
  169. What is “SerDe” in “Hive”?
  170. Explain the differences between Hadoop 1.x and Hadoop 2.x
  171. What are the core changes in Hadoop 2.0?
  172. Differentiate between NFS, Hadoop NameNode and JournalNode.
  173. What are the modules that constitute the Apache Hadoop 2.0 framework?
  174. How is the distance between two nodes defined in Hadoop?
  175. What is the size of the biggest hadoop cluster a company X operates?
  176. For what kind of big data problems, did the organization choose to use Hadoop?
  177. What kind of data the organization works with or what are the HDFS file formats the company uses?
  178. When Namenode is down what happens to job tracker?
  179. Explain how indexing in HDFS is done?
  180. Explain is it possible to search for files using wildcards?
  181. List out Hadoop’s three configuration files?
  182. Explain how can you check whether Namenode is working beside using the jps command?
  183. Explain what is “map” and what is “reducer” in Hadoop?
  184. In Hadoop, which file controls reporting in Hadoop?
  185. For using Hadoop list the network requirements?
  186. Mention what is rack awareness?
  187. Explain what is a Task Tracker in Hadoop?
  188. Explain how can you debug Hadoop code?
  189. Explain what is storage and compute nodes?
  190. Mention what is the use of Context Object?
  191. Mention what is the next step after Mapper or MapTask?
  192. Mention what is the number of default partitioner in Hadoop?
  193. Explain what is the purpose of RecordReader in Hadoop?
  194. Explain how is data partitioned before it is sent to the reducer if no custom partitioner is defined in Hadoop?
  195. Explain what happens when Hadoop spawned 50 tasks for a job and one of the task failed?
  196. Mention what is the best way to copy files between HDFS clusters?
  197. How to configure Replication Factor in HDFS?
  198. Can free form SQL queries be used with Sqoop import command? If yes, then how can they be used?
  199. Differentiate between Sqoop and distCP.
  200. What are the limitations of importing RDBMS tables into Hcatalog directly?
  201. What are the benefits of using counters in Hadoop?
  202. How can you write a customer partitioner?
  203. What are some of the jobs that job trackers do?
  204. How will you describe a sequence file?
  205. Tell us about the ways of executing in Apache Pig?
  206. How to compress mapper output but not the reducer output?
  207. What is the difference between Map Side join and Reduce Side Join?
  208. How can you transfer data from Hive to HDFS?
  209. What companies use Hadoop, any idea?
  210. Explain “Big Data” and what are five V’s of Big Data?
  211. What is Hadoop and its components.
  212. What are HDFS and YARN?
  213. What all modes Hadoop can be run in?
  214. What is SequenceFile in Hadoop?
  215. What is Job Tracker role in Hadoop?
  216. Tell me about the various Hadoop daemons and their roles in a Hadoop cluster.
  217. Compare HDFS with Network Attached Storage (NAS).
  218. What is a rack awareness and on what basis is data stored in a rack?
  219. What happens to a NameNode that has no data?
  220. What happens when a user submits a Hadoop job when the NameNode is down- does the job get in to hold or does it fail.
  221. What happens when a user submits a Hadoop job when the Job Tracker is down- does the job get in to hold or does it fail.
  222. Whenever a client submits a hadoop job, who receives it?
  223. Explain the usage of Context Object
  224. What are the core methods of a Reducer?
  225. Explain about the partitioning, shuffle and sort phase
  226. How to write a custom partitioner for a Hadoop MapReduce job?
  227. When should you use HBase and what are the key components of HBase?
  228. What are the different operational commands in HBase at record level and table level?
  229. What is Row Key?
  230. Explain the difference between RDBMS data model and HBase data model
  231. Explain about the different catalog tables in HBase?
  232. What is column families? What happens if you alter the block size of ColumnFamily on an already populated database?
  233. Explain the difference between HBase and Hive.
  234. Explain the process of row deletion in HBase
  235. What are the different types of tombstone markers in HBase for deletion?
  236. Explain about HLog and WAL in HBase.
  237. Explain about some important Sqoop commands other than import and export.
  238. How Sqoop can be used in a Java program?
  239. What is the process to perform an incremental data load in Sqoop?
  240. Is it possible to do an incremental import using Sqoop?
  241. Many more on the hadoop online training

…………………………………….

And many more Hadoop Online Training Interview Questions

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