Leveraging Database Technologies in Condor

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Leveraging Database Technologies in Condor

• Jeff Naughton
• April 25, 2006

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Overview

• Introducing ourselves
• What we have done since last year
• Obtained funding (Yay! thank you NSF!)
• Quill deployed DB-centric data tool
• Quill more comprehensive, deployed in
  test-cluster, running (guinea pig) user jobs
• Condor J2EE radical departure experimental
  system, deployed last week in test cluster
• Published some research papers
• BOF 130 on Thursday

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Who we are

• Faculty David DeWitt, Jeff Naughton
• Students Jiansheng Huang, Ameet Kini, Christine
  Reilly, Eric Robinson, Srinath Shankar,
  Lakshmikant Shrinivas

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How do we fit in?

• Advanced Development/Research group focused on
  data management.
• Goal
• Interact frequently with Condor Dev. Team and
  users
• Design and prototype new technology
• transfer to Condor team for deployment.
• What we dont do
• Determine roadmap and schedules for deployment
  within Condor.

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Why Condor and DBMS?

• Premise A running Condor system is awash in
  data
• Operational data, Historical data, User data
• DBMS technology can help capture, organize,
  manage, archive, and query this data.
• This can make Condor even more powerful, usable,
  and useful.

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Quill

• Non-invasive approach to capturing job related
  information
• Works by sniffing updates to the job queue log
• Serves condor_q and condor_history queries
• Independent, reliable, and efficient querying of
  job related information, with underlying SQL
  interface
• So how does it work?

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Quill Architecture
Master
Startd

Quill
Schedd
Store events
Write events
Get new events
RDBMS
Queue History Tables
Job Queue log
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Quill

• More comprehensive than Quill (data from all
  daemons, not just SchedD)
• Built on Quill code base
• Condor daemons write to SQL logs, Quill daemon
  reads and inserts in DBMS
• Central database serves entire pool
• Web-based query GUI

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Data Capture in Quill

• Condor daemons augmented to record important
  events in a database
• Database is in addition to standard daemon logs
• Pool will run unaffected even in the absence of a
  database

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Quill Architecture
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Implementation Details

• Quill First class condor daemon
• Managed by Condor Master
• Native PostgreSQL API
• Can be ported to any platform for which
  PostgreSQL drivers are available (AIX, BSD, IRIX,
  HP-UX, Linux, Solaris, Windows etc.)
• Porting Quill to other databases involves
  implementing a database virtual class

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Web Interface

• Useful for
• User job monitoring
• Administrative monitoring over jobs and resources
• Debugging

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Condordb Admin Screen
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Job history by owner
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Machine Report
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Status about a job
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Recency info for exceptional data sources
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Present Status

• Deployed in testbed
• dbc cluster (93 machines)
• Has successfully run almost 100,000 jobs.
• Working with Condor team planning future
  distribution with Condor.

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Caveats

• Web interface to DB
• Basic prototype implemented
• Needs to be made more robust, user friendly (!)
• Gathers incomplete information in multiple pool
  scenarios (flocking, glide-in, condor-c)

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CondorJ2

• To boldly go where no one has gone before
• Quill/Quill Database reflects state of Condor
  pool
• Condor J2 Database is the state of Condor pool
• Overview of CondorJ2
• Use database to maintain operational data
  (workflow state, machine state, config policies,
  etc.)
• Implement workflow management, resource
  management and resource allocation in Application
  Server environment
• Modify master, startd and starter to be thin web
  service clients
• Provide web interface for all system services
  (workflow submission, machine reconfiguration
  etc.)

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Motivation

• Scalability
• Flexibility
• Administratibility

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Java Application Servers

• Industrial strength middleware for high
  performance scalable web applications
• Widely deployed systems
• Oracle AS 10g, IBM WebSphere, BEA WebLogic, JBoss
  (open source)
• Key features
• Support for transactions
• Web service interfaces
• Support for clustering (for scalability)
• Configurable security
• Backend database independence

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Condor Database
JDBC
Application Server
Machine Modules
Matchmaking Modules
Workflow Modules
Condor Web Services
Condor Pool Web Site
HTTP
SOAP over HTTP
Users Web Browser
master startd starter
Users Custom Tools
Web Service Clients
Execute Machines
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What can do in CondorJ2 via browsers and web
services?

• Add and configure new machines
• Reconfigure machines on the fly
• Specify, submit, monitor and manage workflows
• Monitor global system state

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Virtuous Cycle

• As we learn where Condor can use DBMS technology,
  we learn where DBMS technology can be (must be?)
  improved.
• Support for sparse data sets ICDE 2006.
• Pushing match-making style operations into DBMS
  SIGMOD 2006.
• Data provenance as byproduct of Quill data
  capture. IPAW 2006
• Improving DBMS technology will lead to more
  places that it can be installed.

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Other ongoing work

• File caching in Condor pools
• Techniques for explaining data consistency rather
  than dictating consistency
• Automatic monitoring of system health by mining
  captured data

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Visit us and see demos!

• Come see demos of Quill, Quill, and CondorJ2 in
  Rm. 216/218 Fluno Center on Thurs. afternoon 130
  230pm.