Name

       condor_transform_ads  Transform  -  ClassAds  according  to  specified  rules, and output the transformed
       ClassAds.

Synopsis

       condor_transform_ads [-help [rules]]

       condor_transform_ads-rules   rules-file[-in[:<form>]   infile]    [-out[:<form>[,    nosort]]    outfile]
       [<key>=<value>]   [-long]   [-json]   [-xml]   [-verbose]   [-terse]   [-debug]  [-unit-test]  [-testing]
       [-convertoldroutes] [infile1 ...infileN]

       Note that exactly one rules file, and at least one input file, must be specified. If no  output  file  is
       specified, output will be written to  stdout .

Description

       condor_transform_adsreads  ClassAds from a set of input files, transforms them according to rules defined
       in a rules file, and outputs the resulting transformed ClassAds.

       See https://htcondor-wiki.cs.wisc.edu/index.cgi/wiki?p=TjsAdTransformLanguagefor  a  description  of  the
       transform language.

Options

       -help [rules]

          Display usage information and exit. -help rulesdisplays information about the available transformation
          rules.

       -rules rules-file

          Specifies the file containing definitions of the transformation rules.

       -in[:<form>] infile

          Specifies an input file containing ClassAd(s) to be transformed. <form>, if specified, is one of:

             * long: traditional long form (default)

             * xml: XML form

             * json: JSON ClassAd form

             * new: "new" ClassAd form without newlines

             *  auto: guess format by reading the input If  - is specified for infile, input is read from  stdin
             .

       -out[:<form>[, nosort] outfile

          Specifies an output file to receive the transformed ClassAd(s). <form>, if specified, is one of:

             * long: traditional long form (default)

             * xml: XML form

             * json: JSON ClassAd form

             * new: "new" ClassAd form without newlines

             * auto: use the same format as the first input ClassAds are storted by  attribute  unless  nosortis
             specified.

       [<key>=<value>]

          Assign  key/value  pairs  before  rules  file is parsed; can be used to pass arguments to rules. (More
          detail needed here.)

       -long

          Use long form for both input and output ClassAd(s). (This is the default.)

       -json

          Use JSON form for both input and output ClassAd(s).

       -xml

          Use XML form for both input and output ClassAd(s).

       -verbose

          Verbose mode, echo transform rules as they are executed.

       -terse

          Disable the -verboseoption.

       -debug

          More information needed here.

       -unit-test

          More information needed here.

       -testing

          More information needed here.

       -convertoldroutes

          More information needed here.

Exit Status

       condor_transform_adswill exit with a status value of 0 (zero) upon success, and it  will  exit  with  the
       value 1 (one) upon failure.

Examples

       Here's a simple example that transforms the given input ClassAds according to the given rules:

        # File: my_input
        ResidentSetSize = 500
        DiskUsage = 2500000
        NumCkpts = 0
        TransferrErr = false
        Err = "/dev/null"

        # File: my_rules
        EVALSET MemoryUsage ( ResidentSetSize / 100 )
        EVALMACRO WantDisk = ( DiskUsage * 2 )
        SET RequestDisk ( $(WantDisk) / 1024 )
        RENAME NumCkpts NumCheckPoints
        DELETE /(.+)Err/

        # Command:
        condor_transform_ads  -rules my_rules -in my_input

        # Output:
        DiskUsage = 2500000
        Err = "/dev/null"
        MemoryUsage = 5
        NumCheckPoints = 0
        RequestDisk = ( 5000000 / 1024 )
        ResidentSetSize = 500

Author

       Center for High Throughput Computing, University of Wisconsin-Madison

Copyright

       Copyright (C) 1990-2016 Center for High Throughput Computing, Computer Sciences Department, University of
       Wisconsin-Madison, Madison, WI. All Rights Reserved. Licensed under the Apache License, Version 2.0.

                                                   April 2018                            condor_transform_ads(1)