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A Multi Colored YARN
1.
Vinod Kumar Vavilapalli Apache
Hadoop PMC, Co-founder of YARN project Hortonworks Inc A Multi-Colored YARN
2.
2 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved About.html Apache Hadoop PMC, ASF Member 9 years of only Hadoop – Finally the job-adverts asking for “10 years of Hadoop experience” have validity ’Rewritten’ the Hadoop processing side – Became Apache Hadoop YARN With me today – Billie Rinaldi: VP Apache Accumulo, Apache Slider PMC, ASF Member – Jayush Luniya: Apache Ambari PMC – Vadim Vaks: Kickass field guy (Sr. Solutions Architect)
3.
3 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Hadoop Compute Platform Today Layers that enable applications and higher order frameworks It’s all about data! Still a single colored yarn Apache Hadoop YARN pretty good at jobs, queries, short running apps – We will continue doing this Admins and admin tools (Ambari) takes care of statically provisioned services
4.
4 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Hadoop Compute Platform Today Platform Services Storage Resource Management Security Management Monitoring Alerts Governance MR Tez Spark … Run everything in a single secure, multi- tenant, elastic Hadoop YARN cluster – An ongoing journey Adding new ‘stuff’ to this stack is an involved effort
5.
5 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Evolution of user focus A need for reuse, composition and to keep building ‘upwards’ Applications & services & more complex combinations - Assembly IOT ApplicationsApache Metron
6.
6 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved IOT ApplicationsApache Metron • Simplified deployment of an assembly – Ready to go packages – Discovery – Resource/capacity planning • Management / monitoring / metrics of assemblies! – “Start / stop” my business app end-to-end – “Tell me what’s happening with my business application” – “I don’t care whether HBase RegionServer is down or not, is my assembly healthy?” • Scale up/down the entire app! – “I got more input coming in, I don’t care how you scale individual pieces, but do scale the entire machinery” Emerging needs of the platform
7.
7 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Why on YARN? Manual plumbing is very tiresome, not repeatable Assemblies - similar to apps & services, but N x harder (because there are N services to grapple with) Why not static allocations? – Machines die – Jobs (MapReduce, Spark) are tolerant of faults, but static services aren’t! – Upfront capacity planning – Cannot react to hardware or utilization changes without manual intervention – Elasticity is a manual operation This is fundamentally the same resource-management problem that YARN is built to address!
8.
8 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Why on YARN? Contd.. The Apache Hadoop ecosystem knows Data services the best – YARN is data-first! Big Data use-cases don’t stop at Hadoop services and apps – Hive for all data, summary in traditional on-demand DB for driving analysts – Extracting results from HDP and hosting report servers, interactive Uis like Apache Zeppelin Users don’t care about this separation – Big Data is already a huge cluster on one side – Asking for another infrastructure & needing separate management of this other stuff is burdensome – Unified solution >> Silos
9.
9 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Hadoop Compute Platform Next A colorful, multi-threaded yarn For use-cases of various colors Today’s applications better Simplified long running applications Bring your app easily https://www.flickr.com/photos/happyskrappy/15699919424
10.
10 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved What is happening now?
11.
11 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Packaging Containers – Lightweight mechanism for packaging and resource isolation – Popularized and made accessible by Docker – Can replace VMs in some cases – Or more accurately, VMs got used in places where they didn’t need to be Native integration ++ in YARN – Support for “Container Runtimes” in LCE: YARN-3611 – Process runtime – Docker runtime
12.
12 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved APIs Applications need simple APIs Need to be deployable “easily” Simple REST API layer fronting YARN – https://issues.apache.org/jira/browse/YARN-4793 – [Umbrella] Simplified API layer for services and beyond Spawn services & Manage them
13.
13 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Platform++ YARN itself is evolving to support services and complex apps – https://issues.apache.org/jira/browse/YARN-4692 – [Umbrella] Simplified and first-class support for services in YARN Scheduling – Application priorities: YARN-1963 – Affinity / anti-affinity: YARN-1042 – Services as first-class citizens: Preemption, reservations etc
14.
14 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Platform++ Contd Application & Services upgrades – ”Do an upgrade of my Spark / HBase apps with minimal impact to end-users” – YARN-4726 Simplified discovery of services via DNS mechanisms: YARN-4757 YARN Federation – to infinity and beyond: YARN-2915 Easier container sizing models: Resource profiles: YARN-3926
15.
15 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Framework++ Platform is only as good as the tools A native YARN framework – https://issues.apache.org/jira/browse/YARN-4692 – [Umbrella] Native YARN framework layer for services and beyond Slider supporting a DAG of apps: – https://issues.apache.org/jira/browse/SLIDER-875
16.
16 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved User facing and operational experience Modern YARN web UI - YARN-3368 Enhanced shell interfaces Metrics: Timeline Service V2 – YARN-2928 Application & Services monitoring, integration with other systems First class support for YARN hosted services in Ambari – https://issues.apache.org/jira/browse/AMBARI-17353
17.
17 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Use-cases.. Assemble! Platform Services Storage Resource Management Security Service Discovery Management Monitoring Alerts Holiday Assembly HBase Web Server IOT Assembly Kafka Storm HBase Solr Governance MR Tez Spark …
18.
18 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Take away..
19.
19 © Hortonworks
Inc. 2011 – 2016. All Rights Reserved Thank You (Rest of) The demo Team • Gour Saha • Sidhartha Seethana • Varun Vasudev • Shane Kumpf • Jaimin Jetly • Yusaku Sako • Yu Liu
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