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big data hadoop certification course

Big Data Hadoop Certification Kosi Nokudzidziswa

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Vateereri & Prerequisites

Course Outline

Purogiramu nemitengo

kutaura kuti ichokwadi

Big Data Hadoop Certification Course Overview

Iyo yakazara Hadoop Big Data Training course yakagadzirwa nevashambadziri vezvikwata vachifunga nezvemazuva ano emishandiro emabasa ekupa ruzivo rwakadzika pazvinhu zvikuru uye Hadoop Modules. Iyi ndiyo mabhizimisi akacherechedza Big Data certification training course iyo inobatanidza mafundo ekudzidzisa muHadoop developer, Hadoop mutungamiriri, Hadoop kuongororwa, uye analytics. Ichi Cloudera Hadoop kurovedzwa kuchakugadzirira iwe kubvisa guru dhidziro yezvinyorwa.

zvinangwa

  • Mudzidzisi weHadoop 2.7 uye YARN uye nyora zvidzidzo uchishandisa
  • Kugadzira Pseudo node uye Multi node cluster pa Amazon EC2
  • Tenzi HDFS, MepuReduce, Hive, Nguruve, Oozie, Sqoop, Flume, Zookeeper, HBase
  • Dzidza Spark, Spark RDD, Graphx, MLlib kunyora Spark applications
  • Master Hadoop kutungamira mabasa akaita seboka rekuchengetedza, kutarisa, kutungamira uye kukonzera matambudziko
  • Kugadzira zvigadzirwa zve ETL sePentaho / Talend kushanda neMapReduce, Hive, Pig, nezvimwe
  • Kunzwisisa zvakanyanya Big Big analytics
  • Hadoop kuedza kushandiswa kuburikidza naM MR Unit uye mamwe mashandisi ekushandisa.
  • Shandisa neAro data mafomu
  • Iva nemishonga chaiyo yehupenyu uchishandisa Hadoop uye Apache Spark
  • Iva akakagadzirira kubvisa Big Data Hadoop Certification.

chinangwa Audience

  • Programming Developers uye System Administrators
  • Une ruzivo rwekushanda vashandi, Project managers
  • Big DataHadoop Vanokurudzira vanoda kudzidza mamwe maonero akadai kuedza, Analytics, Administration
  • Mainframe Professionals, Architects & Testing Professionals
  • Business Intelligence, Data rerehousing uye Analytics Vadzidzi
  • Vapedza kudzidza, undergraduates vanoda kudzidza ruzivo rweBig Data teknolojia itsva vanogona kutora iyi Big Data Hadoop Certification online yekudzidzisa

Zvinotarisirwa

  • Hapana chakafanirwa kutanga kutora iyi Big data kudzidziswa uye kuziva Hadoop. Asi nheyo dzeUNIX, SQL uye java dzaizova dzakanaka.Iye Intellipaat, tinopa humwe unyanzvi we unix neJava course neBig Data rekudzidziswa mazano kuti tishandise unyanzvi hunodiwa kuitira kuti iwe ufare kwauri Hadoop yekudzidza nzira.

Nzira Yokubuda Nenguva Inguva: 2 Days

Nhanganyaya yeBig Data & Hadoop uye Ecosystem, Mepu Reduce uye HDFS

Chii chinonzi Big Data, Ndeipi iyo Hadoop inopindira, Hadoop Distributed File System - Zvinyorwa, Zvidzidzo zveBlock, Secondary Namenode, High Availability, Kunzwisisa YARN - ResourceManager, NodeManager, Kusiyana pakati pe1.x uye 2.x

Hadoop Installation & setup

Hadoop 2.x Cluster Architecture, Federation uye High Availability, A Typical Production Cluster setup, Hadoop Cluster Modes, Common Hadoop Shell Mitemo, Hadoop 2.x Kugadzirisa Files, Cloudera Single cluster cluster

Deep Dive in Mapreduce

Izvo Mapreduce Inoshanda Sei, Inoshandiswa Sei Inoshandiswa, Nharairi Dzairi Kushanda, MaCombiners, Vachidimbu, Mafomu EkuInyore, Mafomu Okubuda, Shugure uye Kuronga, Mappati Akabatana, Kuderedza Chikamu Chibatana, MRUnit, Distributed Cache

Lab inoshandisa:

Kushanda neHoldFS, Kunyora WordCount Program, Kuverenga tsika yechidimbu, Mapreduce neKubatanidza, Mepu Chete Join, Chengetedza Chikamu Chibatana, Chikwata Chekuona Mapreduce, Running Mapreduce muJapanJobRunner Mode

Girafu Matambudziko Kugadzirisa

Chii chinonzi Girafu, Chimiro cheGrafu, Breadth kutanga Tsvakurudzo yeAlgorithm, Girafu Chimiro cheMepu Inowedzera, Nzira yekuita nayo Girafu Algorithm, Muenzaniso weGirafu Mepu Reduce,

    Dzidzirai 1: Kuedza 2: Kuedza 3:

Kunzwisisa zvakanyanya kwePig

A. Mharidzo yePig

Kunzwisisa Apache Pig, izvo zvinoshandiswa, kushandiswa zvakasiyana-siyana uye kudzidza kudzidza nePig

B. Kutumira Pig kuti iongorore kudarika

Mutsara wePig Latin, tsanangudzo dzakasiyana-siyana, dudzi rwenzira uye firati, marudzi e data, kutumira Pig ye ETL, kudheta dheta, schema kutarisa, tsanangudzo yemunda, mabasa anowanzoshandiswa.

C. Nguruve kuti zvive zvakanyatsogadziriswa kwedhesi

Nhamba dzakasiyana-siyana dzemhando dzinosanganisira dzakasvibiswa uye dzakaoma, kushandura data nePig, yakagadzira data iteration, maitiro anobatsira

D. Kuita mabasa akawanda e dataset

Dhiyabhorosi yakabatana, deta yakagadzikana kuparadzaniswa, nzira dzakasiyana-siyana dzekuiswa zvakagadzirirwa kusanganiswa, kuisa maitiro, maoko-pane zvekuita

E. Kuwedzera Pig

Kunzwisisa kushandiswa kwemashandisirwo emabasa, kuita kudhinda kwedzimwe nedzimwe mitauro, kutengeswa uye macros, kushandisa shanduro uye UDFs kuwedzera Pig, maitiro anobatsira

F. Pig Job Jobs

Kushanda nemagadzirirwe ezvinyorwa zvinosanganisira Walmart uye Electronic Arts semhosva yekudzidza

Kunzwisisa zvakanyanya Hive

A. Hive Chikamu

Kunzwisisa Hive, tsika dzekuda kufanana neHive, Pig uye Hive kufananidza, kuchengetedza data muHive neHive schema, Kubatana kweHive uye kushandiswa kwakasiyana-siyana kweHive

B. Hive yekuongorora dhesekodhi

Kunzwisisa HiveQL, mazwi ekutanga, mazita akasiyana-siyana uye mabhuku akasiyana-siyana, nhamba dzematafura, zvakagadzirirwa deta zvakabatana, zvakasiyana-siyana zvakagadzirwa, kutumira mibvunzo yeHive pane zvinyorwa, shell uye Hue.

C. Kutungamirirwa kweDhina neHive

Zvinyorwa zvakasiyana-siyana, zvisikwa zvemashoko edzimba, zvigadziro zve data muHive, data modeling, Tables yakachengetwa Tables, Tables dzinogadziriswa, dheinhau yekushandisa, kushandura databases neTables, kubvunza zvinyorwa ne Views, sarudzo yekuchengetedza mibvunzo, kushandiswa kwekugona kuwana, kuchengetedza dhenda pamwe neHive, Hive Metastore uye Thrift server.

D. Kugadzirwa kweHive

Kudzidza kushanda kwekutsvaga, kudonongodza deta, kuparadzanisa uye kubheta

E. Kuwedzera Hive

Kuendesa kushandiswa kwemudziri mabasa ekuwedzera Hive

F. Maoko paKuedza - kushanda nematafura makuru etafura uye kuwedzera kukurukura

Kutumira Hive nokuda kwehurukuro yakawanda ye data uye yakawanda yekutengesa

G. UDF, mubvunzo wekushanda

Kushanda zvakazara ne User User Defined Queries, kudzidza nzira yekugadzirisa mibvunzo, nzira dzakasiyana dzekuita kugadzirisa kugadzirisa.

Impala

A. Kutanga ku Impala

Chii chinonzi Impala ?, Iyo Impala Inoparadzaniswa Sei neHive neGuru, Iyo Impala Inoparadzaniswa Sei neHouse Relational Databases, Zvigumisiro uye Mazano Ekuzotevera, Kushandisa Impala Shell

B. Kusarudza Zvakanakisisa (Hive, Nguru, Impala)

C. Kuenzanisa uye Kutarisa Dhidhiyo neImpala neHive

Data Storage Data, Kuumba Databases neTables, Loading Data muTables, HCatalog, Impala Metadata Caching

D. Dhairiro Dhairiro

Kugoverana Mukuona, Kugoverana mu Impala uye Hive

(AVRO) Data Formats

Kusarudza File File, Support Tool yeFomu Formats, Avro Schemas, Kushandisa Avro neHive neSqoop, Avro Schema Evolution, Compression

Nhanganyaya kumapuranga eHibase

Chii chinonzi Hbase, Inobatana kupi, Chii chinonzi NOSQL

Apache Spark

A. Sei Spark? Kushanda neSpark uye Hadoop Kuparadzirwa File System

Chii chinonzi Spark, Kuenzanisa pakati peSpark naHadoop, Components of Spark

B. Spark Zvikamu, Common Spark Maitiro-Iterative Algorithms, Grafu Analysis, Machine Learning

Apache Spark- Kutanga, Kubatana, Kuwanika, Kugovera, Kubatana kweSpark Spark, Spark Components, Scalding muenzaniso, mutariri, dutu, grafu

C. Kumhanya Kunopinda Cluster, Kunyora Spark Applications uchishandisa Python, Java, Scala

Tsanangurai pirthon muenzaniso, Ratidza kuisa mararamiro, Tsanangura chirongwa chekufambisa, Tsanangudzo yemamiriro ezvinhu epakisi nemuenzaniso, Tsanangura zvinyorwa zvisingatauriki zvakasiyana, Shandisai scala uye java musina chinyararire, Tsanangura kubvumirana nekuparadzanisa., Tsanangura kuti chii chiito, Tsanangurai basa rakakwirira rekuronga nemuenzaniso, Tsanangura OFI Scheduler, Kubatsira kweSpark, Muenzaniso weRamda uchishandisa spark, Tsanangura Mapreduce nemuenzaniso

Hadoop Cluster Setup uye Running Map Mutsvaga Mabasa

Multi Node Cluster Setup achishandisa Amazon ec2 - Kugadzira 4 node musikisi setset, Running Map Kupedza Mabasa paCluster

Major Project - Kuzviisa pamwe chete uye Connecting Dots

Kuzviisa pamwe chete uye Kubatanidza Dots, Kushanda neGadzira hurukuro dzezvinhu, Maitiro anobatanidzwa pakuongorora deta huru

ETL Kutaurirana neHadoop Ecosystem

Nzira dzeTL dzinoshanda sei muDhiyabhorosi Dhidha Dzakawanda, Kubatanidza kuHDFS kubva pane ETL nekugadzirisa demo kubva kuNzvimbo yeChechi kusvika kuHDFS, Moving Data kubva kuDBMS kusvika kuHDFS, Kushanda neHive ne ETL Tool, Kugadzira Mepu Kuchera basa muTL tool, Kuguma Kusvikira ETL PoC inoratidza hurukuro yekubatanidza neT ET tool.

Cluster Configuration

Kugadzirisa zvakananga uye zvakakosha mafaira, Zvigadziridzo zvigadziro uye mararamiro, HDFS maparisa MapReduce zviyero, Hadoop mamiriro ekugadzirisa, 'Itai kuti' uye 'Regai' mafaira ekugadzirisa, Bhuku: MapReduce Performance Tuning

Kutarisira uye Maintenance

Namenode / Datanode zvinyorwa uye mafaira, Faira system image uye Edit log, The Checkpoint Procedure, Namenode kusagadzikana uye kugadzirisa nzira, Safe Mode, Metadata uye Dhavhadzo dzeDhina, Matambudziko anokwanisa uye mhinduro / chii chaunotarisa, Kuwedzera uye kubvisa node, Lab: MepuReduce Faira system Kudzoka

Kuongorora uye Kutarisa Matambudziko

Nzira dzakanakisisa dzekutarisa musumbu, Kushandisa matanda uye matanho ekutsvaga nekugadzirisa matambudziko, Kushandisa zvigadziriswa zvitubu zvekutarisa musango

Job Scheduler: Mepu inoderedza basa kuendesa basa

Maitiro ekugadzirisa Mabasa pane imwe musumbu, FIFO Purogiramu, Fair Scheduler uye hurongwa hwayo

Multi Node Cluster Setup uye Running Map Mutsvaga Mabasa pa Amazon Ec2

Multi Node Cluster Setup achishandisa Amazon ec2 - Kugadzira 4 node musikisi setset, Running Map Kupedza Mabasa paCluster

ZOOKEEPER

ZOOKEEPER Mharidzo, ZOOKEEPER dzinoshandisa matambudziko, ZOOKEEPER Services, ZOOKEEPER data Dhigirii, Znodes nemhando dzayo, Znodes maitiro, Znodes maziso, Znodes dzinoverengeka uye dzinonyora, Kubvumirana kweZvimbiso, Cluster management, Leader Election, Distributed Exclusive Lock, Pfungwa dzinokosha

Kupfuura Oozie

Nei Oozie ?, Kuisa Oozie, Kutanga muenzaniso, Oimi- injini yekufambisa, Muenzaniso M / R maitiro, Shoko rekuverengwa kweShoko, Kushanda kwekushanda kweBasa, Kuenderera kweKushanda kweBasa, Kushandiswa kweBasa rekushanda, Oozie kushanda basa, Oozie kuchengetedzwa, Sei Oozie kuchengetedzwa? , Multi-tenancy and scalability, Time line of Oozie basa, Coordinator, Bundle, Layers of abstraction, Architecture, Shandisa Case 1: nguva inotanga, Shandisa Case 2: data uye nguva zvinotanga, Shandisa Case 3: firiji

Advance Flume

Maererano neApache Flume, Zvinyorwa zvakaparadzirwa Dhiyabhorosi, Kuchinja shanduko yeData, Kutarisa kutarisa, Anatomy yePlume, Core concepts, Chiitiko, Vatengi, Vashandi, Chitubu, Chiteshi, Sinks, Interceptors, Chiteshi chesheni, Sink processor, Data ingest, Agent pipeline , Transactional data exchange, Routing uye replicating, Sei makirasi ?, Shandisa kero-Log aggregation, Kuwedzera agarisi veseti, Kutarisira furasi yevavharesi, Dhiyabhorosi yemavhidhiyo neanoshanda, Muenzaniso unotsanangura imwe node yefume

Pfuura HUE

Nheyo yeHUE, nzvimbo yeHUE, Ndeipi HUE ?, HUE maonero enyika chaiwo, Makomborero eHUE, Sei mazaira data muFiri Browser ?, Tarisa zviri mukati, Kubatanidza vashandisi, Kubatanidza HDFS, Zvimwe zvinokosha zveZVIMBO

Advance Impala

IMPALA Overview: Zvinangwa, User View of Impala: Overview, User view of Impala: SQL, User view of Impala: Apache HBase, Impala mapurisa, Impala gorozi rezvematongerwo enyika, Impala kambani yebasa rekutengesa, Kuongorora kutsvaga, Kuenzanisa Impala kuHive

Hadoop Application Testing

Chikonzero nei kuongorora kuchikosha, Chikwata chekuongorora, Kuongororwa kwekuongorora, Kuongororwa kwekushanda, Kuongorora, Nighting QA kuedza, Benchmark uye kuguma kusvika pakupera kwekuedzwa, Kushandiswa kwekuongorora, Kusununguka kuongororwa, Kuongorora kwekuchengetedzwa, Scalability Testing, Kutumira uye Kuparadzanisa kweData Nodhi Kuedza, Kuvimbika kuedza , Bvisa kuedzwa

Basa uye Basa reHadoop Testing Professional

Kunzwisisa Chidimbu, Kugadzirira kwekuongororwa kwekuedzwa, Test Test, Test Test, Test Execution, Defect Reporting, Defect Retest, Daily Retriever report report, Kupedzwa kwekuedzwa, ETL kuongorora pazvikamu zvose (HDFS, HIVE, HBASE) panguva Kutakura zvinyorwa (zvigwaro / mafaira / zvinyorwa nezvimwewo) uchishandisa sqoop / flume iyo inosanganisira asi isingakwanisi kugadziriswa kwepa data, Kuyanana, Kubvumirwa kweVashandi uye Kuongorora kweKutendeseka (Makira, Vashandi, Ropafadzo nezvimwewo), Ratidza kukanganisa kumusangano wekufambisa kana maneja uye kutyaira kuti vadzivirire, Simbisai zvose zvakashata uye tive nekukanganisa mishumo, Kuvimbisa zvitsva uye nyaya muCore Hadoop.

Chimiro chinonzi MR Unit chekuongororwa kweMapu-Kuderedza Mapurogiramu

Rondedzera kukanganisa kumusangano wekufambisa kana mutungamiri uye kuvadzinga kuti vadzivirire, Kubatanidza zvese zvakashata uye kugadzira zvinyorwa zvisiri izvo, Kuzvigadzirisa pakusarudza Chigadziro chinonzi MR Unit chekuongororwa kweMapu-Kuderedza mapurogiramu.

Unit Testing

Automation test using OOZIE, Data kugadziriswa uchishandisa chirwere chekutsvaga mhinduro.

Kuedzwa Kuedzwa

Chirongwa chekuedza cheHDFS chivandudzire, Chengetedza maitiro uye chigumisiro

Chirongwa chekuedza Nzira nekunyora Mhosva Dambudziko rekuedza Hadoop Application

Nzira yekuedza sei kuisa nekugadzirisa

Jobho uye Chivimbiso Kutsigira

Cloudera Certification Tips uye Nhungamiro uye Kunetseka Kukurukurirana Kugadzirira, Kubatsira Kunobatsira Mazano uye Nyanzvi

Ndapota nyorera kwatiri info@itstechschool.com & taura nesu pa + 91-9870480053 pamutengo wematengo & chikwata chemari, purogiramu & nzvimbo

Dhidzai Mhinduro

Iyi dzidzo yekudzidzira yakagadzirirwa kukubatsira kuti ujekese zvose Cloudera Spark uye Hadoop Developer Certification (CCA175) kuongorora uye Cloudera Certified Administrator for Apache Hadoop (CCAH) kuongorora. Iyo yose yekudzidzira zvidzidzo zvayo inowirirana nezvirongwa zviviri izvi zvekudzidziswa uye inokubatsira kuti ujekese izvi zviongorori zvidzidzo nekunyatsoona uye uwane mabasa akanakisisa mumatunhu makuru eMNCs.

Sezvimwe chikamu chekudzidzisa uku iwe uri kushanda panguva chaiyo yemapurogiramu uye nheyo dzinobatanidzwa zvikuru mumamiriro ezvinhu chaiwo emabhizimisi enyika zvichikubatsira kuti uite zvakananga basa rako pasina.

Pakupedzisira kwepurogiramu iyi yekudzidzira pachava nemibvunzo inonyatsoratidza rudzi rwemibvunzo yakabvunzwa muzvidzidzo zvakarongerwa zviyeuchidzo uye inobatsira kuti ureve mararamiro akanaka mukutaridzirwa kwechidziro.

ITS Course Completion Certificate ichapiwa pakupera kwebasa rePurojekiti (pane nyanzvi yekuongorora) uye pamusoro pekutsvaga 60% mavara mumibvunzo. Intellipaat certification inozivikanwa zvakanaka pamusoro pe 80 + MNCs sa Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, nezvimwe.

Kuti uwane mamwe mashoko nemutsa Taura nesu.


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