condor_convert_history man page

condor_convert_historyConvert the history file to the new format

Synopsis

condor_convert_history[-help]

condor_convert_historyhistory-file1[history-file2...]

Description

As of Condor version 6.7.19, the Condor history file has a new format to allow fast searches backwards through the file. Not all queries can take advantage of the speed increase, but the ones that can are significantly faster.

Entries placed in the history file after upgrade to Condor 6.7.19 will automatically be saved in the new format. The new format adds information to the string which distinguishes and separates job entries. In order to search within this new format, no changes are necessary. However, to be able to search the entire history, the history file must be converted to the updated format. condor_convert_historydoes this.

The condor_convert_historycommand can also be used to reconstruct the new format in a history file that has been corrupted or concantenated with another history file.

Turn the condor_schedddaemon off while converting history files. Turn it back on after conversion is completed.

Arguments to condor_convert_historyare the history files to convert. The history file is normally in the Condor spool directory; it is named  history . Since the history file is rotated, there may be multiple history files, and all of them should be converted. On Unix platform variants, the easiest way to do this is:

cd `condor_config_val SPOOL`
condor_convert_history history*

condor_convert_historymakes a back up of each original history files in case of a problem. The names of these back up files are listed; names are formed by appending the suffix  .oldver to the original file name. Move these back up files to a directory other than the spool directory. If kept in the spool directory, condor_historywill find the back ups, and will appear to have duplicate jobs.

Exit Status

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

Author

Center for High Throughput Computing, University of Wisconsin-Madison

Info

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