end
local function gen_learn_functor(redis_params, learn_script_id)
- return function(task, expanded_key, id, is_spam, stat_tokens, callback)
- -- TODO: write this function
+ return function(task, expanded_key, id, is_spam, symbol, is_unlearn, stat_tokens, callback)
+ local function learn_redis_cb(err, data)
+ lua_util.debugm(N, task, 'learn redis cb: %s, %s', err, data)
+ if err then
+ callback(task, false, err)
+ else
+ callback(task, true)
+ end
+ end
+
+ lua_redis.exec_redis_script(learn_script_id,
+ { task = task, is_write = false, key = expanded_key },
+ learn_redis_cb, { expanded_key, is_spam, symbol, is_unlearn, stat_tokens })
end
end
--- /dev/null
+-- Lua script to perform bayes learning
+-- This script accepts the following parameters:
+-- key1 - prefix for bayes tokens (e.g. for per-user classification)
+-- key2 - boolean is_spam
+-- key3 - string symbol
+-- key4 - boolean is_unlearn
+-- key5 - set of tokens encoded in messagepack array of int64_t
+
+local prefix = KEYS[1]
+local is_spam = KEYS[2]
+local symbol = KEYS[3]
+local is_unlearn = KEYS[4]
+local input_tokens = cmsgpack.unpack(KEYS[5])
+
+local prefix_underscore = prefix .. '_'
+local hash_key = is_spam and 'S' or 'H'
+local learned_key = is_spam and 'learns_spam' or 'learns_ham'
+
+redis.call('SADD', symbol .. '_keys', prefix)
+redis.call('HSET', prefix, 'version', '2') -- new schema
+redis.call('HINCRBY', prefix, learned_key, is_unlearn and -1 or 1) -- increase or decrease learned count
+
+for _, token in ipairs(input_tokens) do
+ redis.call('HINCRBY', prefix_underscore .. tostring(token), hash_key, 1)
+end
\ No newline at end of file