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--[[
Copyright (c) 2017, Andrew Lewis <nerf@judo.za.org>
Copyright (c) 2017, Vsevolod Stakhov <vsevolod@highsecure.ru>
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
]] --
if confighelp then
return
end
local N = 'bayes_expiry'
local E = {}
local logger = require "rspamd_logger"
local rspamd_util = require "rspamd_util"
local lutil = require "lua_util"
local lredis = require "lua_redis"
local settings = {
interval = 60, -- one iteration step per minute
count = 1000, -- check up to 1000 keys on each iteration
epsilon_common = 0.01, -- eliminate common if spam to ham rate is equal to this epsilon
common_ttl = 10 * 86400, -- TTL of discriminated common elements
significant_factor = 3.0 / 4.0, -- which tokens should we update
classifiers = {},
cluster_nodes = 0,
}
local template = {}
local function check_redis_classifier(cls, cfg)
-- Skip old classifiers
if cls.new_schema then
local symbol_spam, symbol_ham
local expiry = (cls.expiry or cls.expire)
if type(expiry) == 'table' then
expiry = expiry[1]
end
-- Load symbols from statfiles
local function check_statfile_table(tbl, def_sym)
local symbol = tbl.symbol or def_sym
local spam
if tbl.spam then
spam = tbl.spam
else
if string.match(symbol:upper(), 'SPAM') then
spam = true
else
spam = false
end
end
if spam then
symbol_spam = symbol
else
symbol_ham = symbol
end
end
local statfiles = cls.statfile
if statfiles[1] then
for _,stf in ipairs(statfiles) do
if not stf.symbol then
for k,v in pairs(stf) do
check_statfile_table(v, k)
end
else
check_statfile_table(stf, 'undefined')
end
end
else
for stn,stf in pairs(statfiles) do
check_statfile_table(stf, stn)
end
end
if not symbol_spam or not symbol_ham or type(expiry) ~= 'number' then
logger.debugm(N, rspamd_config,
'disable expiry for classifier %s: no expiry %s',
symbol_spam, cls)
return
end
-- Now try to load redis_params if needed
local redis_params
redis_params = lredis.try_load_redis_servers(cls, rspamd_config, false, 'bayes')
if not redis_params then
redis_params = lredis.try_load_redis_servers(cfg[N] or E, rspamd_config, false, 'bayes')
if not redis_params then
redis_params = lredis.try_load_redis_servers(cfg[N] or E, rspamd_config, true)
if not redis_params then
return false
end
end
end
if redis_params['read_only'] then
logger.infox(rspamd_config, 'disable expiry for classifier %s: read only redis configuration',
symbol_spam)
return
end
logger.debugm(N, rspamd_config, "enabled expiry for %s/%s -> %s expiry",
symbol_spam, symbol_ham, expiry)
table.insert(settings.classifiers, {
symbol_spam = symbol_spam,
symbol_ham = symbol_ham,
redis_params = redis_params,
expiry = expiry
})
end
end
-- Check classifiers and try find the appropriate ones
local obj = rspamd_config:get_ucl()
local classifier = obj.classifier
if classifier then
if classifier[1] then
for _,cls in ipairs(classifier) do
if cls.bayes then cls = cls.bayes end
if cls.backend and cls.backend == 'redis' then
check_redis_classifier(cls, obj)
end
end
else
if classifier.bayes then
classifier = classifier.bayes
if classifier[1] then
for _,cls in ipairs(classifier) do
if cls.backend and cls.backend == 'redis' then
check_redis_classifier(cls, obj)
end
end
else
if classifier.backend and classifier.backend == 'redis' then
check_redis_classifier(classifier, obj)
end
end
end
end
end
local opts = rspamd_config:get_all_opt(N)
if opts then
for k,v in pairs(opts) do
settings[k] = v
end
end
-- In clustered setup, we need to increase interval of expiration
-- according to number of nodes in a cluster
if settings.cluster_nodes == 0 then
local neighbours = obj.neighbours or {}
local n_neighbours = 0
for _,_ in pairs(neighbours) do n_neighbours = n_neighbours + 1 end
settings.cluster_nodes = n_neighbours
end
-- Fill template
template.count = settings.count
template.threshold = settings.threshold
template.common_ttl = settings.common_ttl
template.epsilon_common = settings.epsilon_common
template.significant_factor = settings.significant_factor
template.expire_step = settings.interval
template.hostname = rspamd_util.get_hostname()
for k,v in pairs(template) do
template[k] = tostring(v)
end
-- Arguments:
-- [1] = symbol pattern
-- [2] = expire value
-- [3] = cursor
-- returns {cursor for the next step, step number, step statistic counters, cycle statistic counters, tokens occurrences distribution}
local expiry_script = [[
local unpack_function = table.unpack or unpack
local hash2list = function (hash)
local res = {}
for k, v in pairs(hash) do
table.insert(res, k)
table.insert(res, v)
end
return res
end
local function merge_list(table, list)
local k
for i, v in ipairs(list) do
if i % 2 == 1 then
k = v
else
table[k] = v
end
end
end
local expire = math.floor(KEYS[2])
local pattern_sha1 = redis.sha1hex(KEYS[1])
local lock_key = pattern_sha1 .. '_lock' -- Check locking
local lock = redis.call('GET', lock_key)
if lock then
if lock ~= '${hostname}' then
return 'locked by ' .. lock
end
end
redis.replicate_commands()
redis.call('SETEX', lock_key, ${expire_step}, '${hostname}')
local cursor_key = pattern_sha1 .. '_cursor'
local cursor = tonumber(redis.call('GET', cursor_key) or 0)
local step = 1
local step_key = pattern_sha1 .. '_step'
if cursor > 0 then
step = redis.call('GET', step_key)
step = step and (tonumber(step) + 1) or 1
end
local ret = redis.call('SCAN', cursor, 'MATCH', KEYS[1], 'COUNT', '${count}')
local next_cursor = ret[1]
local keys = ret[2]
local tokens = {}
-- Tokens occurrences distribution counters
local occurr = {
ham = {},
spam = {},
total = {}
}
-- Expiry step statistics counters
local nelts, extended, discriminated, sum, sum_squares, common, significant,
infrequent, infrequent_ttls_set, insignificant, insignificant_ttls_set =
0,0,0,0,0,0,0,0,0,0,0
for _,key in ipairs(keys) do
local t = redis.call('TYPE', key)["ok"]
if t == 'hash' then
local values = redis.call('HMGET', key, 'H', 'S')
local ham = tonumber(values[1]) or 0
local spam = tonumber(values[2]) or 0
local ttl = redis.call('TTL', key)
tokens[key] = {
ham,
spam,
ttl
}
local total = spam + ham
sum = sum + total
sum_squares = sum_squares + total * total
nelts = nelts + 1
for k,v in pairs({['ham']=ham, ['spam']=spam, ['total']=total}) do
if tonumber(v) > 19 then v = 20 end
occurr[k][v] = occurr[k][v] and occurr[k][v] + 1 or 1
end
end
end
local mean, stddev = 0, 0
if nelts > 0 then
mean = sum / nelts
stddev = math.sqrt(sum_squares / nelts - mean * mean)
end
for key,token in pairs(tokens) do
local ham, spam, ttl = token[1], token[2], tonumber(token[3])
local threshold = mean
local total = spam + ham
local function set_ttl()
if expire < 0 then
if ttl ~= -1 then
redis.call('PERSIST', key)
return 1
end
elseif ttl == -1 or ttl > expire then
redis.call('EXPIRE', key, expire)
return 1
end
return 0
end
if total == 0 or math.abs(ham - spam) <= total * ${epsilon_common} then
common = common + 1
if ttl > ${common_ttl} then
discriminated = discriminated + 1
redis.call('EXPIRE', key, ${common_ttl})
end
elseif total >= threshold and total > 0 then
if ham / total > ${significant_factor} or spam / total > ${significant_factor} then
significant = significant + 1
if ttl ~= -1 then
redis.call('PERSIST', key)
extended = extended + 1
end
else
insignificant = insignificant + 1
insignificant_ttls_set = insignificant_ttls_set + set_ttl()
end
else
infrequent = infrequent + 1
infrequent_ttls_set = infrequent_ttls_set + set_ttl()
end
end
-- Expiry cycle statistics counters
local c = {nelts = 0, extended = 0, discriminated = 0, sum = 0, sum_squares = 0,
common = 0, significant = 0, infrequent = 0, infrequent_ttls_set = 0, insignificant = 0, insignificant_ttls_set = 0}
local counters_key = pattern_sha1 .. '_counters'
if cursor ~= 0 then
merge_list(c, redis.call('HGETALL', counters_key))
end
c.nelts = c.nelts + nelts
c.extended = c.extended + extended
c.discriminated = c.discriminated + discriminated
c.sum = c.sum + sum
c.sum_squares = c.sum_squares + sum_squares
c.common = c.common + common
c.significant = c.significant + significant
c.infrequent = c.infrequent + infrequent
c.infrequent_ttls_set = c.infrequent_ttls_set + infrequent_ttls_set
c.insignificant = c.insignificant + insignificant
c.insignificant_ttls_set = c.insignificant_ttls_set + insignificant_ttls_set
redis.call('HMSET', counters_key, unpack_function(hash2list(c)))
redis.call('SET', cursor_key, tostring(next_cursor))
redis.call('SET', step_key, tostring(step))
redis.call('DEL', lock_key)
local occ_distr = {}
for _,cl in pairs({'ham', 'spam', 'total'}) do
local occurr_key = pattern_sha1 .. '_occurrence_' .. cl
if cursor ~= 0 then
local n
for i,v in ipairs(redis.call('HGETALL', occurr_key)) do
if i % 2 == 1 then
n = tonumber(v)
else
occurr[cl][n] = occurr[cl][n] and occurr[cl][n] + v or v
end
end
local str = ''
if occurr[cl][0] ~= nil then
str = '0:' .. occurr[cl][0] .. ','
end
for k,v in ipairs(occurr[cl]) do
if k == 20 then k = '>19' end
str = str .. k .. ':' .. v .. ','
end
table.insert(occ_distr, str)
else
redis.call('DEL', occurr_key)
end
if next(occurr[cl]) ~= nil then
redis.call('HMSET', occurr_key, unpack_function(hash2list(occurr[cl])))
end
end
return {
next_cursor, step,
{nelts, extended, discriminated, mean, stddev, common, significant, infrequent,
infrequent_ttls_set, insignificant, insignificant_ttls_set},
{c.nelts, c.extended, c.discriminated, c.sum, c.sum_squares, c.common,
c.significant, c.infrequent, c.infrequent_ttls_set, c.insignificant, c.insignificant_ttls_set},
occ_distr
}
]]
local function expire_step(cls, ev_base, worker)
local function redis_step_cb(err, args)
if err then
logger.errx(rspamd_config, 'cannot perform expiry step: %s', err)
elseif type(args) == 'table' then
local cur = tonumber(args[1])
local step = args[2]
local data = args[3]
local c_data = args[4]
local occ_distr = args[5]
local function log_stat(cycle)
local infrequent_action = (cls.expiry < 0) and 'made persistent' or 'ttls set'
local c_mean, c_stddev = 0, 0
if cycle and c_data[1] ~= 0 then
c_mean = c_data[4] / c_data[1]
c_stddev = math.floor(.5 + math.sqrt(c_data[5] / c_data[1] - c_mean * c_mean))
c_mean = math.floor(.5 + c_mean)
end
local d = cycle and {
'cycle in ' .. step .. ' steps', c_data[1],
c_data[7], c_data[2], 'made persistent',
c_data[10], c_data[11], infrequent_action,
c_data[6], c_data[3],
c_data[8], c_data[9], infrequent_action,
c_mean,
c_stddev
} or {
'step ' .. step, data[1],
data[7], data[2], 'made persistent',
data[10], data[11], infrequent_action,
data[6], data[3],
data[8], data[9], infrequent_action,
data[4],
data[5]
}
logger.infox(rspamd_config,
'finished expiry %s: %s items checked, %s significant (%s %s), ' ..
'%s insignificant (%s %s), %s common (%s discriminated), ' ..
'%s infrequent (%s %s), %s mean, %s std',
lutil.unpack(d))
if cycle then
for i,cl in ipairs({'in ham', 'in spam', 'total'}) do
logger.infox(rspamd_config, 'tokens occurrences, %s: {%s}', cl, occ_distr[i])
end
end
end
log_stat(false)
if cur == 0 then
log_stat(true)
end
elseif type(args) == 'string' then
logger.infox(rspamd_config, 'skip expiry step: %s', args)
end
end
lredis.exec_redis_script(cls.script,
{ev_base = ev_base, is_write = true},
redis_step_cb,
{'RS*_*', cls.expiry}
)
end
rspamd_config:add_on_load(function (_, ev_base, worker)
-- Exit unless we're the first 'controller' worker
if not worker:is_primary_controller() then return end
local unique_redis_params = {}
-- Push redis script to all unique redis servers
for _,cls in ipairs(settings.classifiers) do
if not unique_redis_params[cls.redis_params.hash] then
unique_redis_params[cls.redis_params.hash] = cls.redis_params
end
end
for h,rp in pairs(unique_redis_params) do
local script_id = lredis.add_redis_script(lutil.template(expiry_script,
template), rp)
for _,cls in ipairs(settings.classifiers) do
if cls.redis_params.hash == h then
cls.script = script_id
end
end
end
-- Expire tokens at regular intervals
for _,cls in ipairs(settings.classifiers) do
rspamd_config:add_periodic(ev_base,
settings['interval'],
function ()
expire_step(cls, ev_base, worker)
return true
end, true)
end
end)
|