TypeHo Koetlisa Sekolo
Ngodisa
e kholo dintlha data hadoop certification

Big Data Hadoop Certification Course & Koetliso

Overview

Bamameli le Litlhokahalo

Tlhahiso ea Tlhahlobo

Kemiso le Litefiso

tiiseletswe

Big Data Hadoop Certification Course Tlhahlobo

Ke thuto e fapaneng ea Hadoop Big Data e entsoeng ke litsebi tsa indasteri tse nahanang ka mekhoa ea hona joale ea indasteri ea mesebetsi ho fana ka thuto e tebileng ho data e kholo le Hadoop Modules. Ena ke indasteri e nang le koetliso ea koetliso ea Big Data e kopantseng lithupelo tsa Hadoop, mookameli oa Hadoop, tlhahlobo ea Hadoop le analytics. Sena Cloudera Koetliso ea Hadoop e tla u lokisetsa ho hlakola setifikeiti se seholo sa dintlha.

maikemisetso

  • Mongolo o ka sehloohong oa Hadoop 2.7 le YARN mme o ngola likopo ho li sebelisa
  • Ho theha node ea pseudo le cluster e mengata ho Amazon EC2
  • Mongolo oa HDFS, Mapolesa, Mapheo, Likolobe, Kolobe, Oozie, Sqoop, Flume, Zookeeper, HBase
  • Ithute Spark, Spark RDD, Graphx, MLlib ho ngola lisebelisoa tsa Spark
  • Master Hadoop tsamaiso ea mesebetsi e kang lekala la ho laola, ho hlahloba, tsamaiso le ho rarolla mathata
  • Ho beha lithulusi tsa ETL tse kang Pentaho / Talend ho sebetsa le MapReduce, Hive, pig, joalo-joalo
  • Tlhaloso e qaqileng ea lik'hamphani tsa Big Data
  • Hadoop tlhahlobo ea lisebelisoa ho sebelisa MR Unit le lisebelisoa tse ling tsa motlakase.
  • Sebetsa ka liforomo tsa Avro tsa data
  • Sebelisa merero ea sebele ea bophelo ka Hadoop le Apache Spark
  • Itokiselitsoe ho hlakola Certification ea Big Data Hadoop.

o ne a rerile Bamameli

  • Ho Etsa Lenaneo la Bahlahlobi le Boemo ba Tsamaiso
  • Basebetsi ba nang le phihlelo, baokameli ba merero
  • Big DataHadoop Bahlahisi ba labalabela ho ithuta lintlheng tse ling tse kang Testing, Analytics, Administration
  • Mainframe Bo-rakhoebo, Bahahi ba meralo le Bo-rakhoebo ba ho hlahloba
  • Bohlale ba Khoebo, Boitsebiso ba Ditshebeletso le Boitsebiso ba Analytics
  • Liithuti, baruti ba tlase lithuto tsa maikemisetso ba lakatsang ho ithuta theknoloji ea morao-rao ea Big Data ba ka nka koetliso ena ea Big Data Hadoop Certification online

batlehang

  • Ha ho na se hlokehang pele ho nka koetliso ena e kholo ea data le ho tseba Hadoop. Empa lithuto tsa motheo tsa UNIX, SQL le java e ka ba tse ntle.A Intellipaat, re fana ka unix ea bonngoe le koetliso ea Java le koetliso ea rona ea Big Data tikoloho ho hlobolisa tsebo e hlokahalang e le hore u le molemo ho uena Hadoop mokhoa oa ho ithuta.

Nako ea Nako ea Tlhahlobo: Matsatsi a 2

Kenyelletso ho Big Data & Hadoop le Ecosystem, Map ea Reduction le HDFS

Big Data ke efe, Hadoop e hokae hokae, Hadoop Distributed File System - Likarabo, Thibelo ea Bohlokoa, Nako e Bohareng ea Namenode, Boemo bo Phahameng, Ho Utloisisa LITABA - ResourceManager, NodeManager, Phapang pakeng tsa 1.x le 2.x

Hadoop Ho kenya & setup

Hadoop 2.x Cluster Architecture, Federation le High Availability, Sebopeho se tloaelehileng sa Cluster sebopeho, Hadoop Cluster Modes, Common Hadoop Shell Melao, Hadoop 2.x Filing Files, Cloudera Single cluster

Pati e tebileng ho Mapreduce

Tsela eo Mapreduce e sebetsang ka eona, Hona e fokotsehang joang, Mokhoa oa ho khanna o sebetsang joang, Li-Combiners, Li-partitioners, Liforomo tsa ho kenya, Lihlahisoa tsa ho tsoa, ​​Phunyeletso le Thabo, Mapolanka a Kopana, Fokotsa lehlakoreng le kopane, MRUnit, Distributed Cache

Lab e sebelisa:

Ho sebetsana le HDFS, Ho ngola Sesebelisoa sa WordCount, Ho ngolla tloaelo ea mohlahlobi, Mapreduce le Moqhamane, 'Mapa oa Kopano Joang, O fokotsa lehlakoreng le kopane, Unit Testing Mapreduce, Running Mapreduce ka LocalJobRunner Mode

Graph Bothata ho rarolla

Sebopeho sa Grafu, Boemeli ba Boholo, Bohobe bo qalang Bobopeho ba Algorithm, Boemeli ba 'Mapa oa Mapolesa, Tsela ea ho etsa Graph Algorithm, Mohlala oa' Mapa oa K'homphieutha Ho fokotsa,

    Ho ikoetlisa 1: Ho ikoetlisa 2: Ho ikoetlisa 3:

Tlhaloso e qaqileng ea pig

A. Tšenolo ho Pariki

Ho utloisisa Apache Pig, likarolo, litšebeliso tse sa tšoaneng le ho ithuta ho sebelisana le Pig

B. Ho romela Pariki bakeng sa tlhahlobo ea lintlha

Tlhaloso ea Pig Latin, litlhaloso tse fapa-fapaneng, mofuta oa data le ho hloekisa, mefuta ea litlaleho, ho romela Pig bakeng sa ETL, ho kenya lintlha, ho sheba maqheka, litlhaloso tsa tšimo, mesebetsi e tloaelehileng e sebelisoang.

C. Kolobe bakeng sa ho rarahana ha data

Mefuta e sa tšoaneng ea data e kenyeletsang sehlaha le e rarahaneng, ho sebetsana le data le Pig, ho arola data iteration, boikoetliso bo sebetsang

D. Ho etsa mesebetsi e mengata ea dataset

Boitsebiso bo behiloe, ho arohanngoa ha data, mekhoa e sa tšoaneng ea boitsebiso bo sebelisitsoeng, ho beha liketso, matsoho a boikoetliso

E. Ho eketsa pig

Ho utloisisa mesebetsi e hlalositsoeng mosebetsing, ho etsa ts'ebetsong ea lipuo le lipuo tse ling, ho kenya lits'ebeletso le li-macros, ho sebelisa phallo le li-UDF ho atolosa Pig, mekhoa ea ho ikoetlisa

Mosebetsi oa F. Pig

Ho sebetsana le lisebelisoa tsa sebele tsa dintlha tse amanang le Walmart le Electronic Arts joaloka thuto ea nyeoe

Tlhaloso e qaqileng ea Hive

Kakaretso

Ho utloisisa mekhoa ea litloaelo, mekhoa ea setso le mekhoa ea mahae, ea kolobe le ea mahaeng, ho boloka boitsebiso ka hara Hive le Hive schema, ho sebelisana ha li-Hive le maemo a fapaneng a ho sebelisa mahlabu

B. Hive bakeng sa tlhahlobo ea litaba tsa moralo

Ho utloisisa HiveQL, syntax ea motheo, litafole tse fapa-fapaneng le marang-rang, mefuta ea data, mechine ea litlhaloso ho kopanya, mesebetsi e sa tšoaneng e hahiloeng, ho romela lipotso tsa Hive ka litokomane, shell le Hue.

C. Tsamaiso ea lits'ebeletso le Hive

Litlhaloso tse fapa-fapaneng, ho thehoa ha marang-rang, mekhoa ea boitsebiso mahaeng, mekhoa ea boitsebiso, lisebelisoa tse laoloang ke Li-Hive, litafole tse laolehileng, ho laola data, ho fetola litsamaiso le litafole, tlhahiso ea lipotso le maikutlo, ho boloka lipotso, ho boloka litlhaloso tsa data, ho laola data e nang le Hive, Metastore ea Hive le Sebapali se Sebetsang.

D. Khothaletso ea Li-Hive

Ho ithuta ts'ebetsong ea potso, boitsebiso ba data, ho arolelana le litlhapi

E. Ho atolosa Hive

Ho tlosa mesebetsi e hlalositsoeng ke mosebedisi bakeng sa ho atolosa Hive

F. Hands on Exercises - ho sebetsana le lisebelisoa tse kholo tsa dintlha le querying e tebileng

Ho tsamaisa Hive bakeng sa boholo ba lisebelisoa tsa lisebelisoa le boholo ba querying

G. UDF, potso ea tlhahiso-pele

Ho sebetsana haholo le Lipotso tse hlalositsoeng ke Basebetsi, ho ithuta ho ntlafatsa lipotso, mekhoa e fapaneng ea ho etsa ts'ebetso ea ts'ebetso.

Impala

Kakaretso ea Impala

Impala ke eng ?, Kamoo Impala e fapaneng kateng le Hive le Pig, Kamoo Impala e fapaneng kateng le Relationship Databases, Limitations le Litaelo tsa nakong e tlang, Ho sebelisa Shell ea Impala

B. Ho Khetha se Molemo ka ho Fetisisa (Mahabe, Kolobe, Impala)

C. Ho etsisa le ho laola Dintlha le Impala le Hive

Tshireletso ea Ditaba ka ho feletseng, Ho theha marang-rang le litafole, Tlatsetsa Ditaba tsa Tables, HCatalog, Impala Metadata Caching

D. Data Partitioning

Tlhaloso e arohaneng, Ho arolelana le Impala le Hive

(AVRO) Data Formats

Ho Khetha Fomati ea Mofuta, Tšehetso ea Tlhahiso bakeng sa Litokomane Tsa Fomoro, Avro Schemas, Ho Sebelisa Avro le Hive le Sqoop, Scheme Evolution, Compression

Tšimoloho ea thepa ea Hbase

Hbase ke eng, e lumellana hokae, NOSQL ke eng

Apache Spark

A. Ke hobane'ng ha Spark? Ho sebetsa le Spark le Hadoop Sesebelisoa sa Fumana

Se Spark ke eng, Ho bapisa pakeng tsa Spark le Hadoop, Lihlopha tsa Spark

B. Li-Spark Components, Common Spark Litsela-tsela tsa ho etsa lintho tse tloaelehileng, Litlhaloso tsa lihlopha, Lithuto tsa ho ithuta.

Apache Spark- Kenyelletso, ho lumellana, ho fumaneha, likarohano, Stack Spark Spark, Spark Components, mohlala oa Scalding, mohlokomeli, sefefo, graph

C. Running Spark on Cluster, Ho ngola Litlhaku tsa Spark sebelisa Python, Java, Scala

Hlalosa setšoantšo sa python, Bontša ho kenya marang-rang, Hlalosa lenaneo la mokhanni, Hlalosetsa moelelo oa marang-rang ka mohlala, Hlalosa moelelo o fokolang ka mokhoa o fokolang, Kopanya scala le java ka mokhoa o tsitsitseng, Hlalosetsa li-concurrency le ho ajoa., Hlalosa se boleloang ke eng, Hlalosa mosebetsi oa boemo bo phahameng ka mohlala, Hlalosa OFI Scheduler, Melemo ea Spark, Mohlala oa Lamda o sebelisa spark, Hlalosetsa Mapreduce ka mohlala

Hadoop Cluster Setup le Mapheo a Matha a Fokotsa Mosebetsi

Setlhopha se seholo sa Custer Cluster ho sebelisa Amazon ec2 - Ho theha setlhopha sa cluster ea node ea 4, Mapa oa ho matha ho fokotsa mesebetsi ho Cluster

Morero o Moholo - Ho o bokella hammoho le Connecting Dots

Ho li kopanya hammoho le Connecting Dots, Ho sebetsana le lisebelisoa tse kholo tsa lintlha, Mehato e amehang ho hlahloba lintlha tse kholo

ETL Hokahanngoa le Hadoop Ecology

Litsebelisoa tsa ETL li sebetsa joang Lefapheng la Boitsebiso bo Boholo, ho sebedisa HDFS ho tloha ho ETL le ho tsamaisa dintlha ho tswa ho tsamaiso ea sebakeng sa HDFS, ho tsamaisa DNA ho tloha DBMS ho HDFS, ho sebetsana le Hive ka ETL Tool, ho etsa Mapao ea ho fokotsa mosebetsi ho ETL, sesebelisoa sa ho felisa ETL PoC e bonts'a kopano e kholo ea data le sesebelisoa sa ETL.

Cluster Configuration

Boitsebiso bo hlophisitsoeng le boitsebiso bo bohlokoa ba setšoantšo, Lisebelisuoa tsa parameters le litekanyetso, mekhahlelo ea HDFS Mapolesa mekhahlelo, Hadoop setlhophiso sa tikoloho, 'Kenyeletsa' le 'Hlakola' lifaele tsa tokisetso, Lab: MapReduce Performance Tuning

Tsamaiso le Tlhokomelo

Meenode / Datanode mehaho le lifaele, Fumana setšoantšo sa setšoantšo le Edit log, Lenaneo la Checkpoint, Meenode e hlōleha le mokhoa oa ho hlaphoheloa, Safe Mode, Metadata le Backup data, Mathata le litharollo tse ka bang teng / Seo u ka se shebellang, Ho eketsa le ho tlosa litsi, Lab: 'Mapa oa ho Fokotsa Phatlalatso ea Fumana

Tlhokomelo le mathata a ho rarolla mathata

Mekhoa e metle ea ho shebella sehlopha, Ho sebelisa lintlha le mekhoa ea ho hlahloba le ho rarolla mathata, Ho sebelisa lisebelisoa tse bulehileng ho hlokomela sehlopha

Job Scheduler: 'Mapa o fokotsa phallo ea mosebetsi

Mokhoa oa ho hlophisa Mesebetsi ka sehlopheng se le seng, Holo ea FIFO, Fair Scheduler le setlhophiso

Mokhoa oa Mapolesa oa Litlhophiso le Mokhoa oa ho Sebetsa o Fokotsa Mesebetsi ka Amazon EQU2

Setlhopha se seholo sa Custer Cluster ho sebelisa Amazon ec2 - Ho theha setlhopha sa cluster ea node ea 4, Mapa oa ho matha ho fokotsa mesebetsi ho Cluster

SEBELETSO

MOKHATLO OA SEBELETSO, LITŠOANTŠISO li sebelisa lits'ebetso, Lits'ebetso tsa ZOOKEEPER, Tlhahlobo ea data ea ZOOKEEPER, Znodes le mefuta ea eona, Znodes tshebetso, Znodes litebello, Znodes li bala le ho ngola, Ts'ebetso ea ho lumellana, Ts'ebetso ea Cluster, Khetho ea Baeta-pele, Phatlalatso ea Li-Exclusive Lock, Lintlha tse bohlokoa

Tsoela Pele Oozie

Ke Hobane'ng ha Oozie ?, Ho kenya Oozie, Ho etsa mohlala, Oozi-mote ea mochini oa ho sebetsa, Mohlala M / R bohato, mohlala oa lentsoe la Word, Tlhahiso ea mosebetsi oa mosebetsi, Tlhaloso ea mosebetsi oa mosebetsi, Phetoho ea mosebetsi oa Oozie, ts'ireletso ea mosebetsi oa Oozie, Ke hobane'ng ha tšireletso ea Oozie? , Tlhokomelo e mengata le ho fokotseha, Nako ea nako ea mosebetsi oa Oozie, Mohokahanyi, Sesebelisoa, Lisebelisoa tsa ho qhelela, Boqapi, Sebelisa Tlhahlobo 1: Lintho tse qalang nako, Sebelisa Case 2: Lintho tse qalang ka nako le nako, Sebelisa Case 3: fensetere

Nakoana ea Flume

Tlhaloso ea Apache Flume, e fanoeng ka tlhaho Dintlha tsa mohloli, Ho fetola sebopeho sa Data, Ho sheba ka ho pharaletseng, Palo ea Flume, Maikutlo a maholo, Ketsahalo, Mecha ea baeti, Litsamaisi, Mohloli, Litsamaiso, Lits'ebetso, Litsamaisi, Khetho ea mocha, Mochine oa motlakase, Mochine oa data, Pipeline ea Agent , Transactional exchange transaction, Ho romela le ho pheta-pheta, Ke hobane'ng ha li-channel ?, Sebelisa likarolo-Lintlha tsa ho ngolisa, Ho eketsa moemeli oa flume, Ho sebetsana le polasing ea seva, Palo ea dintlha ka moemeli, Mohlala o hlalosang mokhoa o le mong oa ho ruruha ha flume

Tsoela Pele HUE

Kenyelletso ea HUE, tikoloho ea HUE, HUE ke eng, HUE pono ea sebele ea lefats'e, Melemo ea HUE, Joang ho kenya data ho Browser File ?, Sheba litaba, Ho kopanya basebedisi, Ho kopanya HDFS, Lintho tsa bohlokoa tsa KHATISO EA HUE

Pele ho Impala

IMPALA Tlhaloso: Lipakane, User View of Impala: Tlhaloso ea Basebelisi ba Impala: SQL, Sebopeho sa basebetsi ba Impala: Apache HBase, litsebi tsa Impala, lebenkele la moaho oa Impala, tšebeletso ea lik'hamphani ea Impala, Likarolo tsa ho etsa lipatlisiso, Ho bapisa Impala ho Hive

Hadoop Testing Application

Ke hobane'ng ha tlhahlobo e le ea bohlokoa, teko ea liteko, ho hlahlojoa ho kopanya, tlhahlobo ea ts'ebetso, ho hlahlojoa ha liteko, ho hlahlojoa ha bosiu ba QA, palo ea boipheliso le liteko tsa ho qetela, tlhahlobo ea ts'ebetso, tlhahlobo ea ho fana ka lits'ebeletso, tlhahlobo ea ts'ireletso, ho hlahlojoa ha lits'oaetso, ho koetlisa le ho nyatsa lits'ebeletso tsa lits'ebeletso. , Ho lokolla tlhahlobo

Mesebetsi le Boikarabello ba Hadoop Testing Professional

Ho utloisisa Tlhokahalo, Tlhahlobo ea Tlhahlobo, Tlhahlobo ea Litlhahlobo, Tlhahlobo ea Teko, Tlaleho e Phethahetseng, Tlhahlobo ea Sepheo sa Boipheliso, Tlhahlobo ea Tlaleho ea Letsatsi le Letsatsi, Ho phethoa ha teko, Tlhahlobo ea ETL moemong o mong le o mong (HDFS, HIVE, HBASE) ha Ho kenya lits'oants'o (li-files / lifaelese / litlaleho joalo-joalo) ho sebelisa sqoop / flume e akarelletsang empa e sa lekanyetsoe ho tiisetso ea data, ho boelanya, ho lumelloa ha basebetsi le ho hlahloba bopaki (Lihlopha, Basebetsi, Litokelo, joalo-joalo). ho koala, ho bokella litšitiso tsohle le ho etsa litlaleho tsa bokooa, ho netefatsa tšobotsi e ncha le litaba ho Core Hadoop.

Motheo o bitsoang MR Unit bakeng sa teko ea 'Mapa-Ho fokotsa mananeo

Tlaleha bokooa sehlopheng sa nts'etsopele kapa mookameli le ho ba khanna ho koala, ho matlafatsa litsi tsohle le ho etsa litlaleho tsa bokooa, ba ikarabellang bakeng sa ho theha moralo oa teko o bitsoang MR Unit bakeng sa ho hlahloba mananeo a ho fokotsa 'mapa.

Unit Testing

Tlhahlobo ea ho iketsetsa matla ka ho sebelisa OOZIE, Tlhaloso ea Dintlha ka ho sebelisa sesebelisoa sa ho hlahisa lipotso.

Tlhahlobo ea Teko

Leano la teko bakeng sa ntlafatso ea HDFS, Test automation le sephetho

Moralo oa Ts'ebetso Leano le Tlhahlobo ea Tlhahlobo ea ho hlahloba Hadoop Application

Tsela ea ho hlahloba ho kenya le ho e lokisa

Tšehetso ea Jobo le Bopaki

Litlhahiso le Tataiso ea Cloudera Certification le Thahasello ea Puisano Boitokisetso, Litlhahiso Tse Sebetsang le Litlhahiso

Re kopa o re ngolle info@itstechschool.com & re ikopanye le rona ka + 91-9870480053 bakeng sa theko ea theko le theko ea tiiso, kemiso le sebaka

Re Tlisetsa Potso

Koetliso ena e etselitsoe ho u thusa ho hlakola bobeli Cloudera Spark le Hadoop Motlatsi oa Motlakase (CCA175) tlhahlobo le Cloudera Certified Administrator bakeng sa Apache Hadoop (CCAH) tlhahlobo. Lintlha tsohle tsa koetliso ea koetliso li lumellana le mananeo ana a mabeli a likopo mme li u thusa ho hlakola litlhahlobo tsena ka boiketlo le ho fumana mesebetsi e ntle ka ho fetisisa MNC tse ka holimo.

E le karolo ea koetliso ena o tla sebetsa mesebetsing ea sebele ea nako le likabelo tse nang le ts'ebetso e khōlō mofuteng oa sebele oa lefapha la lefapha la lefats'e joalo ka hona ho u thusang ho potlakela mosebetsi oa hau ka thata.

Qetellong ea lenaneo lena la koetliso ho tla ba le mekhabiso eo ka ho phethahetseng e bontsang mofuta oa lipotso tse botsoang lipotsong tse fanoeng ka bopaki le ho u thusa hore u fumane matšoao a mangata ka ho hlahloba ho netefatsa.

Setifikeiti sa bona sa ho tlatsa thupelo e tla fuoa ho phethoa ha mosebetsi oa morero (ka tlhahlobo ea litsebi) le ha ho etsoa bonyane matšoao a 60% ho potso. Setifikeiti sa Intellipaat se tsebahala hantle ka holimo ho 80 + MNC e kang Ericsson, Cisco, Sognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, joalo-joalo.

Bakeng sa lintlha tse ling ka mosa Iteanye le rona.


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