1 / 8

Hadoop Online Training course c

Online Bigdata Hadoop Training in USA also Hyderabad, RStrainings is providing classroom & Online Training on Hadoop Bigdata. Our Trainers are real time work experience with 12 years. We allocate Trainings on Hadoop globally UK, India, Aus, Canada, Saudi, Singapore

RSTrainings
Download Presentation

Hadoop Online Training course c

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. www.rstrainings.com Contactus:-9052699906 HADOOPONLINETRAININGCOURSECONTENT: Duringthiscourse,youwilllearn:  IntroductiontoBigDataandAnalytics  IntroductiontoHadoop  Hadoopecosystem-Concepts  HadoopMap-reduceconceptsandfeatures  Developingthemap-reduceApplications  Pigconcepts  Hiveconcepts  Sqoopconcepts  FlumeConcepts  Oozieworkflowconcepts  ImpalaConcepts  HueConcepts  HBASEConcepts  ZooKeeperConcepts  RealLifeUseCases ReportingTool

  2. Tableau 1.Virtualbox/VMWare Basics Installations Backups Snapshots 2.Linux Basics Installations Commands 3.Hadoop WhyHadoop? Scaling DistributedFramework Hadoopv/sRDBMS Briefhistoryofhadoop 4.Setuphadoop Pseudomode Clustermode Ipv6 Ssh Installationofjava,hadoop Configurationsofhadoop HadoopProcesses(NN,SNN,JT,DN,TT) Temporarydirectory UI

  3. Commonerrorswhenrunninghadoopcluster,solutions 5.HDFS-HadoopdistributedFileSystem HDFSDesignandArchitecture HDFSConcepts InteractingHDFSusingcommandline InteractingHDFSusingJavaAPIs Dataflow Blocks Replica 6.HadoopProcesses Namenode Secondarynamenode Jobtracker Tasktracker Datanode 7.MapReduce DevelopingMapReduceApplication PhasesinMapReduceFramework MapReduceInputandOutputFormats AdvancedConcepts SampleApplications Combiner 8.JoiningdatasetsinMapreducejobs Map-sidejoin Reduce-Sidejoin

  4. 9.Mapreduce–customization CustomInputformatclass HashPartitioner CustomPartitioner Sortingtechniques CustomOutputformatclass 10.HadoopProgrammingLanguages:- I.HIVE Introduction InstallationandConfiguration InteractingHDFSusingHIVE MapReduceProgramsthroughHIVE HIVECommands Loading,Filtering,Grouping…. Datatypes,Operators….. Joins,Groups…. SampleprogramsinHIVE II.PIG Basics InstallationandConfigurations Commands…. OVERVIEWHADOOPDEVELOPER 11.Introduction 12.TheMotivationforHadoop Problemswithtraditionallarge-scalesystems Requirementsforanewapproach

  5. 13.Hadoop:BasicConcepts AnOverviewofHadoop TheHadoopDistributedFileSystem Hands-OnExercise HowMapReduceWorks Hands-OnExercise AnatomyofaHadoopCluster OtherHadoopEcosystemComponents 14.WritingaMapReduceProgram  TheMapReduceFlow  ExaminingaSampleMapReduceProgram  BasicMapReduceAPIConcepts  TheDriverCode  TheMapper  TheReducer  Hadoop’sStreamingAPI  UsingEclipseforRapidDevelopment  Hands-onexercise  TheNewMapReduceAPI 15.CommonMapReduceAlgorithms SortingandSearching Indexing MachineLearningWithMahout TermFrequency–InverseDocumentFrequency WordCo-Occurrence Hands-OnExercise.

  6. 16.PIGConcepts.. DataloadinginPIG. DataExtractioninPIG. DataTransformationinPIG. HandsonexerciseonPIG. 17.HiveConcepts.  HiveQueryLanguage.  AlterandDeleteinHive.  PartitioninHive.  Indexing.  JoinsinHive.Unionsinhive.  Industryspecificconfigurationofhiveparameters.  Authentication&Authorization.  StatisticswithHive.  ArchivinginHive.  Hands-onexercise 18.WorkingwithSqoop Introduction. ImportData. ExportData. SqoopSyntaxs. Databasesconnection. Hands-onexercise 19.WorkingwithFlume Introduction. ConfigurationandSetup.

  7. FlumeSinkwithexample. Channel. FlumeSourcewithexample. Complexflumearchitecture. 20.OOZIEConcepts 21.IMPALAConcepts 22.HUEConcepts 23.HBASEConcepts 24.ZooKeeperconcepts ReportingTool.. Tableau Thiscourseisdesignedforthebeginnertointermediate-levelTableauuser.Itisforanyonewhoworkswithdata–regardlessoftechnicaloranalyticalbackground.ThiscourseisdesignedtohelpyouunderstandtheimportantconceptsandtechniquesusedinTableautomovefromsimpletocomplexvisualizationsandlearnhowtocombinethemininteractivedashboards. CourseTopics Overview Whatisvisualanalysis? strengths/weaknessofthevisualsystem. LayingtheGroundworkforVisualAnalysis AnalyticalProcess Preparingforanalysis Getting,CleaningandClassifyingYourData Cleaning,formattingandreshaping. Usingadditionaldatatosupportyouranalysis. Dataclassification VisualMappingTechniques VisualVariables:BasicUnitsofDataVisualization WorkingwithColor

  8. Marksinaction:Commoncharttypes SolvingReal-WorldProblemswithVisualAnalysis GettingaFeelfortheData-ExploratoryAnalysis. Makingcomparisons Lookingat(co-)Relationships. Checkingprogress. SpatialRelationships. Try,tryagain. CommunicatingYourFindings Fine-tuningformoreeffectivevisualization Storytellingandguidedanalytics Dashboards OurOnlineServicesprovidingworldwidelikeAsia,Europe,America,Africa,Sweden,NorthKorea, SouthKorea,Canada,Netherland,Itely,Russia,Israel,NewZealand,Norway,Singapore,Malasia,etc

More Related