SlideShare a Scribd company logo
1 of 21
HDFS RAID DhrubaBorthakur (dhruba@fb.com) Rodrigo Schmidt (rschmidt@fb.com) RamkumarVadali (rvadali@fb.com) Scott Chen (schen@fb.com) Patrick  Kling (pkling@fb.com)
Agenda What is RAID RAID at Facebook Anatomy of RAID How to Deploy Questions
What Is RAID ,[object Object],Default HDFS replication is 3 Too much at PetaByte scale RAID helps save space in HDFS Reduce replication of “source” data Data safety using “parity” data
Tolerates 2 missing blocks, Storage cost 3x  1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Tolerates 4 missing blocks, Storage cost 1.4x  1 2 3 4 5 6 7 8 9 10 Source file P1 P2 P3 P4 Parity file Reed-Solomon Erasure Codes
RAID at Facebook Reduces disk usage in the warehouse Currently saving about 5PB with XOR RAID Gradual deployment Started with few tables Now used with all tables Reed Solomon RAID under way
Saving 5PB at Facebook
Anatomy of RAID Server-side: RaidNode BlockFixer Block placement policy Client-side: DistributedRaidFileSystem Raid Shell
Anatomy of RAID DataNodes NameNode ,[object Object]
 Get files to raidRaidNode ,[object Object]
 Fix missing blocks
 Recover files while readingJobTracker Raid File System
RaidNode Daemon that scans filesystem Policy file used to provide file patterns Generate parity files Single thread Map-Reduce job Reduces replication of source file One thread to purge outdated parity files If the source gets deleted One thread to HAR parity files To reduce inode count
Block Fixer Reconstructs missing/corrupt blocks Retrieves a list of corrupt files from NameNode Source blocks are reconstructed by “decoding” Parity blocks are reconstructed by “encoding”
Block Fixer Bonus: Parity HARs One HAR block => multiple parity blocks Reconstructs all necessary blocks
Block Fixer Stats
Erasure Code ErasureCode abstraction for erasure code implementations    public void encode(int[] message, int[] parity);    public void decode(int[] data,  int[] erasedLocations, int[] erasedValues); Current implementations XOR Code Reed Solomon Code Encoder/Decoder – uses ErasureCode to integrate with RAID framework
Block Placement Replication = 3, Tolerates any 2 errors 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Dependent Blocks Replication = 1, Parity Length = 4, Tolerates any 4 errors 1 2 3 4 5 6 7 8 9 10 P1 P2 P3 P4 Dependent Blocks
Block Placement Raid introduces new dependency between blocks in source and parity files Default block placement is bad for RAID Source/Parity blocks can be on a single node/rack Parity blocks could co-locate with source blocks Raid Block Policy Source files: After RAIDing, disperse blocks Parity files: Control placement of parity blocks to avoid source blocks and other parity blocks
DistributedRaidFileSystem A filter file system implementation Allows clients to read “corrupt” source files Catches BlockMissingException, ChecksumException Recreates missing blocks on the fly by using parity Does not fix the missing blocks Only allows the reads to succeed
RaidShell Administrator tool Recover blocks Reconstruct missing blocks Send reconstructed block to a data node Raid FSCK  Report corrupt files that cannot be fixed by raid Handy tool as a last resort to fix blocks
Deployment Single configuration file “raid.xml” Specifies file patterns to RAID In HDFS config file Specify raid.xml location Specify location of parity files (default: /raid) Specify FileSystem, BlockPlacementPolicy Starting RaidNode start-raidnode.sh, stop-raidnode.sh http://wiki.apache.org/hadoop/HDFS-RAID

More Related Content

What's hot

Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...
Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...
Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...Spark Summit
 
Burst Presto & Spark workloads to AWS EMR with no data copies
Burst Presto & Spark workloads to AWS EMR with no data copiesBurst Presto & Spark workloads to AWS EMR with no data copies
Burst Presto & Spark workloads to AWS EMR with no data copiesAlluxio, Inc.
 
CaffeOnSpark Update: Recent Enhancements and Use Cases
CaffeOnSpark Update: Recent Enhancements and Use CasesCaffeOnSpark Update: Recent Enhancements and Use Cases
CaffeOnSpark Update: Recent Enhancements and Use CasesDataWorks Summit
 
Debunking the Myths of HDFS Erasure Coding Performance
Debunking the Myths of HDFS Erasure Coding Performance Debunking the Myths of HDFS Erasure Coding Performance
Debunking the Myths of HDFS Erasure Coding Performance DataWorks Summit/Hadoop Summit
 
Apache ignite as in-memory computing platform
Apache ignite as in-memory computing platformApache ignite as in-memory computing platform
Apache ignite as in-memory computing platformSurinder Mehra
 
Apache ignite Datagrid
Apache ignite DatagridApache ignite Datagrid
Apache ignite DatagridSurinder Mehra
 
Scalable and High available Distributed File System Metadata Service Using gR...
Scalable and High available Distributed File System Metadata Service Using gR...Scalable and High available Distributed File System Metadata Service Using gR...
Scalable and High available Distributed File System Metadata Service Using gR...Alluxio, Inc.
 
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...Spark Summit
 
Designing your SaaS Database for Scale with Postgres
Designing your SaaS Database for Scale with PostgresDesigning your SaaS Database for Scale with Postgres
Designing your SaaS Database for Scale with PostgresOzgun Erdogan
 
Beyond unit tests: Deployment and testing for Hadoop/Spark workflows
Beyond unit tests: Deployment and testing for Hadoop/Spark workflowsBeyond unit tests: Deployment and testing for Hadoop/Spark workflows
Beyond unit tests: Deployment and testing for Hadoop/Spark workflowsDataWorks Summit
 
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...Spark Summit
 
2011 06-30-hadoop-summit v5
2011 06-30-hadoop-summit v52011 06-30-hadoop-summit v5
2011 06-30-hadoop-summit v5Samuel Rash
 
HDFS Erasure Code Storage - Same Reliability at Better Storage Efficiency
HDFS Erasure Code Storage - Same Reliability at Better Storage EfficiencyHDFS Erasure Code Storage - Same Reliability at Better Storage Efficiency
HDFS Erasure Code Storage - Same Reliability at Better Storage EfficiencyDataWorks Summit
 
700 Updatable Queries Per Second: Spark as a Real-Time Web Service
700 Updatable Queries Per Second: Spark as a Real-Time Web Service700 Updatable Queries Per Second: Spark as a Real-Time Web Service
700 Updatable Queries Per Second: Spark as a Real-Time Web ServiceEvan Chan
 
Top 5 mistakes when writing Spark applications
Top 5 mistakes when writing Spark applicationsTop 5 mistakes when writing Spark applications
Top 5 mistakes when writing Spark applicationshadooparchbook
 
Hive, Presto, and Spark on TPC-DS benchmark
Hive, Presto, and Spark on TPC-DS benchmarkHive, Presto, and Spark on TPC-DS benchmark
Hive, Presto, and Spark on TPC-DS benchmarkDongwon Kim
 

What's hot (20)

Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...
Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...
Lessons Learned from Dockerizing Spark Workloads: Spark Summit East talk by T...
 
Burst Presto & Spark workloads to AWS EMR with no data copies
Burst Presto & Spark workloads to AWS EMR with no data copiesBurst Presto & Spark workloads to AWS EMR with no data copies
Burst Presto & Spark workloads to AWS EMR with no data copies
 
CaffeOnSpark Update: Recent Enhancements and Use Cases
CaffeOnSpark Update: Recent Enhancements and Use CasesCaffeOnSpark Update: Recent Enhancements and Use Cases
CaffeOnSpark Update: Recent Enhancements and Use Cases
 
Debunking the Myths of HDFS Erasure Coding Performance
Debunking the Myths of HDFS Erasure Coding Performance Debunking the Myths of HDFS Erasure Coding Performance
Debunking the Myths of HDFS Erasure Coding Performance
 
HDFS Issues
HDFS IssuesHDFS Issues
HDFS Issues
 
Apache ignite as in-memory computing platform
Apache ignite as in-memory computing platformApache ignite as in-memory computing platform
Apache ignite as in-memory computing platform
 
Apache ignite Datagrid
Apache ignite DatagridApache ignite Datagrid
Apache ignite Datagrid
 
HDFS Internals
HDFS InternalsHDFS Internals
HDFS Internals
 
Scalable and High available Distributed File System Metadata Service Using gR...
Scalable and High available Distributed File System Metadata Service Using gR...Scalable and High available Distributed File System Metadata Service Using gR...
Scalable and High available Distributed File System Metadata Service Using gR...
 
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...
Leverage Mesos for running Spark Streaming production jobs by Iulian Dragos a...
 
Mumak
MumakMumak
Mumak
 
Designing your SaaS Database for Scale with Postgres
Designing your SaaS Database for Scale with PostgresDesigning your SaaS Database for Scale with Postgres
Designing your SaaS Database for Scale with Postgres
 
Enterprise Grade Streaming under 2ms on Hadoop
Enterprise Grade Streaming under 2ms on HadoopEnterprise Grade Streaming under 2ms on Hadoop
Enterprise Grade Streaming under 2ms on Hadoop
 
Beyond unit tests: Deployment and testing for Hadoop/Spark workflows
Beyond unit tests: Deployment and testing for Hadoop/Spark workflowsBeyond unit tests: Deployment and testing for Hadoop/Spark workflows
Beyond unit tests: Deployment and testing for Hadoop/Spark workflows
 
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...
Spark and Object Stores —What You Need to Know: Spark Summit East talk by Ste...
 
2011 06-30-hadoop-summit v5
2011 06-30-hadoop-summit v52011 06-30-hadoop-summit v5
2011 06-30-hadoop-summit v5
 
HDFS Erasure Code Storage - Same Reliability at Better Storage Efficiency
HDFS Erasure Code Storage - Same Reliability at Better Storage EfficiencyHDFS Erasure Code Storage - Same Reliability at Better Storage Efficiency
HDFS Erasure Code Storage - Same Reliability at Better Storage Efficiency
 
700 Updatable Queries Per Second: Spark as a Real-Time Web Service
700 Updatable Queries Per Second: Spark as a Real-Time Web Service700 Updatable Queries Per Second: Spark as a Real-Time Web Service
700 Updatable Queries Per Second: Spark as a Real-Time Web Service
 
Top 5 mistakes when writing Spark applications
Top 5 mistakes when writing Spark applicationsTop 5 mistakes when writing Spark applications
Top 5 mistakes when writing Spark applications
 
Hive, Presto, and Spark on TPC-DS benchmark
Hive, Presto, and Spark on TPC-DS benchmarkHive, Presto, and Spark on TPC-DS benchmark
Hive, Presto, and Spark on TPC-DS benchmark
 

Similar to HUG Nov 2010: HDFS Raid - Facebook

Less is More: 2X Storage Efficiency with HDFS Erasure Coding
Less is More: 2X Storage Efficiency with HDFS Erasure CodingLess is More: 2X Storage Efficiency with HDFS Erasure Coding
Less is More: 2X Storage Efficiency with HDFS Erasure CodingZhe Zhang
 
Facebook's Approach to Big Data Storage Challenge
Facebook's Approach to Big Data Storage ChallengeFacebook's Approach to Big Data Storage Challenge
Facebook's Approach to Big Data Storage ChallengeDataWorks Summit
 
Container Storage Best Practices in 2017
Container Storage Best Practices in 2017Container Storage Best Practices in 2017
Container Storage Best Practices in 2017Keith Resar
 
Raid Levels Technology
Raid Levels TechnologyRaid Levels Technology
Raid Levels TechnologyIshwor Panta
 
Hadoop-professional-software-development-course-in-mumbai
Hadoop-professional-software-development-course-in-mumbaiHadoop-professional-software-development-course-in-mumbai
Hadoop-professional-software-development-course-in-mumbaiUnmesh Baile
 
Hadoop professional-software-development-course-in-mumbai
Hadoop professional-software-development-course-in-mumbaiHadoop professional-software-development-course-in-mumbai
Hadoop professional-software-development-course-in-mumbaiUnmesh Baile
 
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...Simplilearn
 
Hadoop training in hyderabad-kellytechnologies
Hadoop training in hyderabad-kellytechnologiesHadoop training in hyderabad-kellytechnologies
Hadoop training in hyderabad-kellytechnologiesKelly Technologies
 
Zettabyte File Storage System
Zettabyte File Storage SystemZettabyte File Storage System
Zettabyte File Storage SystemAmdocs
 
Zettabyte File Storage System
Zettabyte File Storage SystemZettabyte File Storage System
Zettabyte File Storage SystemAmdocs
 
Efficient Shared Data in Perl
Efficient Shared Data in PerlEfficient Shared Data in Perl
Efficient Shared Data in PerlPerrin Harkins
 

Similar to HUG Nov 2010: HDFS Raid - Facebook (20)

Hdfs architecture
Hdfs architectureHdfs architecture
Hdfs architecture
 
Less is More: 2X Storage Efficiency with HDFS Erasure Coding
Less is More: 2X Storage Efficiency with HDFS Erasure CodingLess is More: 2X Storage Efficiency with HDFS Erasure Coding
Less is More: 2X Storage Efficiency with HDFS Erasure Coding
 
Facebook's Approach to Big Data Storage Challenge
Facebook's Approach to Big Data Storage ChallengeFacebook's Approach to Big Data Storage Challenge
Facebook's Approach to Big Data Storage Challenge
 
Hadoop HDFS Concepts
Hadoop HDFS ConceptsHadoop HDFS Concepts
Hadoop HDFS Concepts
 
Container Storage Best Practices in 2017
Container Storage Best Practices in 2017Container Storage Best Practices in 2017
Container Storage Best Practices in 2017
 
Raid Levels Technology
Raid Levels TechnologyRaid Levels Technology
Raid Levels Technology
 
Hadoop-professional-software-development-course-in-mumbai
Hadoop-professional-software-development-course-in-mumbaiHadoop-professional-software-development-course-in-mumbai
Hadoop-professional-software-development-course-in-mumbai
 
Hadoop professional-software-development-course-in-mumbai
Hadoop professional-software-development-course-in-mumbaiHadoop professional-software-development-course-in-mumbai
Hadoop professional-software-development-course-in-mumbai
 
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...
Hadoop Interview Questions And Answers Part-1 | Big Data Interview Questions ...
 
Hadoop and HDFS
Hadoop and HDFSHadoop and HDFS
Hadoop and HDFS
 
HDFS.ppt
HDFS.pptHDFS.ppt
HDFS.ppt
 
Hadoop training in hyderabad-kellytechnologies
Hadoop training in hyderabad-kellytechnologiesHadoop training in hyderabad-kellytechnologies
Hadoop training in hyderabad-kellytechnologies
 
Hadoop HDFS Concepts
Hadoop HDFS ConceptsHadoop HDFS Concepts
Hadoop HDFS Concepts
 
HDFS.ppt
HDFS.pptHDFS.ppt
HDFS.ppt
 
Raid Level
Raid LevelRaid Level
Raid Level
 
Zettabyte File Storage System
Zettabyte File Storage SystemZettabyte File Storage System
Zettabyte File Storage System
 
Zettabyte File Storage System
Zettabyte File Storage SystemZettabyte File Storage System
Zettabyte File Storage System
 
Efficient Shared Data in Perl
Efficient Shared Data in PerlEfficient Shared Data in Perl
Efficient Shared Data in Perl
 
SEMINAR
SEMINARSEMINAR
SEMINAR
 
Hdfs
HdfsHdfs
Hdfs
 

More from Yahoo Developer Network

Developing Mobile Apps for Performance - Swapnil Patel, Verizon Media
Developing Mobile Apps for Performance - Swapnil Patel, Verizon MediaDeveloping Mobile Apps for Performance - Swapnil Patel, Verizon Media
Developing Mobile Apps for Performance - Swapnil Patel, Verizon MediaYahoo Developer Network
 
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...Yahoo Developer Network
 
Athenz & SPIFFE, Tatsuya Yano, Yahoo Japan
Athenz & SPIFFE, Tatsuya Yano, Yahoo JapanAthenz & SPIFFE, Tatsuya Yano, Yahoo Japan
Athenz & SPIFFE, Tatsuya Yano, Yahoo JapanYahoo Developer Network
 
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...Yahoo Developer Network
 
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, Oath
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, OathBig Data Serving with Vespa - Jon Bratseth, Distinguished Architect, Oath
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, OathYahoo Developer Network
 
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenu
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenuHow @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenu
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenuYahoo Developer Network
 
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, Ampool
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, AmpoolThe Future of Hadoop in an AI World, Milind Bhandarkar, CEO, Ampool
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, AmpoolYahoo Developer Network
 
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...Yahoo Developer Network
 
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...Yahoo Developer Network
 
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, Oath
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, OathHDFS Scalability and Security, Daryn Sharp, Senior Engineer, Oath
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, OathYahoo Developer Network
 
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...Yahoo Developer Network
 
Moving the Oath Grid to Docker, Eric Badger, Oath
Moving the Oath Grid to Docker, Eric Badger, OathMoving the Oath Grid to Docker, Eric Badger, Oath
Moving the Oath Grid to Docker, Eric Badger, OathYahoo Developer Network
 
Architecting Petabyte Scale AI Applications
Architecting Petabyte Scale AI ApplicationsArchitecting Petabyte Scale AI Applications
Architecting Petabyte Scale AI ApplicationsYahoo Developer Network
 
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...Yahoo Developer Network
 
Jun 2017 HUG: YARN Scheduling – A Step Beyond
Jun 2017 HUG: YARN Scheduling – A Step BeyondJun 2017 HUG: YARN Scheduling – A Step Beyond
Jun 2017 HUG: YARN Scheduling – A Step BeyondYahoo Developer Network
 
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies Yahoo Developer Network
 
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...Yahoo Developer Network
 
February 2017 HUG: Exactly-once end-to-end processing with Apache Apex
February 2017 HUG: Exactly-once end-to-end processing with Apache ApexFebruary 2017 HUG: Exactly-once end-to-end processing with Apache Apex
February 2017 HUG: Exactly-once end-to-end processing with Apache ApexYahoo Developer Network
 
February 2017 HUG: Data Sketches: A required toolkit for Big Data Analytics
February 2017 HUG: Data Sketches: A required toolkit for Big Data AnalyticsFebruary 2017 HUG: Data Sketches: A required toolkit for Big Data Analytics
February 2017 HUG: Data Sketches: A required toolkit for Big Data AnalyticsYahoo Developer Network
 

More from Yahoo Developer Network (20)

Developing Mobile Apps for Performance - Swapnil Patel, Verizon Media
Developing Mobile Apps for Performance - Swapnil Patel, Verizon MediaDeveloping Mobile Apps for Performance - Swapnil Patel, Verizon Media
Developing Mobile Apps for Performance - Swapnil Patel, Verizon Media
 
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...
Athenz - The Open-Source Solution to Provide Access Control in Dynamic Infras...
 
Athenz & SPIFFE, Tatsuya Yano, Yahoo Japan
Athenz & SPIFFE, Tatsuya Yano, Yahoo JapanAthenz & SPIFFE, Tatsuya Yano, Yahoo Japan
Athenz & SPIFFE, Tatsuya Yano, Yahoo Japan
 
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...
Athenz with Istio - Single Access Control Model in Cloud Infrastructures, Tat...
 
CICD at Oath using Screwdriver
CICD at Oath using ScrewdriverCICD at Oath using Screwdriver
CICD at Oath using Screwdriver
 
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, Oath
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, OathBig Data Serving with Vespa - Jon Bratseth, Distinguished Architect, Oath
Big Data Serving with Vespa - Jon Bratseth, Distinguished Architect, Oath
 
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenu
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenuHow @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenu
How @TwitterHadoop Chose Google Cloud, Joep Rottinghuis, Lohit VijayaRenu
 
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, Ampool
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, AmpoolThe Future of Hadoop in an AI World, Milind Bhandarkar, CEO, Ampool
The Future of Hadoop in an AI World, Milind Bhandarkar, CEO, Ampool
 
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...
Apache YARN Federation and Tez at Microsoft, Anupam Upadhyay, Adrian Nicoara,...
 
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...
Containerized Services on Apache Hadoop YARN: Past, Present, and Future, Shan...
 
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, Oath
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, OathHDFS Scalability and Security, Daryn Sharp, Senior Engineer, Oath
HDFS Scalability and Security, Daryn Sharp, Senior Engineer, Oath
 
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...
Hadoop {Submarine} Project: Running deep learning workloads on YARN, Wangda T...
 
Moving the Oath Grid to Docker, Eric Badger, Oath
Moving the Oath Grid to Docker, Eric Badger, OathMoving the Oath Grid to Docker, Eric Badger, Oath
Moving the Oath Grid to Docker, Eric Badger, Oath
 
Architecting Petabyte Scale AI Applications
Architecting Petabyte Scale AI ApplicationsArchitecting Petabyte Scale AI Applications
Architecting Petabyte Scale AI Applications
 
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...
Introduction to Vespa – The Open Source Big Data Serving Engine, Jon Bratseth...
 
Jun 2017 HUG: YARN Scheduling – A Step Beyond
Jun 2017 HUG: YARN Scheduling – A Step BeyondJun 2017 HUG: YARN Scheduling – A Step Beyond
Jun 2017 HUG: YARN Scheduling – A Step Beyond
 
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies
Jun 2017 HUG: Large-Scale Machine Learning: Use Cases and Technologies
 
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...
February 2017 HUG: Slow, Stuck, or Runaway Apps? Learn How to Quickly Fix Pro...
 
February 2017 HUG: Exactly-once end-to-end processing with Apache Apex
February 2017 HUG: Exactly-once end-to-end processing with Apache ApexFebruary 2017 HUG: Exactly-once end-to-end processing with Apache Apex
February 2017 HUG: Exactly-once end-to-end processing with Apache Apex
 
February 2017 HUG: Data Sketches: A required toolkit for Big Data Analytics
February 2017 HUG: Data Sketches: A required toolkit for Big Data AnalyticsFebruary 2017 HUG: Data Sketches: A required toolkit for Big Data Analytics
February 2017 HUG: Data Sketches: A required toolkit for Big Data Analytics
 

Recently uploaded

Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsHyundai Motor Group
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetEnjoy Anytime
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxOnBoard
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAndikSusilo4
 
Next-generation AAM aircraft unveiled by Supernal, S-A2
Next-generation AAM aircraft unveiled by Supernal, S-A2Next-generation AAM aircraft unveiled by Supernal, S-A2
Next-generation AAM aircraft unveiled by Supernal, S-A2Hyundai Motor Group
 

Recently uploaded (20)

Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your BudgetHyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
Hyderabad Call Girls Khairatabad ✨ 7001305949 ✨ Cheap Price Your Budget
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
Maximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptxMaximizing Board Effectiveness 2024 Webinar.pptx
Maximizing Board Effectiveness 2024 Webinar.pptx
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & Application
 
Next-generation AAM aircraft unveiled by Supernal, S-A2
Next-generation AAM aircraft unveiled by Supernal, S-A2Next-generation AAM aircraft unveiled by Supernal, S-A2
Next-generation AAM aircraft unveiled by Supernal, S-A2
 

HUG Nov 2010: HDFS Raid - Facebook

  • 1. HDFS RAID DhrubaBorthakur (dhruba@fb.com) Rodrigo Schmidt (rschmidt@fb.com) RamkumarVadali (rvadali@fb.com) Scott Chen (schen@fb.com) Patrick Kling (pkling@fb.com)
  • 2. Agenda What is RAID RAID at Facebook Anatomy of RAID How to Deploy Questions
  • 3.
  • 4. Tolerates 2 missing blocks, Storage cost 3x 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Tolerates 4 missing blocks, Storage cost 1.4x 1 2 3 4 5 6 7 8 9 10 Source file P1 P2 P3 P4 Parity file Reed-Solomon Erasure Codes
  • 5. RAID at Facebook Reduces disk usage in the warehouse Currently saving about 5PB with XOR RAID Gradual deployment Started with few tables Now used with all tables Reed Solomon RAID under way
  • 6. Saving 5PB at Facebook
  • 7. Anatomy of RAID Server-side: RaidNode BlockFixer Block placement policy Client-side: DistributedRaidFileSystem Raid Shell
  • 8.
  • 9.
  • 10. Fix missing blocks
  • 11. Recover files while readingJobTracker Raid File System
  • 12. RaidNode Daemon that scans filesystem Policy file used to provide file patterns Generate parity files Single thread Map-Reduce job Reduces replication of source file One thread to purge outdated parity files If the source gets deleted One thread to HAR parity files To reduce inode count
  • 13. Block Fixer Reconstructs missing/corrupt blocks Retrieves a list of corrupt files from NameNode Source blocks are reconstructed by “decoding” Parity blocks are reconstructed by “encoding”
  • 14. Block Fixer Bonus: Parity HARs One HAR block => multiple parity blocks Reconstructs all necessary blocks
  • 16. Erasure Code ErasureCode abstraction for erasure code implementations public void encode(int[] message, int[] parity); public void decode(int[] data, int[] erasedLocations, int[] erasedValues); Current implementations XOR Code Reed Solomon Code Encoder/Decoder – uses ErasureCode to integrate with RAID framework
  • 17. Block Placement Replication = 3, Tolerates any 2 errors 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Dependent Blocks Replication = 1, Parity Length = 4, Tolerates any 4 errors 1 2 3 4 5 6 7 8 9 10 P1 P2 P3 P4 Dependent Blocks
  • 18. Block Placement Raid introduces new dependency between blocks in source and parity files Default block placement is bad for RAID Source/Parity blocks can be on a single node/rack Parity blocks could co-locate with source blocks Raid Block Policy Source files: After RAIDing, disperse blocks Parity files: Control placement of parity blocks to avoid source blocks and other parity blocks
  • 19. DistributedRaidFileSystem A filter file system implementation Allows clients to read “corrupt” source files Catches BlockMissingException, ChecksumException Recreates missing blocks on the fly by using parity Does not fix the missing blocks Only allows the reads to succeed
  • 20. RaidShell Administrator tool Recover blocks Reconstruct missing blocks Send reconstructed block to a data node Raid FSCK Report corrupt files that cannot be fixed by raid Handy tool as a last resort to fix blocks
  • 21. Deployment Single configuration file “raid.xml” Specifies file patterns to RAID In HDFS config file Specify raid.xml location Specify location of parity files (default: /raid) Specify FileSystem, BlockPlacementPolicy Starting RaidNode start-raidnode.sh, stop-raidnode.sh http://wiki.apache.org/hadoop/HDFS-RAID
  • 23. Limitations RAID needs file with 3 or more blocks Otherwise parity blocks negate space saving Need to HAR small source files Replication of 1 reduces locality for MR jobs Replication of 2 is not too bad Its very difficult to manage block placement of Parity HAR blocks