I have a question. Whether the use of sa-learn to teach spamassassin about email spam and ham it matter? How if I do not use it because I do not have a sample of spam or ham in my mail server?
sa-learn is generally used for mail stored on the machine (in mbox or maildir format), and only works when you have filed spam and ham separately. If you are going to use it, it is best used with a decent amount of examples of both to prevent filter bias.
there is a nice doc here which goes through the process and details, but it does require locally stored mail (in either format).
having said this, I use SA on a few boxes and never use sa-learn, and it still does a pretty good job. I do use a number of other anti-spam techniques that aren't SA based, though...
I agree with Mark Regensberg's answer, but to be more specific: as I understand it, sa-learn and the other Bayesian elements of SpamAssassin only affect the Bayesian tests (you can see the current complete list of SA tests for clarification).
That is to say, all the rule-based tests function at full effectiveness regardless of whether you use sa-learn or not. Only the matching of the
Having said that, some of those tests score quite highly - the rating of a message can be affected by an amount between -1.9 and +3.8, according to how "spammy" the Bayesian engine thinks it is - so I find quite a lot of value in giving my engine some training. As Mark notes, you will need to file your ham and undetected spam separately in order to do this.
In answer to your note to Mark, the "other" technique that has decreased my spam more than any other is greylisting, which by eliminating "fire-and-forget" mail reduced my incoming spam by well over 90%. Introducing SPF filtering on incoming email was the second most effective, cutting out about 5% of it.