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Using Condor An Introduction Condor Week 2008. The Condor Project (Established ‘85). Distributed High Throughput Computing research performed by a team of ~35 faculty, full time staff and students. The Condor Project (Established ‘85).

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Using condor an introduction condor week 2008

Using Condor An IntroductionCondor Week 2008


The condor project established 85

The Condor Project (Established ‘85)

Distributed High Throughput Computing research performed by a team of ~35 faculty, full time staff and students.


The condor project established 851

The Condor Project (Established ‘85)

Distributed High Throughput Computing research performed by a team of ~35 faculty, full time staff and students who:

  • face software engineering challenges in a distributed UNIX/Linux/NT environment

  • are involved in national and international grid collaborations,

  • actively interact with academic and commercial users,

  • maintain and support large distributed production environments,

  • and educate and train students.


Some free software produced by the condor project

Some free software produced by the Condor Project

  • MW

  • NeST / LotMan

  • Stork

  • And others… all as open source

  • Condor System

  • VDT

  • Metronome

  • ClassAd Library

  • DAGMan

  • Hawkeye

  • GCB


Full featured system

Full featured system

  • Flexible scheduling policy engine via ClassAds

    • Preemption, suspension, requirements, preferences, groups, quotas, settable fair-share, system hold…

  • Facilities to manage BOTH dedicated CPUs (clusters) and non-dedicated resources (desktops)

  • Transparent Checkpoint/Migration for many types of serial jobs

  • No shared file-system required

  • Federate clusters w/ a wide array of Grid Middleware

  • Workflow management (inter-dependencies)

  • Support for many job types – serial, parallel, etc.

  • Fault-tolerant: can survive crashes, network outages, no single point of failure.

  • Development APIs: via SOAP / web services, DRMAA (C), Perl package, GAHP, flexible command-line tools, MW

  • Platforms: Linux i386/IA64, Windows 2k/XP, MacOS, Solaris, IRIX, HP-UX, Compaq Tru64, … lots.


Meet frieda

She is a scientist with a big problem.

Meet Frieda.


Frieda s application

Frieda’s Application …

Run a Parameter Sweep of F(x,y,z) for 20 values of x, 10 values of y and 3 values of z

  • 20×10×3 = 600 combinations

  • F takes on the average 6 hours to compute on a “typical” workstation (total = 600 × 6 = 3600 hours)

  • F requires a “moderate” (256MB) amount of memory

  • F performs “moderate” I/O - (x,y,z) is 5 MB and F(x,y,z) is 50 MB


I have 600 simulations to run where can i get help

I have 600simulations to run.Where can I get help?


Using condor an introduction condor week 2008

While sharing a beverage with some colleagues, she shares her problem. Somebody asks “Have you tried Condor? It’s free.”


Getting condor

Getting Condor

  • Available as a free download from

    http://www.cs.wisc.edu/condor

  • Download Condor for your operating system

    • Available for most UNIX (including Linux and Apple’s OS/X) platforms

    • Also for Windows XP / 2003 / Vista


Condor releases

Condor Releases

  • Stable / Developer Releases

    • Version numbering scheme similar to that of the (pre 2.6) Linux kernels …

    • Major.minor.release

      • Minor is even (a.b.c): Stable

        • Examples: 6.6.3, 6.8.4, 6.8.5

        • Very stable, mostly bug fixes

      • Minor is odd (a.b.c): Developer

        • New features, may have some bugs

        • Examples: 6.7.11, 6.9.1, 6.9.2


Frieda installs a personal condor on her machine

Frieda Installs a “Personal Condor” on her machine…

  • What do we mean by a “Personal” Condor?

    • Condor on your own workstation

    • No root / administrator access required

    • No system administrator intervention needed

  • After installation, Frieda submits her jobs to her Personal Condor…


Using condor an introduction condor week 2008

personal

Condor

your

workstation

600 Condor

jobs


Personal condor what s the benefit of a condor pool with just one user and one machine

Personal Condor?!What’s the benefit of a Condor “Pool” with just one user and one machine?


Your personal condor will

Your Personal Condor will ...

  • Keep an eye on your jobs and will keep you posted on their progress

  • Implement your policy on the execution order of the jobs

  • Keep a log of your job activities

  • Add fault tolerance to your jobs

  • Implement your policy on when the jobs can run on your workstation


Definitions

Definitions

  • Job

    • The Condor representation of your work

  • Machine

    • The Condor representation of computers and that can perform the work

  • Match Making

    • Matching a job with a machine “Resource”


Using condor an introduction condor week 2008

Job

Jobs state their requirements and preferences:

I need a Linux/x86 platform

I want the machine with the most memory

I prefer a machine in the chemistry department


Machine

Machine

Machines state their requirements and preferences:

Run jobs only when there is no keyboard activity

I prefer to run Frieda’s jobs

I am a machine in the physics department

Never run jobs belonging to Dr. Smith


The magic of matchmaking

The Magic of Matchmaking

  • Jobs and machines state their requirements and preferences

  • Condor matches jobs with machines

    based on requirements and preferences


Getting started submitting jobs to condor

Getting Started:Submitting Jobs to Condor

  • Overview:

    • Choose a “Universe” for your job

    • Make your job “batch-ready”

    • Create a submit description file

    • Run condor_submitto put your job in the queue


1 choose the universe

1. Choose the “Universe”

  • Controls how Condor handles jobs

  • Choices include:

    • Vanilla

    • Standard

    • Grid

    • Java

    • Parallel

    • VM


Using the vanilla universe

Using the Vanilla Universe

  • The Vanilla Universe:

    • Allows running almost any “serial” job

    • Provides automatic file transfer, etc.

    • Like vanilla ice cream

      • Can be used in just about any situation


2 make your job batch ready

2. Make your job batch-ready

Must be able to run in the background

  • No interactive input

  • No GUI/window clicks

  • No music ;^)


Make your job batch ready continued

Make your job batch-ready (continued)…

  • Job can still use STDIN, STDOUT, and STDERR (the keyboard and the screen), but files are used for these instead of the actual devices

  • Similar to UNIX shell:

    • $ ./myprogram <input.txt >output.txt


3 create a submit description file

3. Create a Submit Description File

  • A plain ASCII text file

  • Condor does not care about file extensions

  • Tells Condor about your job:

    • Which executable, universe, input, output and error files to use, command-line arguments, environment variables, any special requirements or preferences (more on this later)

  • Can describe many jobs at once (a “cluster”), each with different input, arguments, output, etc.


Simple submit description file

Simple Submit Description File

# Simple condor_submit input file

# (Lines beginning with # are comments)

# NOTE: the words on the left side are not

# case sensitive, but filenames are!

Universe = vanilla

Executable = my_job

Output = output.txt

Queue


4 run condor submit

4. Run condor_submit

  • You give condor_submit the name of the submit file you have created:

    • condor_submit my_job.submit

  • condor_submit:

    • Parses the submit file, checks for errors

    • Creates a “ClassAd” that describes your job(s)

    • Puts job(s) in the Job Queue


Classad

ClassAd ?

  • Condor’s internal data representation

    • Similar to classified ads (as the name implies)

    • Represent an object & its attributes

      • Usually many attributes

    • Can also describe what an object matches with


Classad details

ClassAd Details

  • ClassAds can contain a lot of details

    • The job’s executable is analysis.exe

    • The machine’s load average is 5.6

  • ClassAds can specify requirements

    • I require a machine with Linux

  • ClassAds can specify preferences

    • This machine prefers to run jobs from the physics group


Classad details continued

ClassAd Details (continued)

  • ClassAds are:

    • semi-structured

    • user-extensible

    • schema-free

    • Attribute = Expression


Classad example

Example:

MyType = "Job"

TargetType = "Machine"

ClusterId = 1377

Owner = "roy"

Cmd = "sim.exe"

Requirements =

(Arch == "INTEL")

&& (OpSys == "LINUX")

&& (Disk >= DiskUsage)

&& ((Memory * 1024)>=ImageSize)

String

Number

Boolean

ClassAd Example


The dog

ClassAd

Type = “Dog”

Color = “Brown”

Price = 12

ClassAd for the “Job”

. . .

Requirements =

(type == “Dog”) &&

(color == “Brown”) &&

(price <= 15)

. . .

The Dog


The job queue

The Job Queue

  • condor_submit sends your job’s ClassAd(s) to the schedd

  • The schedd (more details later):

    • Manages the local job queue

    • Stores the job in the job queue

      • Atomic operation, two-phase commit

      • “Like money in the bank”

  • View the queue with condor_q


Example condor submit and condor q

Examplecondor_submit and condor_q

% condor_submit my_job.submit

Submitting job(s).

1 job(s) submitted to cluster 1.

% condor_q

-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> :

ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD

1.0 frieda 6/16 06:52 0+00:00:00 I 0 0.0 my_job

1 jobs; 1 idle, 0 running, 0 held

%


Input output error files

Input, output & error files

  • Controlled by submit file settings

  • You can define the job’s standard input, standard output and standard error:

    • Read job’s standard input from “input_file”:

      • Input= input_file

      • Shell equivalent: program <input_file

    • Write job’s standard ouput to “output_file”:

      • Output= output_file

      • Shell equivalent: program >output_file

    • Write job’s standard error to “error_file”:

      • Error= error_file

      • Shell equivalent: program 2>error_file


Email about your job

Email about your job

  • Condor sends email about job events to the submitting user

  • Specify “notification” in your submit file to control which events:

    Notification= complete

    Notification= never

    Notification= error

    Notification= always

Default


Feedback on your job

Feedback on your job

  • Create a log of job events

  • Add to submit description file:

    log = sim.log

  • Becomes the Life Story of a Job

    • Shows all events in the life of a job

    • Always have a log file


Sample condor user log

Sample Condor User Log

000 (0001.000.000) 05/25 19:10:03 Job submitted from host: <128.105.146.14:1816>

...

001 (0001.000.000) 05/25 19:12:17 Job executing on host: <128.105.146.14:1026>

...

005 (0001.000.000) 05/25 19:13:06 Job terminated.

(1) Normal termination (return value 0)

...


Example submit description file with logging

Example Submit Description File With Logging

# Example condor_submit input file

# (Lines beginning with # are comments)

# NOTE: the words on the left side are not

# case sensitive, but filenames are!

Universe = vanilla

Executable = /home/frieda/condor/my_job.condor

Log = my_job.log·Job log (from Condor)

Input = my_job.in·Program’s standard input

Output = my_job.out ·Program’s standard output

Error = my_job.err·Program’s standard error

Arguments = -a1 -a2·Command line arguments

InitialDir = /home/frieda/condor/run

Queue


Clusters and processes

“Clusters” and “Processes”

  • If your submit file describes multiple jobs, we call this a “cluster”

  • Each cluster has a unique “cluster number”

  • Each job in a cluster is called a “process”

    • Process numbers always start at zero

  • A Condor “Job ID” is the cluster number, a period, and the process number (i.e. 2.1)

    • A cluster can have a single process

      • Job ID = 20.0 ·Cluster 20, process 0

    • Or, a cluster can have more than one process

      • Job ID: 21.0, 21.1, 21.2·Cluster 21, process 0, 1, 2


Submit file for a cluster

Submit File for a Cluster

# Example submit file for a cluster of 2 jobs

# with separate input, output, error and log files

Universe = vanilla

Executable = my_job

Arguments = -x 0

log = my_job_0.log

Input = my_job_0.in

Output = my_job_0.out

Error = my_job_0.err

Queue·Job 2.0 (cluster 2, process 0)

Arguments = -x 1

log = my_job_1.log

Input = my_job_1.in

Output = my_job_1.out

Error = my_job_1.err

Queue·Job 2.1 (cluster 2, process 1)


Submitting the job

Submitting The Job

% condor_submit my_job.submit-file

Submitting job(s).

2 job(s) submitted to cluster 2.

% condor_q

-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> :

ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD

1.0 frieda 4/15 06:52 0+00:02:11 R 0 0.0 my_job –a1 –a2

2.0 frieda 4/15 06:56 0+00:00:00 I 0 0.0 my_job –x 0

2.1 frieda 4/15 06:56 0+00:00:00 I 0 0.0 my_job –x 1

3 jobs; 2 idle, 1 running, 0 held

%


Back to our 600 jobs

Back to our 600 jobs…

  • We could put all input, output, error & log files in the one directory

    • One of each type for each job

    • That’d be 2400 files (4 files × 600 jobs)

    • Difficult to sort through

  • Better: Create a subdirectory for each run


Organize your files and directories for big runs

Organize your files and directories for big runs

  • Create subdirectories for each “run”

    • run_0, run_1, … run_599

  • Create input files in each of these

    • run_0/simulation.in

    • run_1/simulation.in

    • run_599/simulation.in

  • The output, error & log files for each job will be created by Condor from your job’s output


Using condor an introduction condor week 2008

simulation.in

simulation.out

simulation.err

simulation.log

simulation.in

simulation.out

simulation.err

simulation.log

Frieda’s simulation directory

sim.exe

sim.sub

run_0

run_599


Submit description file for 600 jobs

Submit Description File for 600 Jobs

# Cluster of 600 jobs with different directories

Universe = vanilla

Executable = sim

Log = simulation.log

...

Arguments = -x 0

InitialDir = run_0·Log, input, output & error files -> run_0

Queue ·Job 3.0 (Cluster 3, Process 0)

Arguments = -x 1

InitialDir = run_1·Log, input, output & error files -> run_1

Queue ·Job 3.1 (Cluster 3, Process 1)

·Do this 598 more times…………


Submit file for a big cluster of jobs

Submit File for a BigCluster of Jobs

  • We just submitted 1 cluster with 600 processes

  • All the input/output files will be in different directories

  • The submit file is pretty unwieldy (over 1200 lines)

  • Isn’t there a better way?


Submit file for a big cluster of jobs the better way 1

Submit File for a BigCluster of Jobs (the better way) #1

  • We can queue all 600 in 1 “Queue” command

    • Queue 600

  • Condor provides $(Process) and $(Cluster)

    • $(Process) will be expanded to the process number for each job in the cluster

      • 0, 1, … 599

    • $(Cluster) will be expanded to the cluster number

      • Will be 4 for all jobs in this cluster


Submit file for a big cluster of jobs the better way 2

Submit File for a BigCluster of Jobs (the better way) #2

  • The initial directory for each job can be specified using $(Process)

    • InitialDir = run_$(Process)

    • Condor will expand these to “run_0”, “run_1”, … “run_599” directories

  • Similarly, arguments can be variable

    • Arguments = -x $(Process)

    • Condor will expand these to “-x 0”, “-x 1”, … “-x 599”


Better submit file for 600 jobs

Better Submit File for 600 Jobs

# Example condor_submit input file that defines

# a cluster of 600 jobs with different directories

Universe = vanilla

Executable = my_job

Log = my_job.log

Input = my_job.in

Output = my_job.out

Error = my_job.err

Arguments = –x $(Process)·–x 0, -x 1, … -x 599

InitialDir = run_$(Process)·run_0 … run_599

Queue 600·Jobs 4.0 … 4.599


Now we submit it

Now, we submit it…

$ condor_submit my_job.submit

Submitting job(s) ...............................................................................................................................................................................................................................................................

Logging submit event(s) ...............................................................................................................................................................................................................................................................

600 job(s) submitted to cluster 4.


And check the queue

And, Check the queue

$condor_q

-- Submitter: x.cs.wisc.edu : <128.105.121.53:510> : x.cs.wisc.edu

ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD

4.0 frieda 4/20 12:08 0+00:00:05 R 0 9.8 my_job -arg1 –x 0

4.1 frieda 4/20 12:08 0+00:00:03 I 0 9.8 my_job -arg1 –x 1

4.2 frieda 4/20 12:08 0+00:00:01 I 0 9.8 my_job -arg1 –x 2

4.3 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 3

...

4.598 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 598

4.599 frieda 4/20 12:08 0+00:00:00 I 0 9.8 my_job -arg1 –x 599

600 jobs; 599 idle, 1 running, 0 held


Removing jobs

Removing jobs

  • If you want to remove a job from the Condor queue, you use condor_rm

  • You can only remove jobs that you own

  • Privileged user can remove any jobs

    • “root” on UNIX

    • “administrator” on Windows


Removing jobs continued

Removing jobs (continued)

  • Remove an entire cluster:

    • condor_rm 4·Removes the whole cluster

  • Remove a specific job from a cluster:

    • condor_rm 4.0·Removes a single job

  • Or, remove all of your jobs with “-a”

    • condor_rm -a·Removes all jobs / clusters


Using condor an introduction condor week 2008

Good News

(Boss Fat Cat)

The Boss says Frieda can add her co-workers’ desktop machines into her Condor pool as well…but only if they can also submit jobs.


Adding nodes

Adding nodes

  • Frieda installs Condor on the desktop machines, and configures them with her machine as the central manager

    • The central manager:

      • Central repository for the whole pool

      • Performs job / machine matching, etc.

  • These are “non-dedicated” nodes, meaning that they can't always run Condor jobs


Using condor an introduction condor week 2008

personal

Condor

Condor Pool

your

workstation

600 Condor

jobs


Condor status

condor_status

% condor_status

Name OpSys Arch State Activ LoadAv Mem ActvtyTime

antipholus.cs LINUX INTEL Unclaimed Idle 0.020 511 0+02:28:42

coral.cs.wisc LINUX INTEL Claimed Busy 0.990 511 0+01:27:21

doc.cs.wisc.e LINUX INTEL Unclaimed Idle 0.260 511 0+00:20:04

dsonokwa.cs.w LINUX INTEL Claimed Busy 0.810 511 0+00:01:45

ferdinand.cs. LINUX INTEL Claimed Suspe 1.130 511 0+00:00:55

[email protected] LINUX INTEL Unclaimed Idle 0.000 255 0+01:03:28

[email protected] LINUX INTEL Unclaimed Idle 0.190 255 0+01:03:29


How can my jobs access their data files

How can my jobs access their data files?


Access to data in condor

Access to Data in Condor

  • Use shared filesystem if available

  • No shared filesystem?

    • Condor can transfer files

      • Can automatically send back changed files

      • Atomic transfer of multiple files

      • Can be encrypted over the wire

    • Remote I/O Socket

    • Standard Universe can use remote system calls (more on this later)


Condor file transfer

Universe = vanilla

Executable = my_job

Log = my_job.log

ShouldTransferFiles = IF_NEEDED

Transfer_input_files = dataset.$(Process), common.data

Transfer_output_files = TheAnswer.dat

Queue 600

Condor File Transfer

  • ShouldTransferFiles = YES

    • Always transfer files to execution site

  • ShouldTransferFiles = NO

    • Rely on a shared filesystem

  • ShouldTransferFiles = IF_NEEDED

    • Will automatically transfer the files if the submit and execute machine are not in the same FileSystemDomain


We always want more

We Always Want More

Condor is managing and running our jobs, but

  • Our CPU requirements are greater than our resources

  • Jobs are preempted more often than we like


Happy day frieda s organization purchased a dedicated cluster

Happy Day! Frieda’s organization purchased a Dedicated Cluster!

  • Frieda Installs Condor on all the dedicated Cluster nodes

  • Frieda also adds a dedicated central manager

  • She configures her entire pool with this new host as the central manager…


Frieda s condor pool

Frieda’s Condor Pool

600 Condor

jobs

Dedicated Cluster

Condor Pool

With the additional resources, Frieda and her co-workers can get their jobs completed even faster.


Another universe

Another Universe


Frieda submits some mpi jobs

Frieda submits some MPI jobs

universe = parallel

executable = mp1script

arguments = my_mpich_linked_executable arg1 arg2

machine_count = 4

should_transfer_files = yes

when_to_transfer_output = on_exit

transfer_input_files = my_mpich_linked_executable

queue


What condor daemons are running on my machine and what do they do

What Condor Daemons are running on my machine, and what do they do?


Condor master

condor_master

  • Starts up all other Condor daemons

  • If there are any problems and a daemon exits, it restarts the daemon and sends email to the administrator

  • Acts as the server for many Condor remote administration commands:

    • condor_reconfig, condor_restart, condor_off, condor_on, condor_config_val, etc.


Condor daemon layout

Personal Condor / Central Manager

negotiator

startd

schedd

collector

= Process Spawned

Condor Daemon Layout

Master


Central manager condor collector

Central Manager:condor_collector

  • Central manager: central repository and match maker for whole pool

  • Collects information from all other Condor daemons in the pool

    • “Directory Service” / Database for a Condor pool

  • Each daemon sends a periodic update called a “ClassAd” to the collector

  • Services queries for information:

    • Queries from other Condor daemons

    • Queries from users (condor_status)

  • Only on the Central Manager

  • At least one collector per pool


Condor pool layout collector

= Process Spawned

Central Manager

Condor Pool Layout: Collector

= ClassAd

Communication

Pathway

Master

Collector


Central manager condor negotiator

Central Manager:condor_negotiator

  • Performs “matchmaking” in Condor

  • Each “Negotiation Cycle” (typically 5 minutes):

    • Gets information from the collector about all available machines and all idle jobs

    • Tries to match jobs with machines that will serve them

    • Both the job and the machine must satisfy each other’s requirements

  • Only one negotiator per pool

  • Only on the Central Manager


Condor pool layout negotiator

= Process Spawned

Central Manager

Condor Pool Layout: Negotiator

= ClassAd

Communication

Pathway

Master

negotiator

Collector


Execute hosts condor startd

Execute Hosts:condor_startd

  • Execute host: machines that run user jobs

  • Represents a machine to the Condor system

  • Responsible for starting, suspending, and stopping jobs

  • Enforces the wishes of the machine owner (the owner’s “policy”… more on this in the administrator’s tutorial)

  • Creates a “starter” for each running job

  • One startd runs on each execute node


Condor pool layout startd

Cluster Node

= Process Spawned

Central Manager

Master

startd

Cluster Node

Master

startd

Condor Pool Layout: startd

= ClassAd

Communication

Pathway

Master

negotiator

Collector


Submit hosts condor schedd

Submit Hosts:condor_schedd

  • Submit hosts: machines that users can submit jobs on

  • Maintains the persistent queue of jobs

  • Responsible for contacting available machines and sending them jobs

  • Services user commands which manipulate the job queue:

    • condor_submit,condor_rm, condor_q, condor_hold, condor_release, condor_prio, …

  • Creates a “shadow” for each running job

  • One schedd runs on each submit host


Condor pool layout schedd

Cluster Node

= Process Spawned

Central Manager

Master

startd

Cluster Node

Master

Desktop

startd

Desktop

Condor Pool Layout: schedd

= ClassAd

Communication

Pathway

Master

negotiator

negotiator

schedd

Collector

Master

Master

startd

startd

schedd

schedd


Condor pool layout master

Cluster Node

= Process Spawned

Central Manager

Master

Master

Master

negotiator

startd

schedd

schedd

Cluster Node

Master

Master

startd

Desktop

Desktop

Master

Master

Condor Pool Layout: master

= ClassAd

Communication

Pathway

Master

negotiator

Collector

Master

Master

startd

startd

schedd

schedd


Now what

Now what?

  • Some of the machines in the pool can’t run my jobs

    • Not enough RAM

    • Not enough scratch disk space

    • Required software not installed

    • Etc.


Specify requirements

Universe = vanilla

Executable = my_job

Log = my_job.log

InitialDir = run_$(Process)

Requirements = Memory >= 256 && Disk > 10000

Queue 600

Specify Requirements

  • An expression (syntax similar to C or Java)

  • Must evaluate to True for a match to be made


Advanced requirements

Universe = vanilla

Executable = $$(MyProgPath)

Log = my_job.log

InitialDir = run_$(Process)

Requirements = Memory >= 256 && Disk > 10000 \

&& ( MyProgPath =!= UNDEFINED) )

Queue 600

Advanced Requirements

  • Requirements can match custom attributes in your Machine Ad

    • Can be added by hand to each machine

    • Or, automatically using the “Hawkeye” mechanism


And specify rank

Universe = vanilla

Executable = my_job

Log = my_job.log

Arguments = -arg1 –arg2

InitialDir = run_$(Process)

Requirements = Memory >= 256 && Disk > 10000

Rank = (KFLOPS*10000) + Memory

Queue 600

And, Specify Rank

  • All matches which meet the requirements can be sorted by preference with a Rank expression.

  • Higher the Rank, the better the match


My jobs aren t running

My jobs aren’t running!!


Check the queue

Check the queue

  • Check the queue with condor_q:

    bash-2.05a$ condor_q

    -- Submitter: x.cs.wisc.edu : <128.105.121.53:510> :x.cs.wisc.edu

    ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD

    5.0 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 0

    5.1 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 1

    5.2 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 2

    5.3 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 3

    5.4 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 4

    5.5 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 5

    5.6 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 6

    5.7 frieda 4/20 12:23 0+00:00:00 I 0 9.8 my_job -arg1 –n 7

    6.0 frieda 4/20 13:22 0+00:00:00 H 0 9.8 my_job -arg1 –arg2

    8 jobs; 8 idle, 0 running, 1 held


Look at jobs on hold

Look at jobs on hold

%condor_q –hold

-- Submiter: x.cs.wisc.edu : <128.105.121.53:510> :x.cs.wisc.edu

ID OWNER HELD_SINCE HOLD_REASON

6.0 frieda 4/20 13:23 Error from starter on skywalker.cs.wisc.edu

9 jobs; 8 idle, 0 running, 1 held

Or, See full details for a job

% condor_q –l 6.0


Check machine status

Check machine status

  • Verify that there are idle machines with condor_status:

    bash-2.05a$ condor_status

    Name OpSys Arch State Activity LoadAv Mem ActvtyTime

    [email protected] LINUX INTEL Claimed Busy 0.000 501 0+00:00:20

    [email protected] LINUX INTEL Claimed Busy 0.000 501 0+00:00:19

    [email protected] LINUX INTEL Claimed Busy 0.040 501 0+00:00:17

    [email protected] LINUX INTEL Claimed Busy 0.000 501 0+00:00:05

    Total Owner Claimed Unclaimed Matched Preempting

    INTEL/LINUX 4 0 4 0 0 0

    Total 4 0 4 0 0 0


Look in job log

Look in Job Log

  • Look in your job log for clues:

    bash-2.05a$ cat my_job.log

    000 (031.000.000) 04/20 14:47:31 Job submitted from host: <128.105.121.53:48740>

    ...

    007 (031.000.000) 04/20 15:02:00 Shadow exception!

    Error from starter on gig06.stat.wisc.edu: Failed to open '/scratch.1/frieda/workspace/v67/condor-test/test3/run_0/my_job.in' as standard input: No such file or directory (errno 2)

    0 - Run Bytes Sent By Job

    0 - Run Bytes Received By Job

    ...


Still not running exercise a little patience

Still not running?Exercise a little patience

  • On a busy pool, it can take a while to match and start your jobs

  • Wait at least a negotiation cycle or two (typically a few minutes)


Look to condor q for help condor q analyze

Look to condor_q for help:condor_q -analyze

bash-2.05a$ condor_q -ana 29

---

029.000: Run analysis summary. Of 1243 machines,

1243 are rejected by your job's requirements

0 are available to run your job

WARNING: Be advised:

No resources matched request's constraints

Check the Requirements expression below:

Requirements = ((Memory > 8192)) && (Arch == "INTEL") && (OpSys == "LINUX") && (Disk >= DiskUsage) && (TARGET.FileSystemDomain == MY.FileSystemDomain)


Better analysis linux only condor q better analyze

Better analysis (Linux only):condor_q –better-analyze

bash-2.05a$ condor_q -better-ana 29

The Requirements expression for your job is:

( ( target.Memory > 8192 ) ) && ( target.Arch == "INTEL" ) &&

( target.OpSys == "LINUX" ) && ( target.Disk >= DiskUsage ) &&

( TARGET.FileSystemDomain == MY.FileSystemDomain )

Condition Machines Matched Suggestion

--------- ---------------- ----------

1 ( ( target.Memory > 8192 ) ) 0 MODIFY TO 4000

2 ( TARGET.FileSystemDomain == "cs.wisc.edu" )584

3 ( target.Arch == "INTEL" ) 1078

4 ( target.OpSys == "LINUX" ) 1100

5 ( target.Disk >= 13 ) 1243


Learn about available resources

Learn about available resources:

bash-2.05a$ condor_status –const 'Memory > 8192'

(no output means no matches)

bash-2.05a$ condor_status -const 'Memory > 4096'

Name OpSys Arch State Activ LoadAv Mem ActvtyTime

[email protected] LINUX X86_64 Unclaimed Idle 0.000 5980 1+05:35:05

[email protected] LINUX X86_64 Unclaimed Idle 0.000 5980 13+05:37:03

[email protected] LINUX X86_64 Unclaimed Idle 0.000 7988 1+06:00:05

[email protected] LINUX X86_64 Unclaimed Idle 0.000 7988 13+06:03:47

Total Owner Claimed Unclaimed Matched Preempting

X86_64/LINUX 4 0 0 4 0 0

Total 4 0 0 4 0 0


Job policy expressions

Job Policy Expressions

  • User can supply job policy expressions in the submit file.

  • Can be used to describe a successful run.

    on_exit_remove = <expression>

    on_exit_hold = <expression>

    periodic_remove = <expression>

    periodic_hold = <expression>


Job policy examples

Job Policy Examples

  • Do not remove if exits with a signal:

    • on_exit_remove = ExitBySignal == False

  • Place on hold if exits with nonzero status or ran for less than an hour:

    • on_exit_hold = ( (ExitBySignal==False) && (ExitSignal != 0) ) || ( (ServerStartTime - JobStartDate) < 3600)

  • Place on hold if job has spent more than 50% of its time suspended:

    • periodic_hold = CumulativeSuspensionTime > (RemoteWallClockTime / 2.0)


Insert classad attributes

Insert ClassAd attributes

  • Special purpose usage

  • In the submit description file, introduce an attribute for the job

    +Department = “biochemistry”

    causes the ClassAd to contain

    Department = “biochemistry”


We ve seen how condor can

We’ve seen how Condor can:

Keep an eye on your jobs and will keep you posted on their progress

Implement your policy on the execution order of the jobs

Keep a log of your job activities


Another universe1

Another Universe


My new jobs run for 20 days

My new jobs run for 20 days…

  • What happens when a job is forced off it’s CPU?

    • Preempted by higher priority user or job

    • Vacated because of user activity

  • How can I add fault tolerance to my jobs?


Condor s standard universe to the rescue

Condor’s Standard Universe to the rescue!

  • Support for transparent process checkpoint and restart

  • Remote system calls (remote I/O)

    • Your job can read / write files as if they were local


Remote system calls in the standard universe

Remote System Calls inthe Standard Universe

  • I/O system calls are trapped and sent back to the submit machine

    Examples: open a file, write to a file

  • No source code changes typically required

  • Programming language independent


Process checkpointing in the standard universe

Process Checkpointing in theStandard Universe

  • Condor’s process checkpointing provides a mechanism to automatically save the state of a job

  • The process can then be restarted from right where it was checkpointed

    • After preemption, crash, etc.


Checkpointing process starts

Checkpointing:Process Starts

checkpoint: the entire state of a program, saved in a file

  • CPU registers, memory image, I/O

time


Checkpointing process checkpointed

Checkpointing:Process Checkpointed

time

1

2

3


Checkpointing process killed

Checkpointing:Process Killed

time

Killed!

3

3


Checkpointing process resumed

Checkpointing:Process Resumed

goodput

goodput

badput

time

3

3


When will condor checkpoint your job

When will Condor checkpoint your job?

  • Periodically, if desired

    • For fault tolerance

  • When your job is preempted by a higher priority job

  • When your job is vacated because the execution machine becomes busy

  • When you explicitly run condor_checkpoint, condor_vacate, condor_off or condor_restart command


Making the standard universe work

Making the Standard Universe Work

  • The job must be relinked with Condor’s standard universe support library

  • To relink, place condor_compile in front of the command used to link the job:

% condor_compile gcc -o myjob myjob.c

- OR -

% condor_compile f77 -o myjob filea.f fileb.f

- OR -

% condor_compile make –f MyMakefile


Limitations of the standard universe

Limitations of the Standard Universe

  • Condor’s checkpointing is not at the kernel level.

    • Standard Universe the job may not:

      • Fork()

      • Use kernel threads

      • Use some forms of IPC, such as pipes and shared memory

  • Must have access to source code to relink

  • Many typical scientific jobs are OK


Connecting condors

Connecting Condors

  • Frieda knows people with their own Condor pools, and gets permission to use their computing resources…

  • How can Condor help her do this?


Connect condors with flocking

Connect Condorswith Flocking

  • Frieda configures her Condor pool to “flock” to her friend’s pool.

  • Flocking is a Condor-specific technology.


Frieda s condor pool1

Frieda’s Condor Pool

600 Condor

jobs

Friendly Condor Pool

Condor Pool


Frieda meets the grid

Frieda meets The Grid

  • Frieda also has access to grid resources she wants to use

    • She has certificates and access to Globus or other resources at remote institutions

  • But Frieda wants Condor’s queue management features for her jobs!

  • She installs Condor so she can submit “Grid Universe” jobs to Condor


Grid universe

“Grid” Universe

  • All handled in your submit file

  • Supports a number of “back end” types:

    • Globus: GT2, GT4

    • NorduGrid

    • UNICORE

    • Condor

    • PBS

    • LSF

    • EC2

    • NQS


Grid universe globus 2

Grid Universe & Globus 2

  • Used for a Globus GT2 back-end

    • “Condor-G”

  • Format:

    Grid_Resource = gt2 Head-Node

    Globus_rsl = <RSL-String>

  • Example:

    Universe = grid

    Grid_Resource = gt2 beak.cs.wisc.edu/jobmanager

    Globus_rsl = (queue=long)(project=atom-smasher)


Grid universe globus 4

Grid Universe & Globus 4

  • Used for a Globus GT4 back-end

  • Format:

    Grid_Resource = gt4 <Head-Node> <Scheduler-Type>

    Globus_XML = <XML-String>

  • Example:

    Universe = grid

    Grid_Resource = gt4 beak.cs.wisc.edu Condor

    Globus_xml = <queue>long</queue><project>atom-smasher</project>


Grid universe condor

Grid Universe & Condor

  • Used for a Condor back-end

    • “Condor-C”

  • Format:

    Grid_Resource = condor <Schedd-Name> <Collector-Name>

    Remote_<param> = <value>

    • “Remote_” part is stripped off

  • Example:

    Universe = grid

    Grid_Resource = condor beak condor.cs.wisc.edu

    Remote_Universe = standard


Grid universe nordugrid

Grid Universe & NorduGrid

  • Used for a NorduGrid back-end

    Grid_Resource = nordugrid <Host-Name>

  • Example:

    Universe = grid

    Grid_Resource = nordugrid ngrid.cs.wisc.edu


Grid universe unicore

Grid Universe & UNICORE

  • Used for a UNICORE back-end

  • Format:

    Grid_Resource = unicore <USite> <VSite>

  • Example:

    Universe = grid

    Grid_Resource = unicore uhost.cs.wisc.edu vhost


Grid universe pbs

Grid Universe & PBS

  • Used for a PBS back-end

  • Format:

    Grid_Resource = pbs

  • Example:

    Universe = grid

    Grid_Resource = pbs


Grid universe lsf

Grid Universe & LSF

  • Used for a LSF back-end

  • Format:

    Grid_Resource = lsf

  • Example:

    Universe = grid

    Grid_Resource = lsf


Credential management

Credential Management

  • Condor will do The Right Thing™ with your X509 certificate and proxy

  • Override default proxy:

    • X509UserProxy = /home/frieda/other/proxy

  • Proxy may expire before jobs finish executing

    • Condor can use MyProxy to renew your proxy

    • When a new proxy is available, Condor will forward the renewed proxy to the job

    • This works for non-grid jobs, too


My jobs have have dependencies

My jobs have have dependencies…

Can Condor help solve my dependency problems?


Condor universes scheduler and local

Condor Universes:Scheduler and Local

  • Scheduler Universe

    • Plug in a meta-scheduler

    • Developed for DAGMan (more later)

    • Similar to Globus’s fork job manager

  • Local

    • Very similar to vanilla, but jobs run on the local host

    • Has more control over jobs than scheduler universe


Frieda learns dagman

Frieda learns DAGMan

  • Directed Acyclic Graph Manager

  • DAGMan allows you to specify the dependencies between your Condor jobs, so it can manage them automatically for you.

  • (e.g., “Don’t run job “B” until job “A” has completed successfully.”)


What is a dag

Job A

Job B

Job C

Job D

What is a DAG?

  • A DAG is the datastructure used by DAGMan to represent these dependencies.

  • Each job is a “node” in the DAG.

  • Each node can have any number of “parent” or “children” nodes – as long as there are no loops!


Defining a dag

Job A

Job B

Job C

Job D

Defining a DAG

  • A DAG is defined by a .dagfile, listing each of its nodes and their dependencies:

    # diamond.dag

    Job A a.sub

    Job B b.sub

    Job C c.sub

    Job D d.sub

    Parent A Child B C

    Parent B C Child D

  • each node will run the Condor job specified by its accompanying Condor submit file


Submitting a dag

Submitting a DAG

  • To start your DAG, just run condor_submit_dag with your .dag file, and Condor will start a personal DAGMan daemon which to begin running your jobs:

    % condor_submit_dag diamond.dag

  • condor_submit_dag is run by the schedd

    • DAGMan daemon itself is “watched” by Condor, so you don’t have to


Running a dag

A

.dag

File

Condor

Job

Queue

A

B

C

D

DAGMan

Running a DAG

  • DAGMan acts as a “meta-scheduler”, managing the submission of your jobs to Condor based on the DAG dependencies.


Running a dag cont d

A

Condor

Job

Queue

B

B

C

C

D

DAGMan

Running a DAG (cont’d)

  • DAGMan holds & submits jobs to the Condor queue at the appropriate times.


Running a dag cont d1

A

Rescue

File

Condor

Job

Queue

B

X

D

DAGMan

Running a DAG (cont’d)

  • In case of a job failure, DAGMan continues until it can no longer make progress, and then creates a “rescue” file with the current state of the DAG.


Recovering a dag

A

Rescue

File

Condor

Job

Queue

B

C

C

D

DAGMan

Recovering a DAG

  • Once the failed job is ready to be re-run, the rescue file can be used to restore the prior state of the DAG.


Recovering a dag cont d

A

Condor

Job

Queue

B

C

D

D

DAGMan

Recovering a DAG (cont’d)

  • Once that job completes, DAGMan will continue the DAG as if the failure never happened.


Finishing a dag

A

Condor

Job

Queue

B

C

D

DAGMan

Finishing a DAG

  • Once the DAG is complete, the DAGMan job itself is finished, and exits.


Additional dagman features

Additional DAGMan Features

  • Provides other handy features for job management…

    • nodes can have PRE & POST scripts

    • failed nodes can be automatically re-tried a configurable number of times

    • job submission can be “throttled”


General user commands

General User Commands

  • condor_status View Pool Status

  • condor_qView Job Queue

  • condor_submitSubmit new Jobs

  • condor_rmRemove Jobs

  • condor_prioIntra-User Prios

  • condor_historyCompleted Job Info

  • condor_submit_dagSubmit new DAG

  • condor_checkpointForce a checkpoint

  • condor_compileLink Condor library


Condor job universes

Vanilla Universe

Standard Universe

Grid Universe

Scheduler Universe

Local Universe

Virtual Machine Universe

Java Universe

Parallel Universe

MPICH-1

MPICH-2

LAM

Condor Job Universes


Why have a special universe for java jobs

Why have a special Universe for Java jobs?

  • Java Universe provides more than just inserting “java” at the start of the execute line of a vanilla job:

    • Knows which machines have a JVM installed

    • Knows the location, version, and performance of JVM on each machine

    • Knows about jar files, etc.

    • Provides more information about Java job completion than just JVM exit code

      • Program runs in a Java wrapper, allowing Condor to report Java exceptions, etc.


Universe java job

Universe Java Job

  • Example Java Universe Submit file:

    Universe = java

    Executable = Main.class

    jar_files = MyLibrary.jar

    Input = infile

    Output = outfile

    Arguments = Main 1 2 3

    Queue


Java support cont

Java support, cont.

bash-2.05a$ condor_status –java

Name JavaVendor Ver State Actv LoadAv Mem

abulafia.cs Sun Microsy 1.5.0_ Claimed Busy 0.180 503

acme.cs.wis Sun Microsy 1.5.0_ Unclaimed Idle 0.000 503

adelie01.cs Sun Microsy 1.5.0_ Claimed Busy 0.000 1002

adelie02.cs Sun Microsy 1.5.0_ Claimed Busy 0.000 1002

Total Owner Claimed Unclaimed Matched Preempting

INTEL/LINUX 965 179 516 250 20 0

INTEL/WINNT50 102 6 65 31 0 0

SUN4u/SOLARIS28 1 0 0 1 0 0

X86_64/LINUX 128 2 106 20 0 0

Total 1196 187 687 302 20 0


Frieda wants condor features on remote resources

Frieda wants Condor features on remote resources

  • She wants to run standard universe jobs on Grid-managed resources

    • For matchmaking and dynamic scheduling of jobs

    • For job checkpointing and migration

    • For remote system calls


Condor glidein

Condor GlideIn

  • Frieda can use the Grid Universe to run Condor daemons on Grid resources

  • When the resources run these GlideIn jobs, they will temporarily join her Condor Pool

  • She can then submit Standard, Vanilla, PVM, or MPI Universe jobs and they will be matched and run on the remote resources

  • Currently only supports Globus GT2

    • We hope to fix this limitation


Using condor an introduction condor week 2008

personal

Condor

Globus Grid

your

workstation

600 Condor

jobs

LSF

PBS

glide-in jobs

Condor

Condor Pool

Friendly Condor Pool


Glidein concerns

GlideIn Concerns

  • What if the remote resource kills my GlideIn job?

    • That resource will disappear from your pool and your jobs will be rescheduled on other machines

    • Standard universe jobs will resume from their last checkpoint like usual

  • What if all my jobs are completed before a GlideIn job runs?

    • If a GlideIn Condor daemon is not matched with a job in 10 minutes, it terminates, freeing the resource


In review

In Review

With Condor’s help, Frieda can:

  • Manage her compute job workload

  • Access local machines

  • Access remote Condor Pools via flocking

  • Access remote compute resources on the Grid via “Grid Universe” jobs

  • Carve out her own personal Condor Pool from the Grid with GlideIn technology


Administrator commands

Administrator Commands

  • condor_vacateLeave a machine now

  • condor_onStart Condor

  • condor_offStop Condor

  • condor_reconfigReconfig on-the-fly

  • condor_config_valView/set config

  • condor_userprioUser Priorities

  • condor_statsView detailed usage accounting stats


My boss wants to watch what condor is doing

My boss wants to watch what Condor is doing


Use condorview

Use CondorView!

  • Provides visual graphs of current and past utilization

  • Data is derived from Condor's own accounting statistics

  • Interactive Java applet

  • Quickly and easily view:

    • How much Condor is being used

    • How many cycles are being delivered

    • Who is using them

    • Utilization by machine platform or by user


Condorview usage graph

CondorView Usage Graph


I could also talk lots about

I could also talk lots about…

  • GCB: Living with firewalls & private networks

  • Federated Grids/Clusters

  • APIs and Portals

  • MW

  • Database Support (Quill)

  • High Availability Fail-over

  • Compute On-Demand (COD)

  • Dynamic Pool Creation (“Glide-in”)

  • Role-based prioritization and accounting

  • Strong security, incl privilege separation

  • Data movement scheduling in workflows


Thank you

Thank you!

Check us out on the Web:

http://www.condorproject.org

Email:

[email protected]


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