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authorVsevolod Stakhov <vsevolod@highsecure.ru>2018-03-08 16:54:34 +0000
committerVsevolod Stakhov <vsevolod@highsecure.ru>2018-03-08 16:54:34 +0000
commit5f6528af25f1dff0357f3b8e5b41950744785c98 (patch)
tree0c3c94f792c534854e0c6175f7ddb071adf557b7 /conf/statistic.conf
parentaafa714bedf7cd2f76d982d07552caffc784915b (diff)
downloadrspamd-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.conf28
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')