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 * Speed issues: ''' spamassassin -D --lint 2>&1 | less ''' and look for any gaps in time

 * Failures: ''' spamassassin -D --lint 2>&1 | grep failed '''

 * DNS related: ''' spamassassin -D --lint 2>&1 | grep dns: '''

 * Shortciruit: ''' spamassassin -D --lint 2>&1 | grep shortcircuit: '''

 * Bayes: ''' spamassassin -D --lint 2>&1 | grep bayes: '''

  * If you are not seeing any BAYES rules hit in your logs/headers, make sure you have at least 200 ham and 200 spam tokens: ''' sa-learn --dump magic '''
  {{{
  0.000 0 3 0 non-token data: bayes db version
  0.000 0 2944470 0 non-token data: nspam
  0.000 0 12169738 0 non-token data: nham
  }}}


Here are some simple steps in debugging your SpamAssassin installation:

  • Run 'spamassassin --lint', especially if you just added anything to your *.cf files or a user_prefs file. Often times you might have something slightly wrong and either a) SpamAssassin stops parsing the file or b) it's just plain wrong and causing the error.

  • Run with '-D'. The debug output from spamassassin, sa-learn, spamd is sometimes very verbose, but it also gives you a large amount of data that can be very helpful. Often times debug is the only place to see what exactly is causing your error. When running spamd with -D you will see some initial startup activity, you can ignore this, it is just scanning a test message to help do the initial load of the perl modules.

  • Sometimes its necessary to output the SpamAssassin debug information to a file. This can be done by redirecting stdout to a file and then redirecting stderr to the same location. Run 'spamassassin -D --lint > test.log 2>&1'.

  • Speed issues: spamassassin -D --lint 2>&1 | less and look for any gaps in time

  • Failures: spamassassin -D --lint 2>&1 | grep failed

  • DNS related: spamassassin -D --lint 2>&1 | grep dns:

  • Shortciruit: spamassassin -D --lint 2>&1 | grep shortcircuit:

  • Bayes: spamassassin -D --lint 2>&1 | grep bayes:

    • If you are not seeing any BAYES rules hit in your logs/headers, make sure you have at least 200 ham and 200 spam tokens: sa-learn --dump magic

        0.000          0          3          0  non-token data: bayes db version
        0.000          0    2944470          0  non-token data: nspam
        0.000          0   12169738          0  non-token data: nham


CategoryFaq

HowToDebug (last edited 2017-05-25 18:09:24 by Dave Jones)