Managing a Job¶
This section provides a brief summary of what can be done once jobs are submitted. The basic mechanisms for monitoring a job are introduced, but the commands are discussed briefly. You are encouraged to look at the man pages of the commands referred to (located in Command Reference Manual (man pages)) for more information.
When jobs are submitted, HTCondor will attempt to find resources to run the jobs. A list of all those with jobs submitted may be obtained through condor_status with the -submitters option. An example of this would yield output similar to:
% condor_status -submitters Name Machine Running IdleJobs HeldJobs email@example.com bluebird.c 0 11 0 nice-user.condor@cs. cardinal.c 6 504 0 firstname.lastname@example.org finch.cs.w 1 1 0 email@example.com perdita.cs 0 0 5 RunningJobs IdleJobs HeldJobs firstname.lastname@example.org 0 11 0 email@example.com 0 0 5 nice-user.condor@cs. 6 504 0 firstname.lastname@example.org 1 1 0 Total 7 516 5
Checking on the progress of jobs¶
At any time, you can check on the status of your jobs with the condor_q command. This command displays the status of all queued jobs. An example of the output from condor_q is
% condor_q -- Submitter: submit.chtc.wisc.edu : <188.8.131.52:32772> : submit.chtc.wisc.edu ID OWNER SUBMITTED RUN_TIME ST PRI SIZE CMD 711197.0 aragorn 1/15 19:18 0+04:29:33 H 0 0.0 script.sh 894381.0 frodo 3/16 09:06 82+17:08:51 R 0 439.5 elk elk.in 894386.0 frodo 3/16 09:06 82+20:21:28 R 0 219.7 elk elk.in 894388.0 frodo 3/16 09:06 81+17:22:10 R 0 439.5 elk elk.in 1086870.0 gollum 4/27 09:07 0+00:10:14 I 0 7.3 condor_dagman 1086874.0 gollum 4/27 09:08 0+00:00:01 H 0 0.0 RunDC.bat 1297254.0 legolas 5/31 18:05 14+17:40:01 R 0 7.3 condor_dagman 1297255.0 legolas 5/31 18:05 14+17:39:55 R 0 7.3 condor_dagman 1297256.0 legolas 5/31 18:05 14+17:39:55 R 0 7.3 condor_dagman 1297259.0 legolas 5/31 18:05 14+17:39:55 R 0 7.3 condor_dagman 1297261.0 legolas 5/31 18:05 14+17:39:55 R 0 7.3 condor_dagman 1302278.0 legolas 6/4 12:22 1+00:05:37 I 0 390.6 mdrun_1.sh 1304740.0 legolas 6/5 00:14 1+00:03:43 I 0 390.6 mdrun_1.sh 1304967.0 legolas 6/5 05:08 0+00:00:00 I 0 0.0 mdrun_1.sh 14 jobs; 4 idle, 8 running, 2 held
This output contains many columns of information about the queued jobs. The ST column (for status) shows the status of current jobs in the queue:
- The job is currently running.
- The job is idle. It is not running right now, because it is waiting for a machine to become available.
- The job is the hold state. In the hold state, the job will not be scheduled to run until it is released. See the condor_hold and the condor_release manual pages.
The RUN_TIME time reported for a job is the time that has been committed to the job.
Another useful method of tracking the progress of jobs is through the
job event log. The specification of a
log in the submit description
file causes the progress of the job to be logged in a file. Follow the
events by viewing the job event log file. Various events such as
execution commencement, checkpoint, eviction and termination are logged
in the file. Also logged is the time at which the event occurred.
When a job begins to run, HTCondor starts up a condor_shadow process on the submit machine. The shadow process is the mechanism by which the remotely executing jobs can access the environment from which it was submitted, such as input and output files.
It is normal for a machine which has submitted hundreds of jobs to have
hundreds of condor_shadow processes running on the machine. Since the
text segments of all these processes is the same, the load on the submit
machine is usually not significant. If there is degraded performance,
limit the number of jobs that can run simultaneously by reducing the
You can also find all the machines that are running your job through the
For example, to find
all the machines that are running jobs submitted by
% condor_status -constraint 'RemoteUser == "email@example.com"' Name Arch OpSys State Activity LoadAv Mem ActvtyTime alfred.cs. INTEL LINUX Claimed Busy 0.980 64 0+07:10:02 biron.cs.w INTEL LINUX Claimed Busy 1.000 128 0+01:10:00 cambridge. INTEL LINUX Claimed Busy 0.988 64 0+00:15:00 falcons.cs INTEL LINUX Claimed Busy 0.996 32 0+02:05:03 happy.cs.w INTEL LINUX Claimed Busy 0.988 128 0+03:05:00 istat03.st INTEL LINUX Claimed Busy 0.883 64 0+06:45:01 istat04.st INTEL LINUX Claimed Busy 0.988 64 0+00:10:00 istat09.st INTEL LINUX Claimed Busy 0.301 64 0+03:45:00 ...
To find all the machines that are running any job at all, type:
% condor_status -run Name Arch OpSys LoadAv RemoteUser ClientMachine adriana.cs INTEL LINUX 0.980 firstname.lastname@example.org chevre.cs.wisc. alfred.cs. INTEL LINUX 0.980 email@example.com neufchatel.cs.w amul.cs.wi X86_64 LINUX 1.000 nice-user.condor@cs. chevre.cs.wisc. anfrom.cs. X86_64 LINUX 1.023 firstname.lastname@example.org jules.ncsa.uiuc anthrax.cs INTEL LINUX 0.285 email@example.com chevre.cs.wisc. astro.cs.w INTEL LINUX 1.000 nice-user.condor@cs. chevre.cs.wisc. aura.cs.wi X86_64 WINDOWS 0.996 nice-user.condor@cs. chevre.cs.wisc. balder.cs. INTEL WINDOWS 1.000 nice-user.condor@cs. chevre.cs.wisc. bamba.cs.w INTEL LINUX 1.574 firstname.lastname@example.org riola.cs.wisc.e bardolph.c INTEL LINUX 1.000 nice-user.condor@cs. chevre.cs.wisc. ...
Removing a job from the queue¶
A job can be removed from the queue at any time by using the condor_rm command. If the job that is being removed is currently running, the job is killed without a checkpoint, and its queue entry is removed. The following example shows the queue of jobs before and after a job is removed.
% condor_q -- Submitter: froth.cs.wisc.edu : <184.108.40.206:33847> : froth.cs.wisc.edu ID OWNER SUBMITTED CPU_USAGE ST PRI SIZE CMD 125.0 jbasney 4/10 15:35 0+00:00:00 I -10 1.2 hello.remote 132.0 raman 4/11 16:57 0+00:00:00 R 0 1.4 hello 2 jobs; 1 idle, 1 running, 0 held % condor_rm 132.0 Job 132.0 removed. % condor_q -- Submitter: froth.cs.wisc.edu : <220.127.116.11:33847> : froth.cs.wisc.edu ID OWNER SUBMITTED CPU_USAGE ST PRI SIZE CMD 125.0 jbasney 4/10 15:35 0+00:00:00 I -10 1.2 hello.remote 1 jobs; 1 idle, 0 running, 0 held
Placing a job on hold¶
A job in the queue may be placed on hold by running the command condor_hold. A job in the hold state remains in the hold state until later released for execution by the command condor_release.
Use of the condor_hold command causes a hard kill signal to be sent to a currently running job (one in the running state). For a standard universe job, this means that no checkpoint is generated before the job stops running and enters the hold state. When released, this standard universe job continues its execution using the most recent checkpoint available.
Jobs in universes other than the standard universe that are running when placed on hold will start over from the beginning when released.
Changing the priority of jobs¶
In addition to the priorities assigned to each user, HTCondor also provides each user with the capability of assigning priorities to each submitted job. These job priorities are local to each queue and can be any integer value, with higher values meaning better priority.
The default priority of a job is 0, but can be changed using the condor_prio command. For example, to change the priority of a job to -15,
% condor_q raman -- Submitter: froth.cs.wisc.edu : <18.104.22.168:33847> : froth.cs.wisc.edu ID OWNER SUBMITTED CPU_USAGE ST PRI SIZE CMD 126.0 raman 4/11 15:06 0+00:00:00 I 0 0.3 hello 1 jobs; 1 idle, 0 running, 0 held % condor_prio -p -15 126.0 % condor_q raman -- Submitter: froth.cs.wisc.edu : <22.214.171.124:33847> : froth.cs.wisc.edu ID OWNER SUBMITTED CPU_USAGE ST PRI SIZE CMD 126.0 raman 4/11 15:06 0+00:00:00 I -15 0.3 hello 1 jobs; 1 idle, 0 running, 0 held
It is important to note that these job priorities are completely different from the user priorities assigned by HTCondor. Job priorities do not impact user priorities. They are only a mechanism for the user to identify the relative importance of jobs among all the jobs submitted by the user to that specific queue.
Why is the job not running?¶
Users occasionally find that their jobs do not run. There are many possible reasons why a specific job is not running. The following prose attempts to identify some of the potential issues behind why a job is not running.
At the most basic level, the user knows the status of a job by using condor_q to see that the job is not running. By far, the most common reason (to the novice HTCondor job submitter) why the job is not running is that HTCondor has not yet been through its periodic negotiation cycle, in which queued jobs are assigned to machines within the pool and begin their execution. This periodic event occurs by default once every 5 minutes, implying that the user ought to wait a few minutes before searching for reasons why the job is not running.
Further inquiries are dependent on whether the job has never run at all, or has run for at least a little bit.
For jobs that have never run, many problems can be diagnosed by using the -analyze option of the condor_q command. Here is an example; running condor_q ‘s analyzer provided the following information:
$ condor_q -analyze 27497829 -- Submitter: s1.chtc.wisc.edu : <126.96.36.199:9618?sock=5557_e660_3> : s1.chtc.wisc.edu User priority for email@example.com is not available, attempting to analyze without it. --- 27497829.000: Run analysis summary. Of 5257 machines, 5257 are rejected by your job's requirements 0 reject your job because of their own requirements 0 match and are already running your jobs 0 match but are serving other users 0 are available to run your job No successful match recorded. Last failed match: Tue Jun 18 14:36:25 2013 Reason for last match failure: no match found WARNING: Be advised: No resources matched request's constraints The Requirements expression for your job is: ( OpSys == "OSX" ) && ( TARGET.Arch == "X86_64" ) && ( TARGET.Disk >= RequestDisk ) && ( TARGET.Memory >= RequestMemory ) && ( ( TARGET.HasFileTransfer ) || ( TARGET.FileSystemDomain == MY.FileSystemDomain ) ) Suggestions: Condition Machines Matched Suggestion --------- ---------------- ---------- 1 ( target.OpSys == "OSX" ) 0 MODIFY TO "LINUX" 2 ( TARGET.Arch == "X86_64" ) 5190 3 ( TARGET.Disk >= 1 ) 5257 4 ( TARGET.Memory >= ifthenelse(MemoryUsage isnt undefined,MemoryUsage,1) ) 5257 5 ( ( TARGET.HasFileTransfer ) || ( TARGET.FileSystemDomain == "submit-1.chtc.wisc.edu" ) ) 5257
This example also shows that the job does not run because the platform requested, Mac OS X, is not available on any of the machines in the pool. Recall that unless informed otherwise in the Requirements expression in the submit description file, the platform requested for an execute machine will be the same as the platform where condor_submit is run to submit the job. And, while Mac OS X is a Unix-type operating system, it is not the same as Linux, and thus will not match with machines running Linux.
While the analyzer can diagnose most common problems, there are some situations that it cannot reliably detect due to the instantaneous and local nature of the information it uses to detect the problem. Thus, it may be that the analyzer reports that resources are available to service the request, but the job still has not run. In most of these situations, the delay is transient, and the job will run following the next negotiation cycle.
A second class of problems represents jobs that do or did run, for at least a short while, but are no longer running. The first issue is identifying whether the job is in this category. The condor_q command is not enough; it only tells the current state of the job. The needed information will be in the log file or the error file, as defined in the submit description file for the job. If these files are not defined, then there is little hope of determining if the job ran at all. For a job that ran, even for the briefest amount of time, the log file will contain an event of type 1, which will contain the string Job executing on host.
A job may run for a short time, before failing due to a file permission problem. The log file used by the condor_shadow daemon will contain more information if this is the problem. This log file is associated with the machine on which the job was submitted. The location and name of this log file may be discovered on the submitting machine, using the command
% condor_config_val SHADOW_LOG
Memory and swap space problems may be identified by looking at the log file used by the condor_schedd daemon. The location and name of this log file may be discovered on the submitting machine, using the command
% condor_config_val SCHEDD_LOG
A swap space problem will show in the log with the following message:
2/3 17:46:53 Swap space estimate reached! No more jobs can be run! 12/3 17:46:53 Solution: get more swap space, or set RESERVED_SWAP = 0 12/3 17:46:53 0 jobs matched, 1 jobs idle
As an explanation, HTCondor computes the total swap space on the submit machine. It then tries to limit the total number of jobs it will spawn based on an estimate of the size of the condor_shadow daemon’s memory footprint and a configurable amount of swap space that should be reserved. This is done to avoid the situation within a very large pool in which all the jobs are submitted from a single host. The huge number of condor_shadow processes would overwhelm the submit machine, and it would run out of swap space and thrash.
Things can go wrong if a machine has a lot of physical memory and little or no swap space. HTCondor does not consider the physical memory size, so the situation occurs where HTCondor thinks it has no swap space to work with, and it will not run the submitted jobs.
To see how much swap space HTCondor thinks a given machine has, use the output of a condor_status command of the following form:
% condor_status -schedd [hostname] -long | grep VirtualMemory
If the value listed is 0, then this is what is confusing HTCondor. There are two ways to fix the problem:
Configure the machine with some real swap space.
Disable this check within HTCondor. Define the amount of reserved swap space for the submit machine to 0. Set
RESERVED_SWAPto 0 in the configuration file:
RESERVED_SWAP = 0
and then send a condor_restart to the submit machine.
Job in the Hold State¶
A variety of errors and unusual conditions may cause a job to be placed into the Hold state. The job will stay in this state and in the job queue until conditions are corrected and condor_release is invoked.
A table listing the reasons why a job may be held is at the Job ClassAd Attributes section. A string identifying the reason that a particular job is in the Hold state may be displayed by invoking condor_q. For the example job ID 16.0, use:
condor_q -hold 16.0
This command prints information about the job, including the job ClassAd
In the Job Event Log File¶
In a job event log file are a listing of events in chronological order that occurred during the life of one or more jobs. The formatting of the events is always the same, so that they may be machine readable. Four fields are always present, and they will most often be followed by other fields that give further information that is specific to the type of event.
The first field in an event is the numeric value assigned as the event
type in a 3-digit format. The second field identifies the job which
generated the event. Within parentheses are the job ClassAd attributes
ProcId value, and the node number for
parallel universe jobs or a set of zeros (for jobs run under all other
universes), separated by periods. The third field is the date and time
of the event logging. The fourth field is a string that briefly
describes the event. Fields that follow the fourth field give further
information for the specific event type.
These are all of the events that can show up in a job log file:
When an HTCondor job completes, either through normal means or by abnormal termination by signal, HTCondor will remove it from the job queue. That is, the job will no longer appear in the output of condor_q, and the job will be inserted into the job history file. Examine the job history file with the condor_history command. If there is a log file specified in the submit description file for the job, then the job exit status will be recorded there as well, along with other information described below.
By default, HTCondor does not send an email message when the job completes. Modify this behavior with the notification command in the submit description file. The message will include the exit status of the job, which is the argument that the job passed to the exit system call when it completed, or it will be notification that the job was killed by a signal. Notification will also include the following statistics (as appropriate) about the job:
- Submitted at:
- when the job was submitted with condor_submit
- Completed at:
- when the job completed
- Real Time:
- the elapsed time between when the job was submitted and when it completed, given in a form of
- Virtual Image Size:
- memory size of the job, computed when the job checkpoints
Statistics about just the last time the job ran:
- Run Time:
- total time the job was running, given in the form
- Remote User Time:
- total CPU time the job spent executing in user mode on remote machines; this does not count time spent on run attempts that were evicted without a checkpoint. Given in the form
- Remote System Time:
- total CPU time the job spent executing in system mode (the time spent at system calls); this does not count time spent on run attempts that were evicted without a checkpoint. Given in the form
The Run Time accumulated by all run attempts are summarized with the
time given in the form
And, statistics about the bytes sent and received by the last run of the job and summed over all attempts at running the job are given.
The job terminated event includes the following:
- the type of termination (normal or by signal)
- the return value (or signal number)
- local and remote usage for the last (most recent) run (in CPU-seconds)
- local and remote usage summed over all runs (in CPU-seconds)
- bytes sent and received by the job’s last (most recent) run,
- bytes sent and received summed over all runs,
- a report on which partitionable resources were used, if any. Resources include CPUs, disk, and memory; all are lifetime peak values.
Your administrator may have configured HTCondor to report on other resources, particularly GPUs (lifetime average) and GPU memory usage (lifetime peak). HTCondor currently assigns all the usage of a GPU to the job running in the slot to which the GPU is assigned; if the admin allows more than one job to run on the same GPU, or non-HTCondor jobs to use the GPU, GPU usage will be misreported accordingly.
When configured to report GPU usage, HTCondor sets the following two attributes in the job:
- GPU usage over the lifetime of the job, reported as a fraction of the the maximum possible utilization of one GPU.
- Peak memory usage over the lifetime of the job, in megabytes.