A job is submitted for execution to Condor using the condor_submit command. condor_submit takes as an argument the name of a file called a submit description file. This file contains commands and keywords to direct the queuing of jobs. In the submit description file, Condor finds everything it needs to know about the job. Items such as the name of the executable to run, the initial working directory, and command-line arguments to the program all go into the submit description file. condor_submit creates a job ClassAd based upon the information, and Condor works toward running the job.
The contents of a submit file can save time for Condor users. It is easy to submit multiple runs of a program to Condor. To run the same program 500 times on 500 different input data sets, arrange your data files accordingly so that each run reads its own input, and each run writes its own output. Each individual run may have its own initial working directory, stdin, stdout, stderr, command-line arguments, and shell environment. A program that directly opens its own files will read the file names to use either from stdin or from the command line. A program that opens a static filename every time will need to use a separate subdirectory for the output of each run.
The condor_submit manual page
is on page ![[*]](crossref.png)
and
contains a complete and full description of how to use condor_submit.
It also includes descriptions of all the commands that may be placed
into a submit description file.
In addition, the index lists entries for each command under the
heading of Submit Commands.
In addition to the examples of submit description files given in the condor_submit manual page, here are a few more.
Example 1 is one of the simplest submit description files possible. It queues up one copy of the program foo (which had been created by condor_compile) for execution by Condor. Since no platform is specified, Condor will use its default, which is to run the job on a machine which has the same architecture and operating system as the machine from which it was submitted. No input, output, and error commands are given in the submit description file, so the files stdin, stdout, and stderr will all refer to /dev/null. The program may produce output by explicitly opening a file and writing to it. A log file, foo.log, will also be produced that contains events the job had during its lifetime inside of Condor. When the job finishes, its exit conditions will be noted in the log file. It is recommended that you always have a log file so you know what happened to your jobs.
####################
#
# Example 1
# Simple condor job description file
#
####################
Executable = foo
Universe = standard
Log = foo.log
Queue
Example 2 queues two copies of the program mathematica. The first copy will run in directory run_1, and the second will run in directory run_2. For both queued copies, stdin will be test.data, stdout will be loop.out, and stderr will be loop.error. There will be two sets of files written, as the files are each written to their own directories. This is a convenient way to organize data if you have a large group of Condor jobs to run. The example file shows program submission of mathematica as a vanilla universe job. This may be necessary if the source and/or object code to mathematica is not available.
The request_memory command is included to insure that the mathematica jobs match with and then execute on pool machines that provide at least 1 GByte of memory.
####################
#
# Example 2: demonstrate use of multiple
# directories for data organization.
#
####################
executable = mathematica
universe = vanilla
input = test.data
output = loop.out
error = loop.error
log = loop.log
request_memory = 1 GB
initialdir = run_1
queue
initialdir = run_2
queue
The submit description file for Example 3 queues 150 runs of program foo which has been compiled and linked for LINUX running on a 32-bit Intel processor. This job requires Condor to run the program on machines which have greater than 32 Mbytes of physical memory, and expresses a preference to run the program on machines with more than 64 Mbytes. It also advises Condor that this standard universe job will use up to 28000 Kbytes of memory when running. Each of the 150 runs of the program is given its own process number, starting with process number 0. So, files stdin, stdout, and stderr will refer to in.0, out.0, and err.0 for the first run of the program, in.1, out.1, and err.1 for the second run of the program, and so forth. A log file containing entries about when and where Condor runs, checkpoints, and migrates processes for all the 150 queued programs will be written into the single file foo.log.
#################### # # Example 3: Show off some fancy features including # use of pre-defined macros and logging. # #################### Executable = foo Universe = standard requirements = OpSys == "LINUX" && Arch =="INTEL" rank = Memory >= 64 image_size = 28000 request_memory = 32 error = err.$(Process) input = in.$(Process) output = out.$(Process) log = foo.log queue 150
The requirements and rank commands in the submit description file are powerful and flexible. Using them effectively requires care, and this section presents those details.
Both requirements and rank need to be specified
as valid Condor ClassAd expressions, however, default values are set by the
condor_submit program if these are not defined in the submit description file.
From the condor_submit manual page and the above examples, you see
that writing ClassAd expressions is intuitive, especially if you
are familiar with the programming language C. There are some
pretty nifty expressions you can write with ClassAds.
A complete description of ClassAds and their expressions
can be found in section 4.1 on
page .
All of the commands in the submit description file are case insensitive, except for the ClassAd attribute string values. ClassAd attribute names are case insensitive, but ClassAd string values are case preserving.
Note that the comparison operators
(<, >, <=, >=, and ==)
compare strings
case insensitively. The special comparison operators
=?= and =!=
compare strings case sensitively.
A requirements or rank command in
the submit description file may utilize attributes
that appear in a machine or a job ClassAd.
Within the submit description file (for a job) the
prefix MY. (on a ClassAd attribute name)
causes a reference to the job ClassAd attribute,
and the prefix TARGET. causes a reference to
a potential machine or matched machine ClassAd attribute.
The condor_status command displays statistics about machines within the pool. The -l option displays the machine ClassAd attributes for all machines in the Condor pool. The job ClassAds, if there are jobs in the queue, can be seen with the condor_q -l command. This shows all the defined attributes for current jobs in the queue.
A list of defined ClassAd attributes for job ClassAds
is given in the unnumbered Appendix on
page .
A list of defined ClassAd attributes for machine ClassAds
is given in the unnumbered Appendix on
page .
When considering the match between a job and a machine, rank is used to choose a match from among all machines that satisfy the job's requirements and are available to the user, after accounting for the user's priority and the machine's rank of the job. The rank expressions, simple or complex, define a numerical value that expresses preferences.
The job's Rank expression evaluates to one of three values. It can be UNDEFINED, ERROR, or a floating point value. If Rank evaluates to a floating point value, the best match will be the one with the largest, positive value. If no Rank is given in the submit description file, then Condor substitutes a default value of 0.0 when considering machines to match. If the job's Rank of a given machine evaluates to UNDEFINED or ERROR, this same value of 0.0 is used. Therefore, the machine is still considered for a match, but has no ranking above any other.
A boolean expression evaluates to the numerical value of 1.0 if true, and 0.0 if false.
The following Rank expressions provide examples to follow.
For a job that desires the machine with the most available memory:
Rank = memory
For a job that prefers to run on a friend's machine on Saturdays and Sundays:
Rank = ( (clockday == 0) || (clockday == 6) )
&& (machine == "friend.cs.wisc.edu")
For a job that prefers to run on one of three specific machines:
Rank = (machine == "friend1.cs.wisc.edu") ||
(machine == "friend2.cs.wisc.edu") ||
(machine == "friend3.cs.wisc.edu")
For a job that wants the machine with the best floating point performance (on Linpack benchmarks):
Rank = kflopsThis particular example highlights a difficulty with Rank expression evaluation as currently defined. While all machines have floating point processing ability, not all machines will have the kflops attribute defined. For machines where this attribute is not defined, Rank will evaluate to the value UNDEFINED, and Condor will use a default rank of the machine of 0.0. The Rank attribute will only rank machines where the attribute is defined. Therefore, the machine with the highest floating point performance may not be the one given the highest rank.
So, it is wise when writing a Rank expression to check if the expression's evaluation will lead to the expected resulting ranking of machines. This can be accomplished using the condor_status command with the -constraint argument. This allows the user to see a list of machines that fit a constraint. To see which machines in the pool have kflops defined, use
condor_status -constraint kflopsAlternatively, to see a list of machines where kflops is not defined, use
condor_status -constraint "kflops=?=undefined"
For a job that prefers specific machines in a specific order:
Rank = ((machine == "friend1.cs.wisc.edu")*3) +
((machine == "friend2.cs.wisc.edu")*2) +
(machine == "friend3.cs.wisc.edu")
If the machine being ranked is friend1.cs.wisc.edu, then the
expression
(machine == "friend1.cs.wisc.edu")is true, and gives the value 1.0. The expressions
(machine == "friend2.cs.wisc.edu")and
(machine == "friend3.cs.wisc.edu")are false, and give the value 0.0. Therefore, Rank evaluates to the value 3.0. In this way, machine friend1.cs.wisc.edu is ranked higher than machine friend2.cs.wisc.edu, machine friend2.cs.wisc.edu is ranked higher than machine friend3.cs.wisc.edu, and all three of these machines are ranked higher than others.
If vanilla, java, or parallel universe jobs are submitted without using the File Transfer mechanism, Condor must use a shared file system to access input and output files. In this case, the job must be able to access the data files from any machine on which it could potentially run.
As an example, suppose a job is submitted from blackbird.cs.wisc.edu, and the job requires a particular data file called /u/p/s/psilord/data.txt. If the job were to run on cardinal.cs.wisc.edu, the file /u/p/s/psilord/data.txt must be available through either NFS or AFS for the job to run correctly.
Condor allows users to ensure their jobs have access to the right shared files by using the FileSystemDomain and UidDomain machine ClassAd attributes. These attributes specify which machines have access to the same shared file systems. All machines that mount the same shared directories in the same locations are considered to belong to the same file system domain. Similarly, all machines that share the same user information (in particular, the same UID, which is important for file systems like NFS) are considered part of the same UID domain.
The default configuration for Condor places each machine in its own UID domain and file system domain, using the full host name of the machine as the name of the domains. So, if a pool does have access to a shared file system, the pool administrator must correctly configure Condor such that all the machines mounting the same files have the same FileSystemDomain configuration. Similarly, all machines that share common user information must be configured to have the same UidDomain configuration.
When a job relies on a shared file system, Condor uses the requirements expression to ensure that the job runs on a machine in the correct UidDomain and FileSystemDomain. In this case, the default requirements expression specifies that the job must run on a machine with the same UidDomain and FileSystemDomain as the machine from which the job is submitted. This default is almost always correct. However, in a pool spanning multiple UidDomains and/or FileSystemDomains, the user may need to specify a different requirements expression to have the job run on the correct machines.
For example, imagine a pool made up of both desktop workstations and a dedicated compute cluster. Most of the pool, including the compute cluster, has access to a shared file system, but some of the desktop machines do not. In this case, the administrators would probably define the FileSystemDomain to be cs.wisc.edu for all the machines that mounted the shared files, and to the full host name for each machine that did not. An example is jimi.cs.wisc.edu.
In this example, a user wants to submit vanilla universe jobs from her own desktop machine (jimi.cs.wisc.edu) which does not mount the shared file system (and is therefore in its own file system domain, in its own world). But, she wants the jobs to be able to run on more than just her own machine (in particular, the compute cluster), so she puts the program and input files onto the shared file system. When she submits the jobs, she needs to tell Condor to send them to machines that have access to that shared data, so she specifies a different requirements expression than the default:
Requirements = TARGET.UidDomain == "cs.wisc.edu" && \
TARGET.FileSystemDomain == "cs.wisc.edu"
WARNING: If there is no shared file system, or the Condor pool administrator does not configure the FileSystemDomain setting correctly (the default is that each machine in a pool is in its own file system and UID domain), a user submits a job that cannot use remote system calls (for example, a vanilla universe job), and the user does not enable Condor's File Transfer mechanism, the job will only run on the machine from which it was submitted.
Condor works well without a shared file system. The Condor file transfer mechanism permits the user to select which files are transferred and under which circumstances. Condor can transfer any files needed by a job from the machine where the job was submitted into a remote scratch directory on the machine where the job is to be executed. Condor executes the job and transfers output back to the submitting machine. The user specifies which files and directories to transfer, and at what point the output files should be copied back to the submitting machine. This specification is done within the job's submit description file.
To enable the file transfer mechanism, place two commands in the job's submit description file: should_transfer_files and when_to_transfer_output. By default, they will be:
should_transfer_files = IF_NEEDED when_to_transfer_output = ON_EXIT
Setting the should_transfer_files command explicitly enables or disables the file transfer mechanism. The command takes on one of three possible values:
YES: Condor transfers both the executable and the file
defined by the input command from the machine where the job is
submitted to the remote machine where the job is to be executed.
The file defined by the output command as well as any files
created by the execution of the job are transferred back to the machine
where the job was submitted.
When they are transferred and the directory location of the files
is determined by the command when_to_transfer_output.
IF_NEEDED: Condor transfers files if the job is
matched with and to be executed on a machine in a
different FileSystemDomain than the
one the submit machine belongs to, the same as if
should_transfer_files = YES.
If the job is matched with a machine in the local FileSystemDomain,
Condor will not transfer files and relies
on the shared file system.
NO: Condor's file transfer mechanism is disabled.
The when_to_transfer_output command tells Condor when output files are to be transferred back to the submit machine. The command takes on one of two possible values:
ON_EXIT: Condor transfers the file defined by the
output command,
as well as any other files in the remote scratch directory created by the job,
back to the submit machine only when the job exits on its own.
ON_EXIT_OR_EVICT: Condor behaves the same as described
for the value ON_EXIT when the job exits on its own.
However, if, and each time the job is evicted from a machine,
files are transferred back at eviction time. The files that
are transferred back at eviction time may include intermediate files
that are not part of the final output of the job. Before the job
starts running again, all of the files that were stored when the job
was last evicted are copied to the job's new remote scratch
directory.
The purpose of saving files at eviction time is to allow the job to
resume from where it left off.
This is similar to using the checkpoint feature of the standard universe,
but just specifying ON_EXIT_OR_EVICT is not enough to make a job
capable of producing or utilizing checkpoints.
The job must be designed to save and restore its state
using the files that are saved at eviction time.
The files that are transferred back at eviction time are not stored in the location where the job's final output will be written when the job exits. Condor manages these files automatically, so usually the only reason for a user to worry about them is to make sure that there is enough space to store them. The files are stored on the submit machine in a temporary directory within the directory defined by the configuration variable SPOOL. The directory is named using the ClusterId and ProcId job ClassAd attributes. The directory name takes the form:
<X mod 10000>/<Y mod 10000>/cluster<X>.proc<Y>.subproc0where
<X> is the value of ClusterId, and
<Y> is the value of ProcId.
As an example, if job 735.0 is evicted, it will produce the directory
$(SPOOL)/735/0/cluster735.proc0.subproc0
The default values for these two submit commands make sense as used together. If only should_transfer_files is set, and set to the value NO, then the default value for an unspecified when_to_transfer_output will be NEVER. Likewise, If only when_to_transfer_output is set, and set to the value ON_EXIT_OR_EVICT, then the default value for an unspecified should_transfer_files will be YES.
Note that the combination of
should_transfer_files = IF_NEEDED when_to_transfer_output = ON_EXIT_OR_EVICTwould produce undefined file access semantics. Therefore, this combination is prohibited by condor_submit.
If the file transfer mechanism is enabled, Condor will transfer the following files before the job is run on a remote machine.
should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = file1,file2This example explicitly enables the file transfer mechanism, and it transfers the executable, the file specified by the input command, any jar files specified by the jar_files command, and files file1 and file2.
If the file transfer mechanism is enabled, Condor will transfer the following files from the execute machine back to the submit machine after the job exits.
A path given for output and error commands represents a path on the submit machine. If no path is specified, the directory specified with initialdir is used, and if that is not specified, the directory from which the job was submitted is used. At the time the job is submitted, zero-length files are created on the submit machine, at the given path for the files defined by the output and error commands. This permits job submission failure, if these files cannot be written by Condor.
To restrict the output files or permit entire directory contents to be transferred, specify the exact list with transfer_output_files. Delimit the list of file names, directory names, or paths with commas. When this list is defined, and any of the files or directories do not exist as the job exits, Condor considers this an error, and places the job on hold. When this list is defined, automatic detection of output files created by the job is disabled. Paths specified in this list refer to locations on the execute machine. The naming and placement of files and directories relies on the term base name. By example, the path a/b/c has the base name c. It is the file name or directory name with all directories leading up to that name stripped off. On the submit machine, the transferred files or directories are named using only the base name. Therefore, each output file or directory must have a different name, even if they originate from different paths.
For grid universe jobs other than than Condor-C grid jobs, files to be transferred (other than standard output and standard error) must be specified using transfer_output_files in the submit description file, because automatic detection of new files created by the job does not take place.
Here are examples to promote understanding of what files and directories are transferred, and how they are named after transfer. Assume that the job produces the following structure within the remote scratch directory:
o1
o2
d1 (directory)
o3
o4
If the submit description file sets
transfer_output_files = o1,o2,d1then transferred back to the submit machine will be
o1
o2
d1 (directory)
o3
o4
Note that the directory d1 and all its contents are specified,
and therefore transferred.
If the directory d1 is not created by the job before exit,
then the job is placed on hold.
If the directory d1 is created by the job before exit,
but is empty, this is not an error.
If, instead, the submit description file sets
transfer_output_files = o1,o2,d1/o3then transferred back to the submit machine will be
o1
o2
o3
Note that only the base name is used in the naming and placement
of the file specified with d1/o3.
The file transfer mechanism specifies file names and/or paths on both the file system of the submit machine and on the file system of the execute machine. Care must be taken to know which machine, submit or execute, is utilizing the file name and/or path.
Files in the transfer_input_files command are specified as they are accessed on the submit machine. The job, as it executes, accesses files as they are found on the execute machine.
There are three ways to specify files and paths for transfer_input_files:
Before executing the program, Condor copies the executable, an input file as specified by the submit command input, along with any input files specified by transfer_input_files. All these files are placed into a remote scratch directory on the execute machine, in which the program runs. Therefore, the executing program must access input files relative to its working directory. Because all files and directories listed for transfer are placed into a single, flat directory, inputs must be uniquely named to avoid collision when transferred. A collision causes the last file in the list to overwrite the earlier one.
Both relative and absolute paths may be used in transfer_output_files. Relative paths are relative to the job's remote scratch directory on the execute machine. When the files and directories are copied back to the submit machine, they are placed in the job's initial working directory as the base name of the original path. An alternate name or path may be specified by using transfer_output_remaps.
A job may create files outside the remote scratch directory but within the file system of the execute machine, in a directory such as /tmp, if this directory is guaranteed to exist and be accessible on all possible execute machines. However, Condor will not automatically transfer such files back after execution completes, nor will it clean up these files.
Here are several examples to illustrate the use of file transfer. The program executable is called my_program, and it uses three command-line arguments as it executes: two input file names and an output file name. The program executable and the submit description file for this job are located in directory /scratch/test.
Here is the directory tree as it exists on the submit machine, for all the examples:
/scratch/test (directory)
my_program.condor (the submit description file)
my_program (the executable)
files (directory)
logs2 (directory)
in1 (file)
in2 (file)
logs (directory)
This first example explicitly transfers input files. These input files to be transferred are specified relative to the directory where the job is submitted. An output file specified in the arguments command, out1, is created when the job is executed. It will be transferred back into the directory /scratch/test.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs/err.$(cluster) Output = logs/out.$(cluster) Log = logs/log.$(cluster) should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = files/in1,files/in2 Arguments = in1 in2 out1 Queue
The log file is written on the submit machine, and is not involved with the file transfer mechanism.
This second example is identical to Example 1, except that absolute paths to the input files are specified, instead of relative paths to the input files.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs/err.$(cluster) Output = logs/out.$(cluster) Log = logs/log.$(cluster) should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = /scratch/test/files/in1,/scratch/test/files/in2 Arguments = in1 in2 out1 Queue
This third example illustrates the use of the
submit command initialdir, and its effect
on the paths used for the various files.
The expected location of the
executable is not affected by the
initialdir command.
All other files
(specified by input, output, error,
transfer_input_files,
as well as files modified or created by the job
and automatically transferred back)
are located relative to the specified initialdir.
Therefore, the output file, out1,
will be placed in the files directory.
Note that the logs2 directory
exists to make this example work correctly.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs2/err.$(cluster) Output = logs2/out.$(cluster) Log = logs2/log.$(cluster) initialdir = files should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = in1,in2 Arguments = in1 in2 out1 Queue
This example illustrates a job that will fail. The files specified using the transfer_input_files command work correctly (see Example 1). However, relative paths to files in the arguments command cause the executing program to fail. The file system on the submission side may utilize relative paths to files, however those files are placed into the single, flat, remote scratch directory on the execute machine.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs/err.$(cluster) Output = logs/out.$(cluster) Log = logs/log.$(cluster) should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = files/in1,files/in2 Arguments = files/in1 files/in2 files/out1 Queue
This example fails with the following error:
err: files/out1: No such file or directory.
As with Example 4, this example illustrates a job that will fail. The executing program's use of absolute paths cannot work.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs/err.$(cluster) Output = logs/out.$(cluster) Log = logs/log.$(cluster) should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = /scratch/test/files/in1, /scratch/test/files/in2 Arguments = /scratch/test/files/in1 /scratch/test/files/in2 /scratch/test/files/out1 Queue
The job fails with the following error:
err: /scratch/test/files/out1: No such file or directory.
This example illustrates a case where the executing program creates an output file in a directory other than within the remote scratch directory that the program executes within. The file creation may or may not cause an error, depending on the existence and permissions of the directories on the remote file system.
The output file /tmp/out1 is transferred back to the job's initial working directory as /scratch/test/out1.
# file name: my_program.condor # Condor submit description file for my_program Executable = my_program Universe = vanilla Error = logs/err.$(cluster) Output = logs/out.$(cluster) Log = logs/log.$(cluster) should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = files/in1,files/in2 transfer_output_files = /tmp/out1 Arguments = in1 in2 /tmp/out1 Queue
This job submission failure avoids having the job run to completion, only to be unable to transfer the job's output due to permission errors.
During transfer, if any of the following three similar types of errors occur, the job is put on hold as the error occurs.
Instead of file transfer that goes only between the submit machine and the execute machine, Condor has the ability to transfer files from a location specified by a URL for a job's input file, or from the execute machine to a location specified by a URL for a job's output file(s). This capability requires administrative set up, as described in section 3.12.2.
The transfer of an input file is restricted to vanilla and vm universe jobs only. Condor's file transfer mechanism must be enabled. Therefore, the submit description file for the job will define both should_transfer_files and when_to_transfer_output. In addition, the URL for any files specified with a URL are given in the transfer_input_files command. An example portion of the submit description file for a job that has a single file specified with a URL:
should_transfer_files = YES when_to_transfer_output = ON_EXIT transfer_input_files = http://www.full.url/path/to/filename
The destination file is given by the file name within the URL.
For the transfer of the entire contents of the output sandbox, which are all files that the job creates or modifies, Condor's file transfer mechanism must be enabled. In this sample portion of the submit description file, the first two commands explicitly enable file transfer, and the added output_destination command provides both the protocol to be used and the destination of the transfer.
should_transfer_files = YES when_to_transfer_output = ON_EXIT output_destination = urltype://path/to/destination/directoryNote that with this feature, no files are transferred back to the submit machine. This does not interfere with the streaming of output.
If only a subset of the output sandbox should be transferred, the subset is specified by further adding a submit command of the form:
transfer_output_files = file1, file2
The requirements expression for a job must depend
on the should_transfer_files command.
The job must specify the correct logic to ensure that the job is matched
with a resource that meets the file transfer needs.
If no requirements expression is in the submit description file,
or if the expression specified does not refer to the
attributes listed below, condor_submit adds an
appropriate clause to the requirements expression for the job.
condor_submit appends these clauses with a logical AND, &&,
to ensure that the proper conditions are met.
Here are the default clauses corresponding to the different values of
should_transfer_files:
should_transfer_files = YES results in the addition of
the clause (HasFileTransfer).
If the job is always going to transfer files, it is required to
match with a machine that has the capability to transfer files.
should_transfer_files = NO results in the addition of
(TARGET.FileSystemDomain == MY.FileSystemDomain).
In addition, Condor automatically adds the
FileSystemDomain attribute to the job ClassAd, with whatever
string is defined for the condor_schedd to which the job is
submitted.
If the job is not using the file transfer mechanism, Condor assumes
it will need a shared file system, and therefore, a machine in the
same FileSystemDomain as the submit machine.
should_transfer_files = IF_NEEDED results in the addition of
(HasFileTransfer || (TARGET.FileSystemDomain == MY.FileSystemDomain))If Condor will optionally transfer files, it must require that the machine is either capable of transferring files or in the same file system domain.
To ensure that the job is matched to a machine with enough local disk space to hold all the transferred files, Condor automatically adds the DiskUsage job attribute. This attribute includes the total size of the job's executable and all input files to be transferred. Condor then adds an additional clause to the Requirements expression that states that the remote machine must have at least enough available disk space to hold all these files:
&& (Disk >= DiskUsage)
If should_transfer_files = IF_NEEDED and the job prefers
to run on a machine in the local file system domain
over transferring files,
but is still willing to allow the job to run remotely and transfer files,
the Rank expression works well. Use:
rank = (TARGET.FileSystemDomain == MY.FileSystemDomain)
The Rank expression is a floating point value, so if other items are considered in ranking the possible machines this job may run on, add the items:
Rank = kflops + (TARGET.FileSystemDomain == MY.FileSystemDomain)
The value of kflops can vary widely among machines, so this Rank expression will likely not do as it intends. To place emphasis on the job running in the same file system domain, but still consider floating point speed among the machines in the file system domain, weight the part of the expression that is matching the file system domains. For example:
Rank = kflops + (10000 * (TARGET.FileSystemDomain == MY.FileSystemDomain))
The environment under which a job executes often contains information that is potentially useful to the job. Condor allows a user to both set and reference environment variables for a job or job cluster.
Within a submit description file, the user may define environment variables for the job's environment by using the environment command. See within the condor_submit manual page at section 10 for more details about this command.
The submitter's entire environment can be copied into the job ClassAd for the job at job submission. The getenv command within the submit description file does this, as described at section 10.
If the environment is set with the environment command and getenv is also set to true, values specified with environment override values in the submitter's environment, regardless of the order of the environment and getenv commands.
Commands within the submit description file may reference the
environment variables of the submitter as a job is submitted.
Submit description file commands use $ENV(EnvironmentVariableName)
to reference the value of an environment variable.
Condor sets several additional environment variables for each executing job that may be useful for the job to reference.
1, just like the SlotID attribute in the machine's
ClassAd.
This setting is available in all universes.
See section 3.12.8 for more details about SMP
machines and their configuration.
If executables are available for the different platforms of machines in the Condor pool, Condor can be allowed the choice of a larger number of machines when allocating a machine for a job. Modifications to the submit description file allow this choice of platforms.
A simplified example is a cross submission. An executable is available for one platform, but the submission is done from a different platform. Given the correct executable, the requirements command in the submit description file specifies the target architecture. For example, an executable compiled for a 32-bit Intel processor running Windows Vista, submitted from an Intel architecture running Linux would add the requirement
requirements = Arch == "INTEL" && OpSys == "WINDOWS"Without this requirement, condor_submit will assume that the program is to be executed on a machine with the same platform as the machine where the job is submitted.
Cross submission works for all universes except scheduler and local. See section 5.3.11 for how matchmaking works in the grid universe. The burden is on the user to both obtain and specify the correct executable for the target architecture. To list the architecture and operating systems of the machines in a pool, run condor_status.
A more complex example of a heterogeneous submission occurs when a job may be executed on many different architectures to gain full use of a diverse architecture and operating system pool. If the executables are available for the different architectures, then a modification to the submit description file will allow Condor to choose an executable after an available machine is chosen.
A special-purpose Machine Ad substitution macro can be used in string attributes in the submit description file. The macro has the form
$$(MachineAdAttribute)The $$() informs Condor to substitute the requested MachineAdAttribute from the machine where the job will be executed.
An example of the heterogeneous job submission has executables available for two platforms: RHEL 3 on both 32-bit and 64-bit Intel processors. This example uses povray to render images using a popular free rendering engine.
The substitution macro chooses a specific executable after a platform for running the job is chosen. These executables must therefore be named based on the machine attributes that describe a platform. The executables named
povray.LINUX.INTEL povray.LINUX.X86_64will work correctly for the macro
povray.$$(OpSys).$$(Arch)
The executables or links to executables with this name are placed into the initial working directory so that they may be found by Condor. A submit description file that queues three jobs for this example:
####################
#
# Example of heterogeneous submission
#
####################
universe = vanilla
Executable = povray.$$(OpSys).$$(Arch)
Log = povray.log
Output = povray.out.$(Process)
Error = povray.err.$(Process)
Requirements = (Arch == "INTEL" && OpSys == "LINUX") || \
(Arch == "X86_64" && OpSys =="LINUX")
Arguments = +W1024 +H768 +Iimage1.pov
Queue
Arguments = +W1024 +H768 +Iimage2.pov
Queue
Arguments = +W1024 +H768 +Iimage3.pov
Queue
These jobs are submitted to the vanilla universe to assure that once a job is started on a specific platform, it will finish running on that platform. Switching platforms in the middle of job execution cannot work correctly.
There are two common errors made with the substitution macro. The first is the use of a non-existent MachineAdAttribute. If the specified MachineAdAttribute does not exist in the machine's ClassAd, then Condor will place the job in the held state until the problem is resolved.
The second common error occurs due to an incomplete job set up. For example, the submit description file given above specifies three available executables. If one is missing, Condor reports back that an executable is missing when it happens to match the job with a resource that requires the missing binary.
Jobs submitted to the standard universe may produce checkpoints. A checkpoint can then be used to start up and continue execution of a partially completed job. For a partially completed job, the checkpoint and the job are specific to a platform. If migrated to a different machine, correct execution requires that the platform must remain the same.
In previous versions of Condor, the author of the heterogeneous submission file would need to write extra policy expressions in the requirements expression to force Condor to choose the same type of platform when continuing a checkpointed job. However, since it is needed in the common case, this additional policy is now automatically added to the requirements expression. The additional expression is added provided the user does not use CkptArch in the requirements expression. Condor will remain backward compatible for those users who have explicitly specified CkptRequirements-implying use of CkptArch, in their requirements expression.
The expression added when the attribute CkptArch is not specified will default to
# Added by Condor
CkptRequirements = ((CkptArch == Arch) || (CkptArch =?= UNDEFINED)) && \
((CkptOpSys == OpSys) || (CkptOpSys =?= UNDEFINED))
Requirements = (<user specified policy>) && $(CkptRequirements)
The behavior of the CkptRequirements expressions and its addition to
requirements is as follows.
The CkptRequirements expression guarantees correct operation
in the two possible cases for a job.
In the first case, the job has not produced a checkpoint.
The ClassAd attributes CkptArch and CkptOpSys
will be undefined, and therefore the meta operator (=?=)
evaluates to true.
In the second case, the job has produced a checkpoint.
The Machine ClassAd is restricted to require further execution
only on a machine of the same platform.
The attributes CkptArch and CkptOpSys
will be defined, ensuring that the platform chosen for further
execution will be the same as the one used just before the
checkpoint.
Note that this restriction of platforms also applies to platforms where the executables are binary compatible.
The complete submit description file for this example:
####################
#
# Example of heterogeneous submission
#
####################
universe = standard
Executable = povray.$$(OpSys).$$(Arch)
Log = povray.log
Output = povray.out.$(Process)
Error = povray.err.$(Process)
# Condor automatically adds the correct expressions to insure that the
# checkpointed jobs will restart on the correct platform types.
Requirements = ( (Arch == "INTEL" && OpSys == "LINUX") || \
(Arch == "X86_64" && OpSys == "LINUX") )
Arguments = +W1024 +H768 +Iimage1.pov
Queue
Arguments = +W1024 +H768 +Iimage2.pov
Queue
Arguments = +W1024 +H768 +Iimage3.pov
Queue
The addition of several related OpSys attributes assists in selection of specific operating systems and versions in heterogeneous pools.
#################### # # Example of submission targeting RedHat platforms in a heterogeneous Linux pool # #################### universe = vanilla Executable = /bin/date Log = distro.log Output = distro.out Error = distro.err Requirements = (OpSysName == "RedHat") Queue
#################### # # Example of submission targeting RedHat 6 platforms in a heterogeneous Linux pool # #################### universe = vanilla Executable = /bin/date Log = distro.log Output = distro.out Error = distro.err Requirements = ( OpSysName == "RedHat" && OpSysMajorVersion == 6) Queue
Here is a more compact way to specify a RedHat 6 platform.
#################### # # Example of submission targeting RedHat 6 platforms in a heterogeneous Linux pool # #################### universe = vanilla Executable = /bin/date Log = distro.log Output = distro.out Error = distro.err Requirements = ( OpSysAndVer == "RedHat6") Queue