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author | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2018-03-08 16:54:34 +0000 |
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committer | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2018-03-08 16:54:34 +0000 |
commit | 5f6528af25f1dff0357f3b8e5b41950744785c98 (patch) | |
tree | 0c3c94f792c534854e0c6175f7ddb071adf557b7 /conf/statistic.conf | |
parent | aafa714bedf7cd2f76d982d07552caffc784915b (diff) | |
download | rspamd-5f6528af25f1dff0357f3b8e5b41950744785c98.tar.gz rspamd-5f6528af25f1dff0357f3b8e5b41950744785c98.zip |
Revert "[Conf] Default statistics is stored in Redis now"
This reverts commit feb910e287c215d5a1b6a03856ad2a1cbd36a394.
Diffstat (limited to 'conf/statistic.conf')
-rw-r--r-- | conf/statistic.conf | 28 |
1 files changed, 12 insertions, 16 deletions
diff --git a/conf/statistic.conf b/conf/statistic.conf index 79c3e3890..26e73c4d2 100644 --- a/conf/statistic.conf +++ b/conf/statistic.conf @@ -13,38 +13,34 @@ # # See https://rspamd.com/doc/tutorials/writing_rules.html for details -# Rspamd statistic setup, set up the Redis server as appropriate +# Rspamd statistic setup +# Pre-built files could be loaded from: +# http://rspamd.com/rspamd_statistics/bayes.spam.sqlite +# - and - +# http://rspamd.com/rspamd_statistics/bayes.ham.sqlite classifier "bayes" { tokenizer { name = "osb"; } - + cache { + path = "${DBDIR}/learn_cache.sqlite"; + } min_tokens = 11; - backend = "redis"; + backend = "sqlite3"; + languages_enabled = true; min_learns = 200; statfile { symbol = "BAYES_HAM"; + path = "${DBDIR}/bayes.ham.sqlite"; spam = false; } statfile { symbol = "BAYES_SPAM"; + path = "${DBDIR}/bayes.spam.sqlite"; spam = true; } - # Define different if needed - servers = "127.0.0.1:6379"; - # Store not only probabilities, but full tokens, false by default - #store_tokens = true; - # Use new schema (TODO: add convert tool) - #new_schema = true; - # Store bayes signatures (TODO: add some usefullnes to this feature) - #signatures = true; - # Expire bayes tokens (TODO: check for new schema, add expiration logic) - #expiry = 30d; - # Enable per user statistics (TODO: describe how to use per user + normal stats) - #per_user = true; - learn_condition =<<EOD return function(task, is_spam, is_unlearn) local prob = task:get_mempool():get_variable('bayes_prob', 'double') |