SlideShare a Scribd company logo
1 of 31
© Hortonworks Inc. 2015
Hadoop YARN Services
Xuan Gong
xgong@hortonworks.com
Steve Loughran
stevel@hortonworks.com
Apache Hadoop + YARN:
An OS for data
An OS can do more than SQL
statements
An OS can do more than run
admin-installed apps
An OS lets you
run whatever you want!
© Hortonworks Inc. 2015
log
…which is important
front end
web
phones
devices
feeds log
stream
processing
front end
front end
log
database
analytics
© Hortonworks Inc. 2015
YARN Services:
Long lived applications
within a Hadoop cluster
Apache Slider (incubating)
(hosting: HBase, Accumulo, Storm…)
Samza
Hive LLAP Daemons
Kafka on YARN
Apache Flink
© Hortonworks Inc. 2015
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
“The RM”
HDFS
YARN Node Manager
• Servers run YARN Node Managers (NM)
• NM's heartbeat to Resource Manager (RM)
• RM schedules work over cluster
• RM allocates containers to apps
• NMs start containers
• NMs report container health
Background: YARN
© Hortonworks Inc. 2015
Client creates App Master
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
“The RM”
HDFS
YARN Node Manager
Client
Application Master
© Hortonworks Inc. 2015
“AM” requests containers
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
HDFS
YARN Node Manager
Application Master
Container
Container
Container
© Hortonworks Inc.
Short lived apps have it easy
• failure: clean restart
• logs: collect at end
• placement: by data
• security: Kerberos delegation tokens
• discovery: launcher app can track
© Hortonworks Inc.
Long-lived services don't
• failure: stay up
• logs: ongoing collection
• placement: availability, performance
• security: stay secure over time
• discovery: locatable by any client
© Hortonworks Inc. 2015
YARN-896
Support for YARN services
Log aggregation
Service registration & discovery
Windowed failure tracking
Anti-affinity placement
Gang scheduling
Applications to continue over AM restart
Container resource flexing
Container reuse
Kerberos token renewal
Container signalling
Net & Disk resources
Labelled nodes & queues
YARN-896
REST
Log aggregation
Service registration & discovery
Windowed failure tracking
Anti-affinity placement
Gang scheduling
Applications to continue over AM restart
Container resource flexing
Container reuse
Kerberos token renewal
Container signalling
Net & Disk resources
Labelled nodes & queues
Hadoop 2.6
(Docker)
REST
© Hortonworks Inc. 2015
Failures
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
HDFS
YARN Node Manager
Application Master
Container
Container
Container
© Hortonworks Inc. 2015
Failures
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
Application Master
Container
Container
container 1
container 2
lost: container 3
Failures
© Hortonworks Inc
Easy: enabling
// Client
amLauncher.setKeepContainersOverRestarts(true);
amLauncher.setMaxAppAttempts(8);
// Server
List<Container> liveContainers =
amRegistrationData.getContainersFromPreviousAttempts();
© Hortonworks Inc. 2015
Harder: rebuilding state
Node Map
Placement History
Specification
Container QueuesComponent Map
Event History
Persisted Rebuilt Transient
© Hortonworks Inc. 2015
<property>
<name>yarn.log-aggregation-enable</name>
<value>true</value>
</property>
Log Aggregation
Labels
ToR Switch
Switch
general
general
HBase
HBase
ToR Switch
general
general
HBase
HBase
ToR Switch
general
general
general,
kafka
HBase
HBase
general,
kafka
general,
kafka
© Hortonworks Inc. 2015
$ yarn rmadmin
...
-addToClusterNodeLabels [label1,label2,label3]
-removeFromClusterNodeLabels [label1,label2,label3]
-replaceLabelsOnNode [node1:port,label1,label2]
-directlyAccessNodeLabelStore
Labels
© Hortonworks Inc
YARN-913: Service Registry
$ slider resolve –path ~/services/org-apache-slider/storm1
{ "type" : "JSONServiceRecord",
"external" : [ {
"api" : "http://",
"addressType" : "uri",
"protocolType" : "webui",
"addresses" : [ {
"uri" : "http://nn.ex.net:4813"
} ]
}, {
"api" : "classpath:org.apache.slider.publisher.configurations",
"addressType" : "uri",
"protocolType" : "REST",
"addresses" : [ {
"uri" : "http://nn.ex.net:4813/ws/v1/slider/publisher/slider"
}]
} } ] }
© Hortonworks Inc. 2015
Internal and external endpoints
"internal" : [ {
"api" : "classpath:org.apache.slider.agents.secure",
"addressType" : "uri",
"protocolType" : "REST",
"addresses" : [ {
"uri" : "https://nn.ex.net:4813/ws/v1/slider/agents"
} ]
} ]
Internal: for an application's own use.
External: for clients, Web UIs and other apps
© Hortonworks Inc.
Security
• Token expiry a core Kerberos feature
• Token expiry inimical to service longevity
• Specifically: token delegation
• After 72h (default)
YARN updates the RM/AM tokens but not HDFS, ZK, ….
© Hortonworks Inc.
How do apps cope?
Do nothing  apps can run up to 72h
–All
Keytabs  apps can run forever; keytabs need to be
managed (securely)
–Slider
Client push  running/scheduled client updates AM;
AM forwards to containers
–Twill
AM keytab  containers ask for new tokens
–Spark via SPARK-5342
© Hortonworks Inc.
…so you can now:
write long lived apps
…with failure resilience
…and centralised log viewing
…and labelled/isolated placement
…in secure clusters
Log aggregation
Service registration & discovery
Windowed failure tracking
Anti-affinity placement
Gang scheduling
Applications to continue over AM restart
Container resource flexing
Container reuse
Kerberos token renewal
Container signalling
Net & Disk resources
Labelled nodes & queues
TODO
RESTREST
© Hortonworks Inc 2015
Questions?
For some code, see
http://slider.incubator.apache.org/
http://hadoop.apache.org

More Related Content

What's hot

Cloudy with a chance of Hadoop - DataWorks Summit 2017 San Jose
Cloudy with a chance of Hadoop - DataWorks Summit 2017 San JoseCloudy with a chance of Hadoop - DataWorks Summit 2017 San Jose
Cloudy with a chance of Hadoop - DataWorks Summit 2017 San JoseMingliang Liu
 
Get most out of Spark on YARN
Get most out of Spark on YARNGet most out of Spark on YARN
Get most out of Spark on YARNDataWorks Summit
 
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsTuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsDataWorks Summit
 
Apache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesApache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesDataWorks Summit
 
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared ClustersMercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared ClustersDataWorks Summit
 
Ozone- Object store for Apache Hadoop
Ozone- Object store for Apache HadoopOzone- Object store for Apache Hadoop
Ozone- Object store for Apache HadoopHortonworks
 
New Data Transfer Tools for Hadoop: Sqoop 2
New Data Transfer Tools for Hadoop: Sqoop 2New Data Transfer Tools for Hadoop: Sqoop 2
New Data Transfer Tools for Hadoop: Sqoop 2DataWorks Summit
 
Apache Ambari: Past, Present, Future
Apache Ambari: Past, Present, FutureApache Ambari: Past, Present, Future
Apache Ambari: Past, Present, FutureHortonworks
 
Apache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and FutureApache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and FutureDataWorks Summit
 
Operating and Supporting Apache HBase Best Practices and Improvements
Operating and Supporting Apache HBase Best Practices and ImprovementsOperating and Supporting Apache HBase Best Practices and Improvements
Operating and Supporting Apache HBase Best Practices and ImprovementsDataWorks Summit/Hadoop Summit
 
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2Cloudera, Inc.
 
Strata Stinger Talk October 2013
Strata Stinger Talk October 2013Strata Stinger Talk October 2013
Strata Stinger Talk October 2013alanfgates
 
Running Non-MapReduce Big Data Applications on Apache Hadoop
Running Non-MapReduce Big Data Applications on Apache HadoopRunning Non-MapReduce Big Data Applications on Apache Hadoop
Running Non-MapReduce Big Data Applications on Apache Hadoophitesh1892
 
Hadoop & cloud storage object store integration in production (final)
Hadoop & cloud storage  object store integration in production (final)Hadoop & cloud storage  object store integration in production (final)
Hadoop & cloud storage object store integration in production (final)Chris Nauroth
 
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...Yahoo Developer Network
 

What's hot (20)

Cloudy with a chance of Hadoop - DataWorks Summit 2017 San Jose
Cloudy with a chance of Hadoop - DataWorks Summit 2017 San JoseCloudy with a chance of Hadoop - DataWorks Summit 2017 San Jose
Cloudy with a chance of Hadoop - DataWorks Summit 2017 San Jose
 
Streamline Hadoop DevOps with Apache Ambari
Streamline Hadoop DevOps with Apache AmbariStreamline Hadoop DevOps with Apache Ambari
Streamline Hadoop DevOps with Apache Ambari
 
Apache Hive on ACID
Apache Hive on ACIDApache Hive on ACID
Apache Hive on ACID
 
Get most out of Spark on YARN
Get most out of Spark on YARNGet most out of Spark on YARN
Get most out of Spark on YARN
 
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agentsTuning Apache Ambari performance for Big Data at scale with 3000 agents
Tuning Apache Ambari performance for Big Data at scale with 3000 agents
 
Apache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesApache Hadoop YARN: best practices
Apache Hadoop YARN: best practices
 
State of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache ZeppelinState of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache Zeppelin
 
YARN and the Docker container runtime
YARN and the Docker container runtimeYARN and the Docker container runtime
YARN and the Docker container runtime
 
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared ClustersMercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters
 
Ozone- Object store for Apache Hadoop
Ozone- Object store for Apache HadoopOzone- Object store for Apache Hadoop
Ozone- Object store for Apache Hadoop
 
New Data Transfer Tools for Hadoop: Sqoop 2
New Data Transfer Tools for Hadoop: Sqoop 2New Data Transfer Tools for Hadoop: Sqoop 2
New Data Transfer Tools for Hadoop: Sqoop 2
 
Apache HBase: State of the Union
Apache HBase: State of the UnionApache HBase: State of the Union
Apache HBase: State of the Union
 
Apache Ambari: Past, Present, Future
Apache Ambari: Past, Present, FutureApache Ambari: Past, Present, Future
Apache Ambari: Past, Present, Future
 
Apache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and FutureApache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and Future
 
Operating and Supporting Apache HBase Best Practices and Improvements
Operating and Supporting Apache HBase Best Practices and ImprovementsOperating and Supporting Apache HBase Best Practices and Improvements
Operating and Supporting Apache HBase Best Practices and Improvements
 
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2
Hadoop Summit 2012 | A New Generation of Data Transfer Tools for Hadoop: Sqoop 2
 
Strata Stinger Talk October 2013
Strata Stinger Talk October 2013Strata Stinger Talk October 2013
Strata Stinger Talk October 2013
 
Running Non-MapReduce Big Data Applications on Apache Hadoop
Running Non-MapReduce Big Data Applications on Apache HadoopRunning Non-MapReduce Big Data Applications on Apache Hadoop
Running Non-MapReduce Big Data Applications on Apache Hadoop
 
Hadoop & cloud storage object store integration in production (final)
Hadoop & cloud storage  object store integration in production (final)Hadoop & cloud storage  object store integration in production (final)
Hadoop & cloud storage object store integration in production (final)
 
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...
April 2016 HUG: The latest of Apache Hadoop YARN and running your docker apps...
 

Similar to Hadoop YARN Services

Overview of slider project
Overview of slider projectOverview of slider project
Overview of slider projectSteve Loughran
 
Combine SAS High-Performance Capabilities with Hadoop YARN
Combine SAS High-Performance Capabilities with Hadoop YARNCombine SAS High-Performance Capabilities with Hadoop YARN
Combine SAS High-Performance Capabilities with Hadoop YARNHortonworks
 
2013 11-19-hoya-status
2013 11-19-hoya-status2013 11-19-hoya-status
2013 11-19-hoya-statusSteve Loughran
 
How YARN Enables Multiple Data Processing Engines in Hadoop
How YARN Enables Multiple Data Processing Engines in HadoopHow YARN Enables Multiple Data Processing Engines in Hadoop
How YARN Enables Multiple Data Processing Engines in HadoopPOSSCON
 
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFS
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFSDiscover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFS
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFSHortonworks
 
Developing YARN Applications - Integrating natively to YARN July 24 2014
Developing YARN Applications - Integrating natively to YARN July 24 2014Developing YARN Applications - Integrating natively to YARN July 24 2014
Developing YARN Applications - Integrating natively to YARN July 24 2014Hortonworks
 
Discover HDP2.1: Apache Storm for Stream Data Processing in Hadoop
Discover HDP2.1: Apache Storm for Stream Data Processing in HadoopDiscover HDP2.1: Apache Storm for Stream Data Processing in Hadoop
Discover HDP2.1: Apache Storm for Stream Data Processing in HadoopHortonworks
 
Hadoop: today and tomorrow
Hadoop: today and tomorrowHadoop: today and tomorrow
Hadoop: today and tomorrowSteve Loughran
 
Taming the Elephant: Efficient and Effective Apache Hadoop Management
Taming the Elephant: Efficient and Effective Apache Hadoop ManagementTaming the Elephant: Efficient and Effective Apache Hadoop Management
Taming the Elephant: Efficient and Effective Apache Hadoop ManagementDataWorks Summit/Hadoop Summit
 
Accumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit
 
YARN Ready - Integrating to YARN using Slider Webinar
YARN Ready - Integrating to YARN using Slider WebinarYARN Ready - Integrating to YARN using Slider Webinar
YARN Ready - Integrating to YARN using Slider WebinarHortonworks
 
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...Big Data Spain
 
Big data spain keynote nov 2016
Big data spain keynote nov 2016Big data spain keynote nov 2016
Big data spain keynote nov 2016alanfgates
 
What's new in Hadoop Yarn- Dec 2014
What's new in Hadoop Yarn- Dec 2014What's new in Hadoop Yarn- Dec 2014
What's new in Hadoop Yarn- Dec 2014InMobi Technology
 
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUG
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUGReal-Time Processing in Hadoop for IoT Use Cases - Phoenix HUG
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUGskumpf
 
Apache Ambari BOF - OpenStack - Hadoop Summit 2013
Apache Ambari BOF - OpenStack - Hadoop Summit 2013Apache Ambari BOF - OpenStack - Hadoop Summit 2013
Apache Ambari BOF - OpenStack - Hadoop Summit 2013Hortonworks
 

Similar to Hadoop YARN Services (20)

Overview of slider project
Overview of slider projectOverview of slider project
Overview of slider project
 
Combine SAS High-Performance Capabilities with Hadoop YARN
Combine SAS High-Performance Capabilities with Hadoop YARNCombine SAS High-Performance Capabilities with Hadoop YARN
Combine SAS High-Performance Capabilities with Hadoop YARN
 
Hoya for Code Review
Hoya for Code ReviewHoya for Code Review
Hoya for Code Review
 
October 2014 HUG : Apache Slider
October 2014 HUG : Apache SliderOctober 2014 HUG : Apache Slider
October 2014 HUG : Apache Slider
 
2013 11-19-hoya-status
2013 11-19-hoya-status2013 11-19-hoya-status
2013 11-19-hoya-status
 
How YARN Enables Multiple Data Processing Engines in Hadoop
How YARN Enables Multiple Data Processing Engines in HadoopHow YARN Enables Multiple Data Processing Engines in Hadoop
How YARN Enables Multiple Data Processing Engines in Hadoop
 
Running Services on YARN
Running Services on YARNRunning Services on YARN
Running Services on YARN
 
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFS
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFSDiscover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFS
Discover HDP 2.1: Apache Hadoop 2.4.0, YARN & HDFS
 
Developing YARN Applications - Integrating natively to YARN July 24 2014
Developing YARN Applications - Integrating natively to YARN July 24 2014Developing YARN Applications - Integrating natively to YARN July 24 2014
Developing YARN Applications - Integrating natively to YARN July 24 2014
 
Discover HDP2.1: Apache Storm for Stream Data Processing in Hadoop
Discover HDP2.1: Apache Storm for Stream Data Processing in HadoopDiscover HDP2.1: Apache Storm for Stream Data Processing in Hadoop
Discover HDP2.1: Apache Storm for Stream Data Processing in Hadoop
 
Apache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and FutureApache Hadoop YARN: Past, Present and Future
Apache Hadoop YARN: Past, Present and Future
 
Hadoop: today and tomorrow
Hadoop: today and tomorrowHadoop: today and tomorrow
Hadoop: today and tomorrow
 
Taming the Elephant: Efficient and Effective Apache Hadoop Management
Taming the Elephant: Efficient and Effective Apache Hadoop ManagementTaming the Elephant: Efficient and Effective Apache Hadoop Management
Taming the Elephant: Efficient and Effective Apache Hadoop Management
 
Accumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARN
 
YARN Ready - Integrating to YARN using Slider Webinar
YARN Ready - Integrating to YARN using Slider WebinarYARN Ready - Integrating to YARN using Slider Webinar
YARN Ready - Integrating to YARN using Slider Webinar
 
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...
The Enterprise and Connected Data, Trends in the Apache Hadoop Ecosystem by A...
 
Big data spain keynote nov 2016
Big data spain keynote nov 2016Big data spain keynote nov 2016
Big data spain keynote nov 2016
 
What's new in Hadoop Yarn- Dec 2014
What's new in Hadoop Yarn- Dec 2014What's new in Hadoop Yarn- Dec 2014
What's new in Hadoop Yarn- Dec 2014
 
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUG
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUGReal-Time Processing in Hadoop for IoT Use Cases - Phoenix HUG
Real-Time Processing in Hadoop for IoT Use Cases - Phoenix HUG
 
Apache Ambari BOF - OpenStack - Hadoop Summit 2013
Apache Ambari BOF - OpenStack - Hadoop Summit 2013Apache Ambari BOF - OpenStack - Hadoop Summit 2013
Apache Ambari BOF - OpenStack - Hadoop Summit 2013
 

More from DataWorks Summit

Floating on a RAFT: HBase Durability with Apache Ratis
Floating on a RAFT: HBase Durability with Apache RatisFloating on a RAFT: HBase Durability with Apache Ratis
Floating on a RAFT: HBase Durability with Apache RatisDataWorks Summit
 
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFiTracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFiDataWorks Summit
 
HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...DataWorks Summit
 
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...DataWorks Summit
 
Managing the Dewey Decimal System
Managing the Dewey Decimal SystemManaging the Dewey Decimal System
Managing the Dewey Decimal SystemDataWorks Summit
 
Practical NoSQL: Accumulo's dirlist Example
Practical NoSQL: Accumulo's dirlist ExamplePractical NoSQL: Accumulo's dirlist Example
Practical NoSQL: Accumulo's dirlist ExampleDataWorks Summit
 
HBase Global Indexing to support large-scale data ingestion at Uber
HBase Global Indexing to support large-scale data ingestion at UberHBase Global Indexing to support large-scale data ingestion at Uber
HBase Global Indexing to support large-scale data ingestion at UberDataWorks Summit
 
Scaling Cloud-Scale Translytics Workloads with Omid and Phoenix
Scaling Cloud-Scale Translytics Workloads with Omid and PhoenixScaling Cloud-Scale Translytics Workloads with Omid and Phoenix
Scaling Cloud-Scale Translytics Workloads with Omid and PhoenixDataWorks Summit
 
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFi
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiBuilding the High Speed Cybersecurity Data Pipeline Using Apache NiFi
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiDataWorks Summit
 
Supporting Apache HBase : Troubleshooting and Supportability Improvements
Supporting Apache HBase : Troubleshooting and Supportability ImprovementsSupporting Apache HBase : Troubleshooting and Supportability Improvements
Supporting Apache HBase : Troubleshooting and Supportability ImprovementsDataWorks Summit
 
Security Framework for Multitenant Architecture
Security Framework for Multitenant ArchitectureSecurity Framework for Multitenant Architecture
Security Framework for Multitenant ArchitectureDataWorks Summit
 
Presto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EnginePresto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EngineDataWorks Summit
 
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...DataWorks Summit
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudDataWorks Summit
 
Event-Driven Messaging and Actions using Apache Flink and Apache NiFi
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiEvent-Driven Messaging and Actions using Apache Flink and Apache NiFi
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiDataWorks Summit
 
Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerSecuring Data in Hybrid on-premise and Cloud Environments using Apache Ranger
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerDataWorks Summit
 
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...DataWorks Summit
 
Computer Vision: Coming to a Store Near You
Computer Vision: Coming to a Store Near YouComputer Vision: Coming to a Store Near You
Computer Vision: Coming to a Store Near YouDataWorks Summit
 
Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
Big Data Genomics: Clustering Billions of DNA Sequences with Apache SparkBig Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
Big Data Genomics: Clustering Billions of DNA Sequences with Apache SparkDataWorks Summit
 

More from DataWorks Summit (20)

Data Science Crash Course
Data Science Crash CourseData Science Crash Course
Data Science Crash Course
 
Floating on a RAFT: HBase Durability with Apache Ratis
Floating on a RAFT: HBase Durability with Apache RatisFloating on a RAFT: HBase Durability with Apache Ratis
Floating on a RAFT: HBase Durability with Apache Ratis
 
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFiTracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
 
HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...HBase Tales From the Trenches - Short stories about most common HBase operati...
HBase Tales From the Trenches - Short stories about most common HBase operati...
 
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
 
Managing the Dewey Decimal System
Managing the Dewey Decimal SystemManaging the Dewey Decimal System
Managing the Dewey Decimal System
 
Practical NoSQL: Accumulo's dirlist Example
Practical NoSQL: Accumulo's dirlist ExamplePractical NoSQL: Accumulo's dirlist Example
Practical NoSQL: Accumulo's dirlist Example
 
HBase Global Indexing to support large-scale data ingestion at Uber
HBase Global Indexing to support large-scale data ingestion at UberHBase Global Indexing to support large-scale data ingestion at Uber
HBase Global Indexing to support large-scale data ingestion at Uber
 
Scaling Cloud-Scale Translytics Workloads with Omid and Phoenix
Scaling Cloud-Scale Translytics Workloads with Omid and PhoenixScaling Cloud-Scale Translytics Workloads with Omid and Phoenix
Scaling Cloud-Scale Translytics Workloads with Omid and Phoenix
 
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFi
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFiBuilding the High Speed Cybersecurity Data Pipeline Using Apache NiFi
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFi
 
Supporting Apache HBase : Troubleshooting and Supportability Improvements
Supporting Apache HBase : Troubleshooting and Supportability ImprovementsSupporting Apache HBase : Troubleshooting and Supportability Improvements
Supporting Apache HBase : Troubleshooting and Supportability Improvements
 
Security Framework for Multitenant Architecture
Security Framework for Multitenant ArchitectureSecurity Framework for Multitenant Architecture
Security Framework for Multitenant Architecture
 
Presto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything EnginePresto: Optimizing Performance of SQL-on-Anything Engine
Presto: Optimizing Performance of SQL-on-Anything Engine
 
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
 
Extending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google CloudExtending Twitter's Data Platform to Google Cloud
Extending Twitter's Data Platform to Google Cloud
 
Event-Driven Messaging and Actions using Apache Flink and Apache NiFi
Event-Driven Messaging and Actions using Apache Flink and Apache NiFiEvent-Driven Messaging and Actions using Apache Flink and Apache NiFi
Event-Driven Messaging and Actions using Apache Flink and Apache NiFi
 
Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger
Securing Data in Hybrid on-premise and Cloud Environments using Apache RangerSecuring Data in Hybrid on-premise and Cloud Environments using Apache Ranger
Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger
 
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
 
Computer Vision: Coming to a Store Near You
Computer Vision: Coming to a Store Near YouComputer Vision: Coming to a Store Near You
Computer Vision: Coming to a Store Near You
 
Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
Big Data Genomics: Clustering Billions of DNA Sequences with Apache SparkBig Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
 

Recently uploaded

The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxLoriGlavin3
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyAlfredo García Lavilla
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 

Recently uploaded (20)

The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptxDigital Identity is Under Attack: FIDO Paris Seminar.pptx
Digital Identity is Under Attack: FIDO Paris Seminar.pptx
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 

Hadoop YARN Services

  • 1. © Hortonworks Inc. 2015 Hadoop YARN Services Xuan Gong xgong@hortonworks.com Steve Loughran stevel@hortonworks.com
  • 2.
  • 3. Apache Hadoop + YARN: An OS for data
  • 4. An OS can do more than SQL statements
  • 5. An OS can do more than run admin-installed apps
  • 6. An OS lets you run whatever you want!
  • 7. © Hortonworks Inc. 2015 log …which is important front end web phones devices feeds log stream processing front end front end log database analytics
  • 8. © Hortonworks Inc. 2015 YARN Services: Long lived applications within a Hadoop cluster
  • 9. Apache Slider (incubating) (hosting: HBase, Accumulo, Storm…) Samza Hive LLAP Daemons Kafka on YARN Apache Flink
  • 10. © Hortonworks Inc. 2015 HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager “The RM” HDFS YARN Node Manager • Servers run YARN Node Managers (NM) • NM's heartbeat to Resource Manager (RM) • RM schedules work over cluster • RM allocates containers to apps • NMs start containers • NMs report container health Background: YARN
  • 11. © Hortonworks Inc. 2015 Client creates App Master HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager “The RM” HDFS YARN Node Manager Client Application Master
  • 12. © Hortonworks Inc. 2015 “AM” requests containers HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager HDFS YARN Node Manager Application Master Container Container Container
  • 13. © Hortonworks Inc. Short lived apps have it easy • failure: clean restart • logs: collect at end • placement: by data • security: Kerberos delegation tokens • discovery: launcher app can track
  • 14. © Hortonworks Inc. Long-lived services don't • failure: stay up • logs: ongoing collection • placement: availability, performance • security: stay secure over time • discovery: locatable by any client
  • 15. © Hortonworks Inc. 2015 YARN-896 Support for YARN services
  • 16. Log aggregation Service registration & discovery Windowed failure tracking Anti-affinity placement Gang scheduling Applications to continue over AM restart Container resource flexing Container reuse Kerberos token renewal Container signalling Net & Disk resources Labelled nodes & queues YARN-896 REST
  • 17. Log aggregation Service registration & discovery Windowed failure tracking Anti-affinity placement Gang scheduling Applications to continue over AM restart Container resource flexing Container reuse Kerberos token renewal Container signalling Net & Disk resources Labelled nodes & queues Hadoop 2.6 (Docker) REST
  • 18. © Hortonworks Inc. 2015 Failures HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager HDFS YARN Node Manager Application Master Container Container Container
  • 19. © Hortonworks Inc. 2015 Failures HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager Application Master Container Container container 1 container 2 lost: container 3 Failures
  • 20. © Hortonworks Inc Easy: enabling // Client amLauncher.setKeepContainersOverRestarts(true); amLauncher.setMaxAppAttempts(8); // Server List<Container> liveContainers = amRegistrationData.getContainersFromPreviousAttempts();
  • 21. © Hortonworks Inc. 2015 Harder: rebuilding state Node Map Placement History Specification Container QueuesComponent Map Event History Persisted Rebuilt Transient
  • 22. © Hortonworks Inc. 2015 <property> <name>yarn.log-aggregation-enable</name> <value>true</value> </property> Log Aggregation
  • 23. Labels ToR Switch Switch general general HBase HBase ToR Switch general general HBase HBase ToR Switch general general general, kafka HBase HBase general, kafka general, kafka
  • 24. © Hortonworks Inc. 2015 $ yarn rmadmin ... -addToClusterNodeLabels [label1,label2,label3] -removeFromClusterNodeLabels [label1,label2,label3] -replaceLabelsOnNode [node1:port,label1,label2] -directlyAccessNodeLabelStore Labels
  • 25. © Hortonworks Inc YARN-913: Service Registry $ slider resolve –path ~/services/org-apache-slider/storm1 { "type" : "JSONServiceRecord", "external" : [ { "api" : "http://", "addressType" : "uri", "protocolType" : "webui", "addresses" : [ { "uri" : "http://nn.ex.net:4813" } ] }, { "api" : "classpath:org.apache.slider.publisher.configurations", "addressType" : "uri", "protocolType" : "REST", "addresses" : [ { "uri" : "http://nn.ex.net:4813/ws/v1/slider/publisher/slider" }] } } ] }
  • 26. © Hortonworks Inc. 2015 Internal and external endpoints "internal" : [ { "api" : "classpath:org.apache.slider.agents.secure", "addressType" : "uri", "protocolType" : "REST", "addresses" : [ { "uri" : "https://nn.ex.net:4813/ws/v1/slider/agents" } ] } ] Internal: for an application's own use. External: for clients, Web UIs and other apps
  • 27. © Hortonworks Inc. Security • Token expiry a core Kerberos feature • Token expiry inimical to service longevity • Specifically: token delegation • After 72h (default) YARN updates the RM/AM tokens but not HDFS, ZK, ….
  • 28. © Hortonworks Inc. How do apps cope? Do nothing  apps can run up to 72h –All Keytabs  apps can run forever; keytabs need to be managed (securely) –Slider Client push  running/scheduled client updates AM; AM forwards to containers –Twill AM keytab  containers ask for new tokens –Spark via SPARK-5342
  • 29. © Hortonworks Inc. …so you can now: write long lived apps …with failure resilience …and centralised log viewing …and labelled/isolated placement …in secure clusters
  • 30. Log aggregation Service registration & discovery Windowed failure tracking Anti-affinity placement Gang scheduling Applications to continue over AM restart Container resource flexing Container reuse Kerberos token renewal Container signalling Net & Disk resources Labelled nodes & queues TODO RESTREST
  • 31. © Hortonworks Inc 2015 Questions? For some code, see http://slider.incubator.apache.org/ http://hadoop.apache.org