SlideShare ist ein Scribd-Unternehmen logo
1 von 23
Downloaden Sie, um offline zu lesen
HBase
by
Pooja Sunkapur
2SD09CS060
Contents
• Objective
• What is HBase?
• Why HBase?
• Features of HBase
• HBase architecture(overview)
• HBase architecture(Write-ahead-Log)
• HBase architecture(Hlog)
• HBase architecture(HFile)
• HBase Client
• Zookeeper
• Master
• HBase Region server
• HBase tables and regions
• HBase tables
• HBase Examples
• HBase users
• Conclusion
Objective
• To study and understand one of the growing
technologies of cloud computing and clone of
big table i.e “HBase”.
What is HBase?
• Open source project.
• Hbase ia a Hadoop data base.
• It is a distributed,large scale data store.
• Efficient at random reads/writes.
• Initially modeled after google’s big table.
Why HBase?
• Datasets are reaching petabytes.
• Need for random access and batch processing.
• Traditional databases are expensive to scale
and difficult to manage.
• Commodity hardware is cheap and powerful.
Features of HBase
• It supports unstructured and semistructured
data.
• It has built in version management.
• Fast key based lookups.
• It stores null values for free.
HBase Architecture
(overview)
HBase Architecture
(Write-ahead-Log flow)
HBase Architecture
(HLog)
HBase Architecture
(HFile and KeyValue)
HBase Client
• The HBase client is responsible for finding
RegionServers that are serving the particular row
range of interest.
• It does this by querying the .META. and -ROOT-
catalog tables in Zookeeper.
• After locating the required region(s), the client
directly contacts the RegionServer serving that
region
Zookeeper
• Zookeeper serves as a distributed co-ordinator
service.
• It bootstraps and co-ordinates clusters.
• Manages Master election and server availability
• The catalog tables -ROOT- and .META. are
maintained in Zookeeper.
• -ROOT- keeps track of where the .META. table is.
• The .META. table keeps a list of all regions in the
system with their corresponding region server
assignments .
Master
• The Master server is responsible for
monitoring all RegionServer instances in the
cluster, and is the interface for all metadata
changes.
• If the active Master shuts down then the
remaining Masters jostle to take over the
Master role in the Zookeeper.
HBase Region Server
HBase Region Server
• It is responsible for serving and managing
regions.
• It supports both data-oriented and region-
maintenance methods.
• data(get, put, delete, next, etc.)
• Region (splitRegion, compactRegion, etc.)
interfaces.
HBase Tables and Regions
• HBase table is made up of roughly equal sized
regions.
• Each region may live on a different node and
is made up of several HDFS files and blocks,
each of which is replicated by Hadoop.
• Region is specified by its startKey and endKey
HBase Tables
• Tables are sorted by Row in lexicographical order
• Table schema only defines its column families
i)Each family consists of any number of columns
ii)Each column consists of any number of versions
iii)Columns only exist when inserted, NULLs are free
iv)Columns within a family are sorted and
stored together
v)Everything except table names are byte[]
(Table, Row, Family:Column, Timestamp) -> Value
Example
Let us take an example of a user and his
friendship details.
In RDBMS:
Example
In HBase:
HBase users
•Facebook
•Twitter
•Yfrog
•Adobe
•Groups at yahoo
•Mozilla(Socorro)
•Trend Micro
•Stumble upon
Conclusion
• HBase is one of the most successful ,growing
technologies of cloud computing.
• It have opened the window for further research
in many field.
• whenever we need scalability then the
propeties and the flexibility of HBase can
relieve us from the headaches associated with
scaling an RDBMS.
References
• http://en.wikipedia.org/wiki/HBase
• http://www.slideshare.net/cloudera/chicago-data-summit-
apache-hbase-an-introduction
• http://cs.brown.edu/courses/cs227/archives/2011/slides/mar14-
hbase.pdf
• http://nosql.mypopescu.com/post/2862795125/advance
d-hbase
• http://www.slideshare.net/cloudera/5-final-ravi-
veeramchaneni-informatica-practical-hbase-hadoop-
world2011
HBase

Weitere ähnliche Inhalte

Was ist angesagt?

Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetup
Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics MeetupIntroduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetup
Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetupiwrigley
 
Deep Dive: Memory Management in Apache Spark
Deep Dive: Memory Management in Apache SparkDeep Dive: Memory Management in Apache Spark
Deep Dive: Memory Management in Apache SparkDatabricks
 
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...Simplilearn
 
Hadoop File system (HDFS)
Hadoop File system (HDFS)Hadoop File system (HDFS)
Hadoop File system (HDFS)Prashant Gupta
 
Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)Ryan Blue
 
HBaseCon 2012 | HBase Schema Design - Ian Varley, Salesforce
HBaseCon 2012 | HBase Schema Design - Ian Varley, SalesforceHBaseCon 2012 | HBase Schema Design - Ian Varley, Salesforce
HBaseCon 2012 | HBase Schema Design - Ian Varley, SalesforceCloudera, Inc.
 
Introduction To HBase
Introduction To HBaseIntroduction To HBase
Introduction To HBaseAnil Gupta
 
Big data architectures and the data lake
Big data architectures and the data lakeBig data architectures and the data lake
Big data architectures and the data lakeJames Serra
 
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 Million
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 MillionHow One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 Million
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 MillionDataWorks Summit
 
Dealing with Azure Cosmos DB
Dealing with Azure Cosmos DBDealing with Azure Cosmos DB
Dealing with Azure Cosmos DBMihail Mateev
 
HBase Schema Design - HBase-Con 2012
HBase Schema Design - HBase-Con 2012HBase Schema Design - HBase-Con 2012
HBase Schema Design - HBase-Con 2012Ian Varley
 
Relational databases vs Non-relational databases
Relational databases vs Non-relational databasesRelational databases vs Non-relational databases
Relational databases vs Non-relational databasesJames Serra
 
Introduction to Apache Hadoop Eco-System
Introduction to Apache Hadoop Eco-SystemIntroduction to Apache Hadoop Eco-System
Introduction to Apache Hadoop Eco-SystemMd. Hasan Basri (Angel)
 

Was ist angesagt? (20)

Gcp data engineer
Gcp data engineerGcp data engineer
Gcp data engineer
 
Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetup
Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics MeetupIntroduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetup
Introduction to Hadoop and Cloudera, Louisville BI & Big Data Analytics Meetup
 
Introduction to Amazon DynamoDB
Introduction to Amazon DynamoDBIntroduction to Amazon DynamoDB
Introduction to Amazon DynamoDB
 
Deep Dive: Memory Management in Apache Spark
Deep Dive: Memory Management in Apache SparkDeep Dive: Memory Management in Apache Spark
Deep Dive: Memory Management in Apache Spark
 
Map Reduce
Map ReduceMap Reduce
Map Reduce
 
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
 
Hadoop File system (HDFS)
Hadoop File system (HDFS)Hadoop File system (HDFS)
Hadoop File system (HDFS)
 
Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)Iceberg: A modern table format for big data (Strata NY 2018)
Iceberg: A modern table format for big data (Strata NY 2018)
 
HBaseCon 2012 | HBase Schema Design - Ian Varley, Salesforce
HBaseCon 2012 | HBase Schema Design - Ian Varley, SalesforceHBaseCon 2012 | HBase Schema Design - Ian Varley, Salesforce
HBaseCon 2012 | HBase Schema Design - Ian Varley, Salesforce
 
Introduction To HBase
Introduction To HBaseIntroduction To HBase
Introduction To HBase
 
Big data architectures and the data lake
Big data architectures and the data lakeBig data architectures and the data lake
Big data architectures and the data lake
 
Apache hadoop hbase
Apache hadoop hbaseApache hadoop hbase
Apache hadoop hbase
 
The delta architecture
The delta architectureThe delta architecture
The delta architecture
 
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 Million
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 MillionHow One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 Million
How One Company Offloaded Data Warehouse ETL To Hadoop and Saved $30 Million
 
Amazon Aurora
Amazon AuroraAmazon Aurora
Amazon Aurora
 
Dealing with Azure Cosmos DB
Dealing with Azure Cosmos DBDealing with Azure Cosmos DB
Dealing with Azure Cosmos DB
 
Lakehouse in Azure
Lakehouse in AzureLakehouse in Azure
Lakehouse in Azure
 
HBase Schema Design - HBase-Con 2012
HBase Schema Design - HBase-Con 2012HBase Schema Design - HBase-Con 2012
HBase Schema Design - HBase-Con 2012
 
Relational databases vs Non-relational databases
Relational databases vs Non-relational databasesRelational databases vs Non-relational databases
Relational databases vs Non-relational databases
 
Introduction to Apache Hadoop Eco-System
Introduction to Apache Hadoop Eco-SystemIntroduction to Apache Hadoop Eco-System
Introduction to Apache Hadoop Eco-System
 

Ähnlich wie HBase

Intro to HBase - Lars George
Intro to HBase - Lars GeorgeIntro to HBase - Lars George
Intro to HBase - Lars GeorgeJAX London
 
Nyc hadoop meetup introduction to h base
Nyc hadoop meetup   introduction to h baseNyc hadoop meetup   introduction to h base
Nyc hadoop meetup introduction to h base智杰 付
 
CCS334 BIG DATA ANALYTICS UNIT 5 PPT ELECTIVE PAPER
CCS334 BIG DATA ANALYTICS UNIT 5 PPT  ELECTIVE PAPERCCS334 BIG DATA ANALYTICS UNIT 5 PPT  ELECTIVE PAPER
CCS334 BIG DATA ANALYTICS UNIT 5 PPT ELECTIVE PAPERKrishnaVeni451953
 
Introduction to Apache HBase
Introduction to Apache HBaseIntroduction to Apache HBase
Introduction to Apache HBaseGokuldas Pillai
 
Hbase Introduction
Hbase IntroductionHbase Introduction
Hbase IntroductionKim Yong-Duk
 
Hbasepreso 111116185419-phpapp02
Hbasepreso 111116185419-phpapp02Hbasepreso 111116185419-phpapp02
Hbasepreso 111116185419-phpapp02Gokuldas Pillai
 
HBase.pptx
HBase.pptxHBase.pptx
HBase.pptxSadhik7
 
HBase in Practice
HBase in PracticeHBase in Practice
HBase in Practicelarsgeorge
 
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsBig Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsEsther Kundin
 
Unit II Hadoop Ecosystem_Updated.pptx
Unit II Hadoop Ecosystem_Updated.pptxUnit II Hadoop Ecosystem_Updated.pptx
Unit II Hadoop Ecosystem_Updated.pptxBhavanaHotchandani
 
Techincal Talk Hbase-Ditributed,no-sql database
Techincal Talk Hbase-Ditributed,no-sql databaseTechincal Talk Hbase-Ditributed,no-sql database
Techincal Talk Hbase-Ditributed,no-sql databaseRishabh Dugar
 
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsBig Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsEsther Kundin
 
Facebook keynote-nicolas-qcon
Facebook keynote-nicolas-qconFacebook keynote-nicolas-qcon
Facebook keynote-nicolas-qconYiwei Ma
 
支撑Facebook消息处理的h base存储系统
支撑Facebook消息处理的h base存储系统支撑Facebook消息处理的h base存储系统
支撑Facebook消息处理的h base存储系统yongboy
 
Facebook Messages & HBase
Facebook Messages & HBaseFacebook Messages & HBase
Facebook Messages & HBase强 王
 

Ähnlich wie HBase (20)

Hbase
HbaseHbase
Hbase
 
Intro to HBase - Lars George
Intro to HBase - Lars GeorgeIntro to HBase - Lars George
Intro to HBase - Lars George
 
Nyc hadoop meetup introduction to h base
Nyc hadoop meetup   introduction to h baseNyc hadoop meetup   introduction to h base
Nyc hadoop meetup introduction to h base
 
CCS334 BIG DATA ANALYTICS UNIT 5 PPT ELECTIVE PAPER
CCS334 BIG DATA ANALYTICS UNIT 5 PPT  ELECTIVE PAPERCCS334 BIG DATA ANALYTICS UNIT 5 PPT  ELECTIVE PAPER
CCS334 BIG DATA ANALYTICS UNIT 5 PPT ELECTIVE PAPER
 
Introduction to Apache HBase
Introduction to Apache HBaseIntroduction to Apache HBase
Introduction to Apache HBase
 
4. hbase overview
4. hbase overview4. hbase overview
4. hbase overview
 
Hadoop - Apache Hbase
Hadoop - Apache HbaseHadoop - Apache Hbase
Hadoop - Apache Hbase
 
Hbase
HbaseHbase
Hbase
 
Hbase Introduction
Hbase IntroductionHbase Introduction
Hbase Introduction
 
Hbasepreso 111116185419-phpapp02
Hbasepreso 111116185419-phpapp02Hbasepreso 111116185419-phpapp02
Hbasepreso 111116185419-phpapp02
 
HBase.pptx
HBase.pptxHBase.pptx
HBase.pptx
 
HBase in Practice
HBase in Practice HBase in Practice
HBase in Practice
 
HBase in Practice
HBase in PracticeHBase in Practice
HBase in Practice
 
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsBig Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
 
Unit II Hadoop Ecosystem_Updated.pptx
Unit II Hadoop Ecosystem_Updated.pptxUnit II Hadoop Ecosystem_Updated.pptx
Unit II Hadoop Ecosystem_Updated.pptx
 
Techincal Talk Hbase-Ditributed,no-sql database
Techincal Talk Hbase-Ditributed,no-sql databaseTechincal Talk Hbase-Ditributed,no-sql database
Techincal Talk Hbase-Ditributed,no-sql database
 
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsBig Data and Hadoop - History, Technical Deep Dive, and Industry Trends
Big Data and Hadoop - History, Technical Deep Dive, and Industry Trends
 
Facebook keynote-nicolas-qcon
Facebook keynote-nicolas-qconFacebook keynote-nicolas-qcon
Facebook keynote-nicolas-qcon
 
支撑Facebook消息处理的h base存储系统
支撑Facebook消息处理的h base存储系统支撑Facebook消息处理的h base存储系统
支撑Facebook消息处理的h base存储系统
 
Facebook Messages & HBase
Facebook Messages & HBaseFacebook Messages & HBase
Facebook Messages & HBase
 

Kürzlich hochgeladen

Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Seán Kennedy
 
Activity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationActivity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationRosabel UA
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptxmary850239
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfPatidar M
 
Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)cama23
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfTechSoup
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Mark Reed
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptxmary850239
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptxmary850239
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONHumphrey A Beña
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfJemuel Francisco
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...Nguyen Thanh Tu Collection
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...Postal Advocate Inc.
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfVanessa Camilleri
 
Food processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsFood processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsManeerUddin
 
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxBarangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxCarlos105
 

Kürzlich hochgeladen (20)

Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...Student Profile Sample - We help schools to connect the data they have, with ...
Student Profile Sample - We help schools to connect the data they have, with ...
 
Activity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translationActivity 2-unit 2-update 2024. English translation
Activity 2-unit 2-update 2024. English translation
 
4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx4.16.24 21st Century Movements for Black Lives.pptx
4.16.24 21st Century Movements for Black Lives.pptx
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdf
 
Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)Global Lehigh Strategic Initiatives (without descriptions)
Global Lehigh Strategic Initiatives (without descriptions)
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx
 
Raw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptxRaw materials used in Herbal Cosmetics.pptx
Raw materials used in Herbal Cosmetics.pptx
 
4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx4.16.24 Poverty and Precarity--Desmond.pptx
4.16.24 Poverty and Precarity--Desmond.pptx
 
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATIONTHEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
THEORIES OF ORGANIZATION-PUBLIC ADMINISTRATION
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
 
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
HỌC TỐT TIẾNG ANH 11 THEO CHƯƠNG TRÌNH GLOBAL SUCCESS ĐÁP ÁN CHI TIẾT - CẢ NĂ...
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptxLEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
 
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptxFINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdf
 
Food processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture honsFood processing presentation for bsc agriculture hons
Food processing presentation for bsc agriculture hons
 
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptxBarangay Council for the Protection of Children (BCPC) Orientation.pptx
Barangay Council for the Protection of Children (BCPC) Orientation.pptx
 

HBase

  • 2. Contents • Objective • What is HBase? • Why HBase? • Features of HBase • HBase architecture(overview) • HBase architecture(Write-ahead-Log) • HBase architecture(Hlog) • HBase architecture(HFile) • HBase Client • Zookeeper • Master • HBase Region server • HBase tables and regions • HBase tables • HBase Examples • HBase users • Conclusion
  • 3. Objective • To study and understand one of the growing technologies of cloud computing and clone of big table i.e “HBase”.
  • 4. What is HBase? • Open source project. • Hbase ia a Hadoop data base. • It is a distributed,large scale data store. • Efficient at random reads/writes. • Initially modeled after google’s big table.
  • 5. Why HBase? • Datasets are reaching petabytes. • Need for random access and batch processing. • Traditional databases are expensive to scale and difficult to manage. • Commodity hardware is cheap and powerful.
  • 6. Features of HBase • It supports unstructured and semistructured data. • It has built in version management. • Fast key based lookups. • It stores null values for free.
  • 11. HBase Client • The HBase client is responsible for finding RegionServers that are serving the particular row range of interest. • It does this by querying the .META. and -ROOT- catalog tables in Zookeeper. • After locating the required region(s), the client directly contacts the RegionServer serving that region
  • 12. Zookeeper • Zookeeper serves as a distributed co-ordinator service. • It bootstraps and co-ordinates clusters. • Manages Master election and server availability • The catalog tables -ROOT- and .META. are maintained in Zookeeper. • -ROOT- keeps track of where the .META. table is. • The .META. table keeps a list of all regions in the system with their corresponding region server assignments .
  • 13. Master • The Master server is responsible for monitoring all RegionServer instances in the cluster, and is the interface for all metadata changes. • If the active Master shuts down then the remaining Masters jostle to take over the Master role in the Zookeeper.
  • 15. HBase Region Server • It is responsible for serving and managing regions. • It supports both data-oriented and region- maintenance methods. • data(get, put, delete, next, etc.) • Region (splitRegion, compactRegion, etc.) interfaces.
  • 16. HBase Tables and Regions • HBase table is made up of roughly equal sized regions. • Each region may live on a different node and is made up of several HDFS files and blocks, each of which is replicated by Hadoop. • Region is specified by its startKey and endKey
  • 17. HBase Tables • Tables are sorted by Row in lexicographical order • Table schema only defines its column families i)Each family consists of any number of columns ii)Each column consists of any number of versions iii)Columns only exist when inserted, NULLs are free iv)Columns within a family are sorted and stored together v)Everything except table names are byte[] (Table, Row, Family:Column, Timestamp) -> Value
  • 18. Example Let us take an example of a user and his friendship details. In RDBMS:
  • 20. HBase users •Facebook •Twitter •Yfrog •Adobe •Groups at yahoo •Mozilla(Socorro) •Trend Micro •Stumble upon
  • 21. Conclusion • HBase is one of the most successful ,growing technologies of cloud computing. • It have opened the window for further research in many field. • whenever we need scalability then the propeties and the flexibility of HBase can relieve us from the headaches associated with scaling an RDBMS.
  • 22. References • http://en.wikipedia.org/wiki/HBase • http://www.slideshare.net/cloudera/chicago-data-summit- apache-hbase-an-introduction • http://cs.brown.edu/courses/cs227/archives/2011/slides/mar14- hbase.pdf • http://nosql.mypopescu.com/post/2862795125/advance d-hbase • http://www.slideshare.net/cloudera/5-final-ravi- veeramchaneni-informatica-practical-hbase-hadoop- world2011