SlideShare une entreprise Scribd logo
1  sur  41
© Hortonworks Inc. 2014
YARN Ready – Apache Slider
Provisioning, Managing, and Monitoring YARN Applications
Sumit Mohanty
@smohanty (@hortonworks)
Steve Loughran
@steveloughran (@hortonworks)
Page 1
© Hortonworks Inc. 2014
Agenda
• Long running applications on YARN
• Introduction to Slider
• Writing a Slider Application
• Key Slider Features
• Conclusion
• Q/A
Page 2
© Hortonworks Inc. 2014
Applications on Yarn
Page 3
© Hortonworks Inc. 2014
YARN runs code across the cluster
Page 4
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
“The RM”
HDFS
YARN Node Manager
• Servers run YARN Node Managers
• NM's heartbeat to Resource Manager
• RM schedules work over cluster
• RM allocates containers to apps
• NMs start containers
• NMs report container health
© Hortonworks Inc. 2014
Client creates App Master
Page 5
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
“The RM”
HDFS
YARN Node Manager
Client
Application Master
© Hortonworks Inc. 2014
AM asks for containers
Page 6
HDFS
YARN Node Manager
HDFS
YARN Node Manager
HDFS
YARN Resource Manager
HDFS
YARN Node Manager
Application Master
Container
Container
Container
© Hortonworks Inc. 2014
YARN notifies AM of failures
Page 7
HDFS
YARN Node Manager
HDFS
YARN Node Manager
Container
HDFS
YARN Resource Manager
HDFS
YARN Node Manager
Application Master
Container
Container
© Hortonworks Inc. 2014
Long Running Applications
Page 8
© Hortonworks Inc. 2014
Management
Page 9
• Application instance must be managed
–(Install/Configure/Start)
–Restart
–Reconfigure/Rolling update
–Stop/Graceful stop
–Status
–Activate/deactivate/rebalance
• Upgrade
–Long running applications need to provide upgrade support,
preferably rolling upgrade
© Hortonworks Inc. 2014
Registration and Discovery
Page 10
• Application must declare itself
–URLs
–Host/port
–Config (client config)
• Application must be discoverable
–Registry
–Name-based lookups
–Regularly updated
• Client support
–Callback if “data” changes; thick clients
–Configurable gateway; thin clients
© Hortonworks Inc. 2014
Monitoring
Page 11
• Metrics
–Instantaneous metrics (jmx)
–Time-series metrics (ganglia)
–Configure Ganglia or other metrics stores
• Alerts
–Based of jmx/port scan/container status
–Configure Nagios or other alerting mechanism
© Hortonworks Inc. 2014
Logs and Events
Page 12
• Logs
–Continuous log gathering
–Single view for logs across all containers
• Lifecycle Events
–Integration with Application Timeline Server
© Hortonworks Inc. 2014
In addition to …
Page 13
• Security
–Configured for security
–Token renewal
• High Availability
–On a highly available cluster (NN, RM HA)
–Itself highly available (multi-master)
• Packaging
• Configurability
• …
© Hortonworks Inc. 2014
Apache Slider
Page 14
© Hortonworks Inc. 2014
Why?
• Many mature applications exist
• Full YARN-integration takes effort
• Running under YARN delivers access to all the data in
HDFS –and the CPU power alongside it
• As Hadoop stack evolves, more to integrate with
• Management tools –e.g. Ambari– exist to monitor
applications in-cluster
Page 15
© Hortonworks Inc. 2014
Slider is an in-incubation project with one goal:
Make it possible and easy to deploy and
manage existing applications on a YARN
cluster
Page 16
Status: Currently in Tech Preview
GA with the next HDP release, tentatively November
© Hortonworks Inc. 2014
Slider view of an Application
Page 17
• An application is a set of components
• A component is a daemon/launched exe
–configuration
–scripts, data files, etc.
• Component may have one or more instances
• Component instances are managed
–By extension, the app instance is
• Example
–HBase Application (3 components)
– HBase Master
– HBase RegionServer
– HBase REST service
© Hortonworks Inc. 2014
YARN Containers with Slider
Page 18
YARN Node Manager
Component (container)AppMaster (container)
YARN Node Manager
HDFS
Slider Agent
Application
Slider AppMaster
Slider Client
HDFS
HDFS
YARN Resource Manager
© Hortonworks Inc. 2014
Application by Slider
Page 19
Slider
App
Package
Slider
CLI
HDFS
YARN Resource Manager
“The RM”
HDFS
YARN Node Manager
Agent Component
HDFS
YARN Node Manager
Agent Component
Similar to any YARN application
1. CLI starts an instance of the AM
2. AM requests containers
3. Containers activate with an Agent
4. Agent gets application definition
5. Agent registers with AM
6. AM issues commands
7. Agent reports back, status,
configuration, etc.
8. AM publishes endpoints,
configurations
Application
Registry
App Master/Agent Provider
© Hortonworks Inc. 2014
Slider AppMaster/Agent/Client
Page 20
• AppMaster
–Common YARN interactions
–Common *-client interactions
–Publishing needs
• Agent
–Configure and start
–Re-configure and restart
–Heartbeats & failure detection
–Port allocations and publishing
–Custom commands if any (e.g. graceful-stop)
• Client
–App life cycle commands (flex, status, …)
© Hortonworks Inc. 2014
Memcached on YARN
Sample Slider App
Page 21
© Hortonworks Inc. 2014
Other Application Packages
Page 23
• Reference doc for Memcached Application
–http://slider.incubator.apache.org/docs/slider_specs/hello_world_sl
ider_app.html
• Slider github repo has other app
–Accumulo
–HBase
–Storm
–Memcached-windows
© Hortonworks Inc. 2014
Other Capabilities
Page 24
© Hortonworks Inc. 2014
App Packaging Capabilities
Page 25
• Dynamic port allocation and sharing
• Inter-component dependency
–Specify the start order of components
• Exports
–Construct arbitrary name value pairs
–E.g. URLs (org.apache.slider.monitor:
http://${HBASE_MASTER_HOST}:${site.hbase-
site.hbase.master.info.port}/master-status)
• Default HDFS and ZK isolation
© Hortonworks Inc. 2014
Application Registry
Page 26
• A common problem (not specific to Slider)
– https://issues.apache.org/jira/browse/YARN-913
• Currently,
– Apache Curator based
– Register URLs pointing to actual data
– AM doubles up as a webserver for published data
• Plan
– Registry should be stand-alone
– Slider is a consumer as well as publisher
– Slider focuses on declarative solution for Applications to publish data
– Allows integration of Applications independent of how they are hosted
© Hortonworks Inc. 2014
Plan: YARN Service Registry
# YARN-wide registry in Zookeeper
# Services listed by (user, service class, name)
/yarnRegistry/users/sumit/slider/cluster1
# Ephemeral liveness node
/yarnRegistry/users/sumit/slider/cluster1/live
# service entry lists bindings: URLs, IPC (host, port), ZK
# individual components have own (ephemeral) entries & endpoints
/yarnRegistry/users/sumit/slider/cluster1/components/appmaster
# ZK R/W API, REST read-only API
Page 27
© Hortonworks Inc. 2014
Security
Page 28
• Applications validated to work in Kerberos secured
cluster
–Secure cluster created and keytabs available to application
components
–Security parameters specified in application configuration
–User obtains TGT (kinit) prior to Slider application creation
–E.g. HBase 0.98.4
• Agent-AM SSL communication
–One-Way by default
–Two-Way can be enabled
• Work initiated on ticket renewal for long running
applications
–YARN, HDFS
© Hortonworks Inc. 2014
Failure Handling
Page 29
• Application Component Failure
–Component instance restarted
• AppMaster failure
–YARN restarts the AppMaster, Slider reconstructs states, registry
–App lifecycle commands are temporarily unavailable
• NodeManager failure
–App remains unaffected
• ResourceManager/NodeManager failures with HA
–App remains unaffected
© Hortonworks Inc. 2014
Windows and Linux Support
Page 30
• Feature set parity on both platforms
• Similar packaging constructs
–Typically, only path spec needs to change
• Both Linux and Windows Server as a platform for
–Client (host slider-client)
–Cluster (host hadoop cluster)
© Hortonworks Inc. 2014
Join in: Bring your favorite
Applications to YARN
Page 31
© Hortonworks Inc. 2014
Slider-ifying a new application
1. Grab slider:
http://slider.incubator.apache.org/downloads/
2. Look at App Package docs:
http://slider.incubator.apache.org/docs/slider_specs/
3. Look at source code examples under app-packages
4. Start with memcached/memcached-windows
Page 32
© Hortonworks Inc. 2014
YARN API vs. Slider
Page 33
• Native YARN app
–Your own AppMaster is in charge: container placement, fault handling
–You can implement an IPC API for callers to manipulate the
application
–AppMaster can send out event notifications
Ideal for large-scale distributed algorithms, with specific
placement and scheduling needs
• Slider App
–Slider AppMaster handles YARN integration with best-effort
placement history, fault handling (recreate component instance)
–Simple API/Web UI for cluster manipulation, endpoint listing
–Lots of failure and security testing
–You only need to write the App package (& test)
Long-lived applications where failures can addressed by
restarting elsewhere, with flexing decisions by admins
© Hortonworks Inc. 2014
Everyone is welcome
• Useful Links
–Website
– http://slider.incubator.apache.org/
–Dev Mailing Lists
– dev@slider.incubator.apache.org
–JIRA
– https://issues.apache.org/jira/browse/SLIDER
• Current and Upcoming Releases
– Slider 0.30 (May)
– Slider 0.40 (July)
– Slider 0.50 (planned)
Page 34
© Hortonworks Inc. 2014
Q/A
http://slider.incubator.apache.org/
Page 35
Next Steps
Next Steps
1. Review YARN Slider Resources
2. Review webinar recording
or attend the next webinar
3. Attend Office Hours
4. Sign up for a 2 day class
5. Attend the next YARN webinar
Resources
Setup HDP 2.1 environment
• Leverage Sandbox: Hortonworks.com/Sandbox
Get Started with YARN
• http://hortonworks.com/get-started/YARN
Technical Preview
• http://hortonworks.com/blog/apache-slider-technical-preview-now-
available/
Apache
• http://slider.incubator.apache.org/
Dev Mailing Lists
• dev@slider.incubator.apache.org
JIRA
• https://issues.apache.org/jira/browse/SLIDER
Hortonworks Office Hours
YARN Office Hours
Dial in and chat with YARN experts
Next Office Hour: Thursday August 14 @ 10-11am PDT. Register:
https://hortonworks.webex.com/hortonworks/onstage/g.php?t=a&d=628
190636
We plan Office Hours for September 11th and October 9th @ 10am
PT (2nd Thursdays)
Invitations will go out to those that attended or reviewed YARN
webinars
And from Hortonworks University
Hortonworks Course: Developing Custom YARN
Applications
Format: Online
Duration: 2 Days
When: September – date tbd
Cost: No Charge to Hortonworks Partners
Space: Very Limited
Interested? Please contact Lisa
Next in the Series!
Join us for the full series of YARN Ready webinars:
YARN Native July 24 @ 9am PT (recording link)
Tez August 21 @ 9am PT (registration link)
Additional webinar topics are being added – watch the
blog or visit Hortonworks.com/webinars:
September: Ambari and Scalding
October: Spark
http://hortonworks.com/webinars
© Hortonworks Inc. 2014
Thank you.
Page 42

Contenu connexe

Tendances

Pig Out to Hadoop
Pig Out to HadoopPig Out to Hadoop
Pig Out to HadoopHortonworks
 
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
 
Enabling Diverse Workload Scheduling in YARN
Enabling Diverse Workload Scheduling in YARNEnabling Diverse Workload Scheduling in YARN
Enabling Diverse Workload Scheduling in YARNDataWorks Summit
 
Deploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderDeploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderHortonworks
 
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
 
Hadoop crashcourse v3
Hadoop crashcourse v3Hadoop crashcourse v3
Hadoop crashcourse v3Hortonworks
 
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters Hortonworks
 
HDF: Hortonworks DataFlow: Technical Workshop
HDF: Hortonworks DataFlow: Technical WorkshopHDF: Hortonworks DataFlow: Technical Workshop
HDF: Hortonworks DataFlow: Technical WorkshopHortonworks
 
Hortonworks Technical Workshop: Apache Ambari
Hortonworks Technical Workshop:   Apache AmbariHortonworks Technical Workshop:   Apache Ambari
Hortonworks Technical Workshop: Apache AmbariHortonworks
 
LLAP: long-lived execution in Hive
LLAP: long-lived execution in HiveLLAP: long-lived execution in Hive
LLAP: long-lived execution in HiveDataWorks Summit
 
Securing Hadoop with Apache Ranger
Securing Hadoop with Apache RangerSecuring Hadoop with Apache Ranger
Securing Hadoop with Apache RangerDataWorks Summit
 
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele Hakka Labs
 
Log Analytics Optimization
Log Analytics OptimizationLog Analytics Optimization
Log Analytics OptimizationHortonworks
 
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
 
Hortonworks Technical Workshop: HDP everywhere - cloud considerations using...
Hortonworks Technical Workshop:   HDP everywhere - cloud considerations using...Hortonworks Technical Workshop:   HDP everywhere - cloud considerations using...
Hortonworks Technical Workshop: HDP everywhere - cloud considerations using...Hortonworks
 
Internet of things Crash Course Workshop
Internet of things Crash Course WorkshopInternet of things Crash Course Workshop
Internet of things Crash Course WorkshopDataWorks Summit
 
Hortonworks Technical Workshop: HBase For Mission Critical Applications
Hortonworks Technical Workshop: HBase For Mission Critical ApplicationsHortonworks Technical Workshop: HBase For Mission Critical Applications
Hortonworks Technical Workshop: HBase For Mission Critical ApplicationsHortonworks
 
Delivering Apache Hadoop for the Modern Data Architecture
Delivering Apache Hadoop for the Modern Data Architecture Delivering Apache Hadoop for the Modern Data Architecture
Delivering Apache Hadoop for the Modern Data Architecture Hortonworks
 
What s new in spark 2.3 and spark 2.4
What s new in spark 2.3 and spark 2.4What s new in spark 2.3 and spark 2.4
What s new in spark 2.3 and spark 2.4DataWorks Summit
 
Hortonworks Technical Workshop - Operational Best Practices Workshop
Hortonworks Technical Workshop - Operational Best Practices WorkshopHortonworks Technical Workshop - Operational Best Practices Workshop
Hortonworks Technical Workshop - Operational Best Practices WorkshopHortonworks
 

Tendances (20)

Pig Out to Hadoop
Pig Out to HadoopPig Out to Hadoop
Pig Out to Hadoop
 
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
 
Enabling Diverse Workload Scheduling in YARN
Enabling Diverse Workload Scheduling in YARNEnabling Diverse Workload Scheduling in YARN
Enabling Diverse Workload Scheduling in YARN
 
Deploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderDeploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via Slider
 
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 crashcourse v3
Hadoop crashcourse v3Hadoop crashcourse v3
Hadoop crashcourse v3
 
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters
Discover HDP 2.1: Using Apache Ambari to Manage Hadoop Clusters
 
HDF: Hortonworks DataFlow: Technical Workshop
HDF: Hortonworks DataFlow: Technical WorkshopHDF: Hortonworks DataFlow: Technical Workshop
HDF: Hortonworks DataFlow: Technical Workshop
 
Hortonworks Technical Workshop: Apache Ambari
Hortonworks Technical Workshop:   Apache AmbariHortonworks Technical Workshop:   Apache Ambari
Hortonworks Technical Workshop: Apache Ambari
 
LLAP: long-lived execution in Hive
LLAP: long-lived execution in HiveLLAP: long-lived execution in Hive
LLAP: long-lived execution in Hive
 
Securing Hadoop with Apache Ranger
Securing Hadoop with Apache RangerSecuring Hadoop with Apache Ranger
Securing Hadoop with Apache Ranger
 
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele
Developing Applications with Hadoop 2.0 and YARN by Abhijit Lele
 
Log Analytics Optimization
Log Analytics OptimizationLog Analytics Optimization
Log Analytics Optimization
 
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
 
Hortonworks Technical Workshop: HDP everywhere - cloud considerations using...
Hortonworks Technical Workshop:   HDP everywhere - cloud considerations using...Hortonworks Technical Workshop:   HDP everywhere - cloud considerations using...
Hortonworks Technical Workshop: HDP everywhere - cloud considerations using...
 
Internet of things Crash Course Workshop
Internet of things Crash Course WorkshopInternet of things Crash Course Workshop
Internet of things Crash Course Workshop
 
Hortonworks Technical Workshop: HBase For Mission Critical Applications
Hortonworks Technical Workshop: HBase For Mission Critical ApplicationsHortonworks Technical Workshop: HBase For Mission Critical Applications
Hortonworks Technical Workshop: HBase For Mission Critical Applications
 
Delivering Apache Hadoop for the Modern Data Architecture
Delivering Apache Hadoop for the Modern Data Architecture Delivering Apache Hadoop for the Modern Data Architecture
Delivering Apache Hadoop for the Modern Data Architecture
 
What s new in spark 2.3 and spark 2.4
What s new in spark 2.3 and spark 2.4What s new in spark 2.3 and spark 2.4
What s new in spark 2.3 and spark 2.4
 
Hortonworks Technical Workshop - Operational Best Practices Workshop
Hortonworks Technical Workshop - Operational Best Practices WorkshopHortonworks Technical Workshop - Operational Best Practices Workshop
Hortonworks Technical Workshop - Operational Best Practices Workshop
 

Similaire à Manage Long-Running Apps on YARN with Apache Slider

Accumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit
 
Bring your Service to YARN
Bring your Service to YARNBring your Service to YARN
Bring your Service to YARNDataWorks Summit
 
Apache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesApache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesDataWorks Summit
 
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterEnterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterDataWorks Summit
 
Docker based Hadoop provisioning - anywhere
Docker based Hadoop provisioning - anywhereDocker based Hadoop provisioning - anywhere
Docker based Hadoop provisioning - anywhereDataWorks Summit
 
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
 
YARN - Presented At Dallas Hadoop User Group
YARN - Presented At Dallas Hadoop User GroupYARN - Presented At Dallas Hadoop User Group
YARN - Presented At Dallas Hadoop User GroupRommel Garcia
 
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
 
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
 
Hadoop Summit Europe 2015 - YARN Present and Future
Hadoop Summit Europe 2015 - YARN Present and FutureHadoop Summit Europe 2015 - YARN Present and Future
Hadoop Summit Europe 2015 - YARN Present and FutureVinod Kumar Vavilapalli
 
Apache Hadoop YARN 2015: Present and Future
Apache Hadoop YARN 2015: Present and FutureApache Hadoop YARN 2015: Present and Future
Apache Hadoop YARN 2015: Present and FutureDataWorks Summit
 
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterEnterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterDataWorks Summit
 
Apache Tez - A unifying Framework for Hadoop Data Processing
Apache Tez - A unifying Framework for Hadoop Data ProcessingApache Tez - A unifying Framework for Hadoop Data Processing
Apache Tez - A unifying Framework for Hadoop Data ProcessingDataWorks Summit
 
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...Data Con LA
 
Apache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitApache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitSaptak Sen
 
Introduction to the Hortonworks YARN Ready Program
Introduction to the Hortonworks YARN Ready ProgramIntroduction to the Hortonworks YARN Ready Program
Introduction to the Hortonworks YARN Ready ProgramHortonworks
 
Deploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderDeploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderHortonworks
 
One Click Hadoop Clusters - Anywhere (Using Docker)
One Click Hadoop Clusters - Anywhere (Using Docker)One Click Hadoop Clusters - Anywhere (Using Docker)
One Click Hadoop Clusters - Anywhere (Using Docker)DataWorks Summit
 

Similaire à Manage Long-Running Apps on YARN with Apache Slider (20)

Apache Slider
Apache SliderApache Slider
Apache Slider
 
October 2014 HUG : Apache Slider
October 2014 HUG : Apache SliderOctober 2014 HUG : Apache Slider
October 2014 HUG : Apache Slider
 
Accumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARNAccumulo Summit 2014: Accumulo on YARN
Accumulo Summit 2014: Accumulo on YARN
 
Bring your Service to YARN
Bring your Service to YARNBring your Service to YARN
Bring your Service to YARN
 
Apache Hadoop YARN: best practices
Apache Hadoop YARN: best practicesApache Hadoop YARN: best practices
Apache Hadoop YARN: best practices
 
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterEnterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
 
Docker based Hadoop provisioning - anywhere
Docker based Hadoop provisioning - anywhereDocker based Hadoop provisioning - anywhere
Docker based Hadoop provisioning - anywhere
 
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
 
YARN - Presented At Dallas Hadoop User Group
YARN - Presented At Dallas Hadoop User GroupYARN - Presented At Dallas Hadoop User Group
YARN - Presented At Dallas Hadoop User Group
 
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
 
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
 
Hadoop Summit Europe 2015 - YARN Present and Future
Hadoop Summit Europe 2015 - YARN Present and FutureHadoop Summit Europe 2015 - YARN Present and Future
Hadoop Summit Europe 2015 - YARN Present and Future
 
Apache Hadoop YARN 2015: Present and Future
Apache Hadoop YARN 2015: Present and FutureApache Hadoop YARN 2015: Present and Future
Apache Hadoop YARN 2015: Present and Future
 
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop ClusterEnterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
Enterprise-Grade Rolling Upgrade for a Live Hadoop Cluster
 
Apache Tez - A unifying Framework for Hadoop Data Processing
Apache Tez - A unifying Framework for Hadoop Data ProcessingApache Tez - A unifying Framework for Hadoop Data Processing
Apache Tez - A unifying Framework for Hadoop Data Processing
 
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...
Big Data Day LA 2015 - What's new and next in Apache Tez by Bikas Saha of Hor...
 
Apache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop SummitApache Spark Workshop at Hadoop Summit
Apache Spark Workshop at Hadoop Summit
 
Introduction to the Hortonworks YARN Ready Program
Introduction to the Hortonworks YARN Ready ProgramIntroduction to the Hortonworks YARN Ready Program
Introduction to the Hortonworks YARN Ready Program
 
Deploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via SliderDeploying Docker applications on YARN via Slider
Deploying Docker applications on YARN via Slider
 
One Click Hadoop Clusters - Anywhere (Using Docker)
One Click Hadoop Clusters - Anywhere (Using Docker)One Click Hadoop Clusters - Anywhere (Using Docker)
One Click Hadoop Clusters - Anywhere (Using Docker)
 

Plus de Hortonworks

Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next Level
Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next LevelHortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next Level
Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next LevelHortonworks
 
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT Strategy
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT StrategyIoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT Strategy
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT StrategyHortonworks
 
Getting the Most Out of Your Data in the Cloud with Cloudbreak
Getting the Most Out of Your Data in the Cloud with CloudbreakGetting the Most Out of Your Data in the Cloud with Cloudbreak
Getting the Most Out of Your Data in the Cloud with CloudbreakHortonworks
 
Johns Hopkins - Using Hadoop to Secure Access Log Events
Johns Hopkins - Using Hadoop to Secure Access Log EventsJohns Hopkins - Using Hadoop to Secure Access Log Events
Johns Hopkins - Using Hadoop to Secure Access Log EventsHortonworks
 
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad Guys
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad GuysCatch a Hacker in Real-Time: Live Visuals of Bots and Bad Guys
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad GuysHortonworks
 
HDF 3.2 - What's New
HDF 3.2 - What's NewHDF 3.2 - What's New
HDF 3.2 - What's NewHortonworks
 
Curing Kafka Blindness with Hortonworks Streams Messaging Manager
Curing Kafka Blindness with Hortonworks Streams Messaging ManagerCuring Kafka Blindness with Hortonworks Streams Messaging Manager
Curing Kafka Blindness with Hortonworks Streams Messaging ManagerHortonworks
 
Interpretation Tool for Genomic Sequencing Data in Clinical Environments
Interpretation Tool for Genomic Sequencing Data in Clinical EnvironmentsInterpretation Tool for Genomic Sequencing Data in Clinical Environments
Interpretation Tool for Genomic Sequencing Data in Clinical EnvironmentsHortonworks
 
IBM+Hortonworks = Transformation of the Big Data Landscape
IBM+Hortonworks = Transformation of the Big Data LandscapeIBM+Hortonworks = Transformation of the Big Data Landscape
IBM+Hortonworks = Transformation of the Big Data LandscapeHortonworks
 
Premier Inside-Out: Apache Druid
Premier Inside-Out: Apache DruidPremier Inside-Out: Apache Druid
Premier Inside-Out: Apache DruidHortonworks
 
Accelerating Data Science and Real Time Analytics at Scale
Accelerating Data Science and Real Time Analytics at ScaleAccelerating Data Science and Real Time Analytics at Scale
Accelerating Data Science and Real Time Analytics at ScaleHortonworks
 
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATA
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATATIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATA
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATAHortonworks
 
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...Hortonworks
 
Delivering Real-Time Streaming Data for Healthcare Customers: Clearsense
Delivering Real-Time Streaming Data for Healthcare Customers: ClearsenseDelivering Real-Time Streaming Data for Healthcare Customers: Clearsense
Delivering Real-Time Streaming Data for Healthcare Customers: ClearsenseHortonworks
 
Making Enterprise Big Data Small with Ease
Making Enterprise Big Data Small with EaseMaking Enterprise Big Data Small with Ease
Making Enterprise Big Data Small with EaseHortonworks
 
Webinewbie to Webinerd in 30 Days - Webinar World Presentation
Webinewbie to Webinerd in 30 Days - Webinar World PresentationWebinewbie to Webinerd in 30 Days - Webinar World Presentation
Webinewbie to Webinerd in 30 Days - Webinar World PresentationHortonworks
 
Driving Digital Transformation Through Global Data Management
Driving Digital Transformation Through Global Data ManagementDriving Digital Transformation Through Global Data Management
Driving Digital Transformation Through Global Data ManagementHortonworks
 
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming Features
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming FeaturesHDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming Features
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming FeaturesHortonworks
 
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...Hortonworks
 
Unlock Value from Big Data with Apache NiFi and Streaming CDC
Unlock Value from Big Data with Apache NiFi and Streaming CDCUnlock Value from Big Data with Apache NiFi and Streaming CDC
Unlock Value from Big Data with Apache NiFi and Streaming CDCHortonworks
 

Plus de Hortonworks (20)

Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next Level
Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next LevelHortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next Level
Hortonworks DataFlow (HDF) 3.3 - Taking Stream Processing to the Next Level
 
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT Strategy
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT StrategyIoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT Strategy
IoT Predictions for 2019 and Beyond: Data at the Heart of Your IoT Strategy
 
Getting the Most Out of Your Data in the Cloud with Cloudbreak
Getting the Most Out of Your Data in the Cloud with CloudbreakGetting the Most Out of Your Data in the Cloud with Cloudbreak
Getting the Most Out of Your Data in the Cloud with Cloudbreak
 
Johns Hopkins - Using Hadoop to Secure Access Log Events
Johns Hopkins - Using Hadoop to Secure Access Log EventsJohns Hopkins - Using Hadoop to Secure Access Log Events
Johns Hopkins - Using Hadoop to Secure Access Log Events
 
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad Guys
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad GuysCatch a Hacker in Real-Time: Live Visuals of Bots and Bad Guys
Catch a Hacker in Real-Time: Live Visuals of Bots and Bad Guys
 
HDF 3.2 - What's New
HDF 3.2 - What's NewHDF 3.2 - What's New
HDF 3.2 - What's New
 
Curing Kafka Blindness with Hortonworks Streams Messaging Manager
Curing Kafka Blindness with Hortonworks Streams Messaging ManagerCuring Kafka Blindness with Hortonworks Streams Messaging Manager
Curing Kafka Blindness with Hortonworks Streams Messaging Manager
 
Interpretation Tool for Genomic Sequencing Data in Clinical Environments
Interpretation Tool for Genomic Sequencing Data in Clinical EnvironmentsInterpretation Tool for Genomic Sequencing Data in Clinical Environments
Interpretation Tool for Genomic Sequencing Data in Clinical Environments
 
IBM+Hortonworks = Transformation of the Big Data Landscape
IBM+Hortonworks = Transformation of the Big Data LandscapeIBM+Hortonworks = Transformation of the Big Data Landscape
IBM+Hortonworks = Transformation of the Big Data Landscape
 
Premier Inside-Out: Apache Druid
Premier Inside-Out: Apache DruidPremier Inside-Out: Apache Druid
Premier Inside-Out: Apache Druid
 
Accelerating Data Science and Real Time Analytics at Scale
Accelerating Data Science and Real Time Analytics at ScaleAccelerating Data Science and Real Time Analytics at Scale
Accelerating Data Science and Real Time Analytics at Scale
 
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATA
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATATIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATA
TIME SERIES: APPLYING ADVANCED ANALYTICS TO INDUSTRIAL PROCESS DATA
 
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...
Blockchain with Machine Learning Powered by Big Data: Trimble Transportation ...
 
Delivering Real-Time Streaming Data for Healthcare Customers: Clearsense
Delivering Real-Time Streaming Data for Healthcare Customers: ClearsenseDelivering Real-Time Streaming Data for Healthcare Customers: Clearsense
Delivering Real-Time Streaming Data for Healthcare Customers: Clearsense
 
Making Enterprise Big Data Small with Ease
Making Enterprise Big Data Small with EaseMaking Enterprise Big Data Small with Ease
Making Enterprise Big Data Small with Ease
 
Webinewbie to Webinerd in 30 Days - Webinar World Presentation
Webinewbie to Webinerd in 30 Days - Webinar World PresentationWebinewbie to Webinerd in 30 Days - Webinar World Presentation
Webinewbie to Webinerd in 30 Days - Webinar World Presentation
 
Driving Digital Transformation Through Global Data Management
Driving Digital Transformation Through Global Data ManagementDriving Digital Transformation Through Global Data Management
Driving Digital Transformation Through Global Data Management
 
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming Features
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming FeaturesHDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming Features
HDF 3.1 pt. 2: A Technical Deep-Dive on New Streaming Features
 
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...
Hortonworks DataFlow (HDF) 3.1 - Redefining Data-In-Motion with Modern Data A...
 
Unlock Value from Big Data with Apache NiFi and Streaming CDC
Unlock Value from Big Data with Apache NiFi and Streaming CDCUnlock Value from Big Data with Apache NiFi and Streaming CDC
Unlock Value from Big Data with Apache NiFi and Streaming CDC
 

Dernier

Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesZilliz
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
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
 
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
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
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
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024The Digital Insurer
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piececharlottematthew16
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...Fwdays
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embeddingZilliz
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
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
 

Dernier (20)

Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector Databases
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
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?
 
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
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
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
 
My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024My INSURER PTE LTD - Insurtech Innovation Award 2024
My INSURER PTE LTD - Insurtech Innovation Award 2024
 
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
 
Story boards and shot lists for my a level piece
Story boards and shot lists for my a level pieceStory boards and shot lists for my a level piece
Story boards and shot lists for my a level piece
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Training state-of-the-art general text embedding
Training state-of-the-art general text embeddingTraining state-of-the-art general text embedding
Training state-of-the-art general text embedding
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
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
 

Manage Long-Running Apps on YARN with Apache Slider

  • 1. © Hortonworks Inc. 2014 YARN Ready – Apache Slider Provisioning, Managing, and Monitoring YARN Applications Sumit Mohanty @smohanty (@hortonworks) Steve Loughran @steveloughran (@hortonworks) Page 1
  • 2. © Hortonworks Inc. 2014 Agenda • Long running applications on YARN • Introduction to Slider • Writing a Slider Application • Key Slider Features • Conclusion • Q/A Page 2
  • 3. © Hortonworks Inc. 2014 Applications on Yarn Page 3
  • 4. © Hortonworks Inc. 2014 YARN runs code across the cluster Page 4 HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager “The RM” HDFS YARN Node Manager • Servers run YARN Node Managers • NM's heartbeat to Resource Manager • RM schedules work over cluster • RM allocates containers to apps • NMs start containers • NMs report container health
  • 5. © Hortonworks Inc. 2014 Client creates App Master Page 5 HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager “The RM” HDFS YARN Node Manager Client Application Master
  • 6. © Hortonworks Inc. 2014 AM asks for containers Page 6 HDFS YARN Node Manager HDFS YARN Node Manager HDFS YARN Resource Manager HDFS YARN Node Manager Application Master Container Container Container
  • 7. © Hortonworks Inc. 2014 YARN notifies AM of failures Page 7 HDFS YARN Node Manager HDFS YARN Node Manager Container HDFS YARN Resource Manager HDFS YARN Node Manager Application Master Container Container
  • 8. © Hortonworks Inc. 2014 Long Running Applications Page 8
  • 9. © Hortonworks Inc. 2014 Management Page 9 • Application instance must be managed –(Install/Configure/Start) –Restart –Reconfigure/Rolling update –Stop/Graceful stop –Status –Activate/deactivate/rebalance • Upgrade –Long running applications need to provide upgrade support, preferably rolling upgrade
  • 10. © Hortonworks Inc. 2014 Registration and Discovery Page 10 • Application must declare itself –URLs –Host/port –Config (client config) • Application must be discoverable –Registry –Name-based lookups –Regularly updated • Client support –Callback if “data” changes; thick clients –Configurable gateway; thin clients
  • 11. © Hortonworks Inc. 2014 Monitoring Page 11 • Metrics –Instantaneous metrics (jmx) –Time-series metrics (ganglia) –Configure Ganglia or other metrics stores • Alerts –Based of jmx/port scan/container status –Configure Nagios or other alerting mechanism
  • 12. © Hortonworks Inc. 2014 Logs and Events Page 12 • Logs –Continuous log gathering –Single view for logs across all containers • Lifecycle Events –Integration with Application Timeline Server
  • 13. © Hortonworks Inc. 2014 In addition to … Page 13 • Security –Configured for security –Token renewal • High Availability –On a highly available cluster (NN, RM HA) –Itself highly available (multi-master) • Packaging • Configurability • …
  • 14. © Hortonworks Inc. 2014 Apache Slider Page 14
  • 15. © Hortonworks Inc. 2014 Why? • Many mature applications exist • Full YARN-integration takes effort • Running under YARN delivers access to all the data in HDFS –and the CPU power alongside it • As Hadoop stack evolves, more to integrate with • Management tools –e.g. Ambari– exist to monitor applications in-cluster Page 15
  • 16. © Hortonworks Inc. 2014 Slider is an in-incubation project with one goal: Make it possible and easy to deploy and manage existing applications on a YARN cluster Page 16 Status: Currently in Tech Preview GA with the next HDP release, tentatively November
  • 17. © Hortonworks Inc. 2014 Slider view of an Application Page 17 • An application is a set of components • A component is a daemon/launched exe –configuration –scripts, data files, etc. • Component may have one or more instances • Component instances are managed –By extension, the app instance is • Example –HBase Application (3 components) – HBase Master – HBase RegionServer – HBase REST service
  • 18. © Hortonworks Inc. 2014 YARN Containers with Slider Page 18 YARN Node Manager Component (container)AppMaster (container) YARN Node Manager HDFS Slider Agent Application Slider AppMaster Slider Client HDFS HDFS YARN Resource Manager
  • 19. © Hortonworks Inc. 2014 Application by Slider Page 19 Slider App Package Slider CLI HDFS YARN Resource Manager “The RM” HDFS YARN Node Manager Agent Component HDFS YARN Node Manager Agent Component Similar to any YARN application 1. CLI starts an instance of the AM 2. AM requests containers 3. Containers activate with an Agent 4. Agent gets application definition 5. Agent registers with AM 6. AM issues commands 7. Agent reports back, status, configuration, etc. 8. AM publishes endpoints, configurations Application Registry App Master/Agent Provider
  • 20. © Hortonworks Inc. 2014 Slider AppMaster/Agent/Client Page 20 • AppMaster –Common YARN interactions –Common *-client interactions –Publishing needs • Agent –Configure and start –Re-configure and restart –Heartbeats & failure detection –Port allocations and publishing –Custom commands if any (e.g. graceful-stop) • Client –App life cycle commands (flex, status, …)
  • 21. © Hortonworks Inc. 2014 Memcached on YARN Sample Slider App Page 21
  • 22. © Hortonworks Inc. 2014 Other Application Packages Page 23 • Reference doc for Memcached Application –http://slider.incubator.apache.org/docs/slider_specs/hello_world_sl ider_app.html • Slider github repo has other app –Accumulo –HBase –Storm –Memcached-windows
  • 23. © Hortonworks Inc. 2014 Other Capabilities Page 24
  • 24. © Hortonworks Inc. 2014 App Packaging Capabilities Page 25 • Dynamic port allocation and sharing • Inter-component dependency –Specify the start order of components • Exports –Construct arbitrary name value pairs –E.g. URLs (org.apache.slider.monitor: http://${HBASE_MASTER_HOST}:${site.hbase- site.hbase.master.info.port}/master-status) • Default HDFS and ZK isolation
  • 25. © Hortonworks Inc. 2014 Application Registry Page 26 • A common problem (not specific to Slider) – https://issues.apache.org/jira/browse/YARN-913 • Currently, – Apache Curator based – Register URLs pointing to actual data – AM doubles up as a webserver for published data • Plan – Registry should be stand-alone – Slider is a consumer as well as publisher – Slider focuses on declarative solution for Applications to publish data – Allows integration of Applications independent of how they are hosted
  • 26. © Hortonworks Inc. 2014 Plan: YARN Service Registry # YARN-wide registry in Zookeeper # Services listed by (user, service class, name) /yarnRegistry/users/sumit/slider/cluster1 # Ephemeral liveness node /yarnRegistry/users/sumit/slider/cluster1/live # service entry lists bindings: URLs, IPC (host, port), ZK # individual components have own (ephemeral) entries & endpoints /yarnRegistry/users/sumit/slider/cluster1/components/appmaster # ZK R/W API, REST read-only API Page 27
  • 27. © Hortonworks Inc. 2014 Security Page 28 • Applications validated to work in Kerberos secured cluster –Secure cluster created and keytabs available to application components –Security parameters specified in application configuration –User obtains TGT (kinit) prior to Slider application creation –E.g. HBase 0.98.4 • Agent-AM SSL communication –One-Way by default –Two-Way can be enabled • Work initiated on ticket renewal for long running applications –YARN, HDFS
  • 28. © Hortonworks Inc. 2014 Failure Handling Page 29 • Application Component Failure –Component instance restarted • AppMaster failure –YARN restarts the AppMaster, Slider reconstructs states, registry –App lifecycle commands are temporarily unavailable • NodeManager failure –App remains unaffected • ResourceManager/NodeManager failures with HA –App remains unaffected
  • 29. © Hortonworks Inc. 2014 Windows and Linux Support Page 30 • Feature set parity on both platforms • Similar packaging constructs –Typically, only path spec needs to change • Both Linux and Windows Server as a platform for –Client (host slider-client) –Cluster (host hadoop cluster)
  • 30. © Hortonworks Inc. 2014 Join in: Bring your favorite Applications to YARN Page 31
  • 31. © Hortonworks Inc. 2014 Slider-ifying a new application 1. Grab slider: http://slider.incubator.apache.org/downloads/ 2. Look at App Package docs: http://slider.incubator.apache.org/docs/slider_specs/ 3. Look at source code examples under app-packages 4. Start with memcached/memcached-windows Page 32
  • 32. © Hortonworks Inc. 2014 YARN API vs. Slider Page 33 • Native YARN app –Your own AppMaster is in charge: container placement, fault handling –You can implement an IPC API for callers to manipulate the application –AppMaster can send out event notifications Ideal for large-scale distributed algorithms, with specific placement and scheduling needs • Slider App –Slider AppMaster handles YARN integration with best-effort placement history, fault handling (recreate component instance) –Simple API/Web UI for cluster manipulation, endpoint listing –Lots of failure and security testing –You only need to write the App package (& test) Long-lived applications where failures can addressed by restarting elsewhere, with flexing decisions by admins
  • 33. © Hortonworks Inc. 2014 Everyone is welcome • Useful Links –Website – http://slider.incubator.apache.org/ –Dev Mailing Lists – dev@slider.incubator.apache.org –JIRA – https://issues.apache.org/jira/browse/SLIDER • Current and Upcoming Releases – Slider 0.30 (May) – Slider 0.40 (July) – Slider 0.50 (planned) Page 34
  • 34. © Hortonworks Inc. 2014 Q/A http://slider.incubator.apache.org/ Page 35
  • 36. Next Steps 1. Review YARN Slider Resources 2. Review webinar recording or attend the next webinar 3. Attend Office Hours 4. Sign up for a 2 day class 5. Attend the next YARN webinar
  • 37. Resources Setup HDP 2.1 environment • Leverage Sandbox: Hortonworks.com/Sandbox Get Started with YARN • http://hortonworks.com/get-started/YARN Technical Preview • http://hortonworks.com/blog/apache-slider-technical-preview-now- available/ Apache • http://slider.incubator.apache.org/ Dev Mailing Lists • dev@slider.incubator.apache.org JIRA • https://issues.apache.org/jira/browse/SLIDER
  • 38. Hortonworks Office Hours YARN Office Hours Dial in and chat with YARN experts Next Office Hour: Thursday August 14 @ 10-11am PDT. Register: https://hortonworks.webex.com/hortonworks/onstage/g.php?t=a&d=628 190636 We plan Office Hours for September 11th and October 9th @ 10am PT (2nd Thursdays) Invitations will go out to those that attended or reviewed YARN webinars
  • 39. And from Hortonworks University Hortonworks Course: Developing Custom YARN Applications Format: Online Duration: 2 Days When: September – date tbd Cost: No Charge to Hortonworks Partners Space: Very Limited Interested? Please contact Lisa
  • 40. Next in the Series! Join us for the full series of YARN Ready webinars: YARN Native July 24 @ 9am PT (recording link) Tez August 21 @ 9am PT (registration link) Additional webinar topics are being added – watch the blog or visit Hortonworks.com/webinars: September: Ambari and Scalding October: Spark http://hortonworks.com/webinars
  • 41. © Hortonworks Inc. 2014 Thank you. Page 42

Notes de l'éditeur

  1. Register for Office Hours: https://hortonworks.webex.com/hortonworks/onstage/g.php?t=a&d=628190636
  2. Recording “YARN Native” https://hortonworks.webex.com/hortonworks/lsr.php?RCID=7bad7795d07e408ccbe7412e9950603d Integrating with Tez Aug 21 https://hortonworks.webex.com/hortonworks/onstage/g.php?t=a&d=622317625