[Minor] Neural: Extract lua scripts

.luacheckrc

@@ -63,6 +63,7 @@ files['/**/lualib/lua_redis.lua'].globals = {
 files['/**/lualib/redis_scripts/**'].globals = {
   'redis',
   'KEYS',
+  'cjson',
 }
 
 files['/**/src/rspamadm/*'].globals = {

lualib/plugins/neural.lua

@@ -96,113 +96,22 @@ local module_config = rspamd_config:get_all_opt(N)
 settings = lua_util.override_defaults(settings, module_config)
 local redis_params = lua_redis.parse_redis_server('neural')
 
-local redis_lua_script_vectors_len = [[
-  local prefix = KEYS[1]
-  local locked = redis.call('HGET', prefix, 'lock')
-  if locked then
-    local host = redis.call('HGET', prefix, 'hostname') or 'unknown'
-    return string.format('%s:%s', host, locked)
-  end
-  local nspam = 0
-  local nham = 0
-
-  local ret = redis.call('SCARD', prefix .. '_spam_set')
-  if ret then nspam = tonumber(ret) end
-  ret = redis.call('SCARD', prefix .. '_ham_set')
-  if ret then nham = tonumber(ret) end
-
-  return {nspam,nham}
-]]
-
-local redis_lua_script_maybe_invalidate = [[
-  local card = redis.call('ZCARD', KEYS[1])
-  local lim = tonumber(KEYS[2])
-  if card > lim then
-    local to_delete = redis.call('ZRANGE', KEYS[1], 0, card - lim - 1)
-    if to_delete then
-      for _,k in ipairs(to_delete) do
-        local tb = cjson.decode(k)
-        if type(tb) == 'table' and type(tb.redis_key) == 'string' then
-          redis.call('DEL', tb.redis_key)
-          -- Also train vectors
-          redis.call('DEL', tb.redis_key .. '_spam_set')
-          redis.call('DEL', tb.redis_key .. '_ham_set')
-        end
-      end
-    end
-    redis.call('ZREMRANGEBYRANK', KEYS[1], 0, card - lim - 1)
-    return to_delete
-  else
-    return {}
-  end
-]]
-
-local redis_lua_script_maybe_lock = [[
-  local locked = redis.call('HGET', KEYS[1], 'lock')
-  local now = tonumber(KEYS[2])
-  if locked then
-    locked = tonumber(locked)
-    local expire = tonumber(KEYS[3])
-    if now > locked and (now - locked) < expire then
-      return {tostring(locked), redis.call('HGET', KEYS[1], 'hostname') or 'unknown'}
-    end
-  end
-  redis.call('HSET', KEYS[1], 'lock', tostring(now))
-  redis.call('HSET', KEYS[1], 'hostname', KEYS[4])
-  return 1
-]]
-
-local redis_lua_script_save_unlock = [[
-  local now = tonumber(KEYS[6])
-  redis.call('ZADD', KEYS[2], now, KEYS[4])
-  redis.call('HSET', KEYS[1], 'ann', KEYS[3])
-  redis.call('DEL', KEYS[1] .. '_spam_set')
-  redis.call('DEL', KEYS[1] .. '_ham_set')
-  redis.call('HDEL', KEYS[1], 'lock')
-  redis.call('HDEL', KEYS[7], 'lock')
-  redis.call('EXPIRE', KEYS[1], tonumber(KEYS[5]))
-  redis.call('HSET', KEYS[1], 'roc_thresholds', KEYS[8])
-  if KEYS[9] then
-    redis.call('HSET', KEYS[1], 'pca', KEYS[9])
-  end
-  return 1
-]]
+
+local redis_lua_script_vectors_len = "neural_train_size.lua"
+local redis_lua_script_maybe_invalidate = "neural_maybe_invalidate.lua"
+local redis_lua_script_maybe_lock = "neural_maybe_lock.lua"
+local redis_lua_script_save_unlock = "neural_save_unlock.lua"
 
 local redis_script_id = {}
 
 local function load_scripts()
-  redis_script_id.vectors_len = lua_redis.add_redis_script(redis_lua_script_vectors_len,
+  redis_script_id.vectors_len = lua_redis.load_redis_script_from_file(redis_lua_script_vectors_len,
     redis_params)
-  redis_script_id.maybe_invalidate = lua_redis.add_redis_script(redis_lua_script_maybe_invalidate,
+  redis_script_id.maybe_invalidate = lua_redis.load_redis_script_from_file(redis_lua_script_maybe_invalidate,
     redis_params)
-  redis_script_id.maybe_lock = lua_redis.add_redis_script(redis_lua_script_maybe_lock,
+  redis_script_id.maybe_lock = lua_redis.load_redis_script_from_file(redis_lua_script_maybe_lock,
     redis_params)
-  redis_script_id.save_unlock = lua_redis.add_redis_script(redis_lua_script_save_unlock,
+  redis_script_id.save_unlock = lua_redis.load_redis_script_from_file(redis_lua_script_save_unlock,
     redis_params)
 end
 

lualib/redis_scripts/neural_maybe_invalidate.lua

@@ -0,0 +1,25 @@
+-- Lua script to invalidate ANNs by rank
+-- Uses the following keys
+-- key1 - prefix for keys
+-- key2 - number of elements to leave
+
+local card = redis.call('ZCARD', KEYS[1])
+local lim = tonumber(KEYS[2])
+if card > lim then
+  local to_delete = redis.call('ZRANGE', KEYS[1], 0, card - lim - 1)
+  if to_delete then
+    for _,k in ipairs(to_delete) do
+      local tb = cjson.decode(k)
+      if type(tb) == 'table' and type(tb.redis_key) == 'string' then
+        redis.call('DEL', tb.redis_key)
+        -- Also train vectors
+        redis.call('DEL', tb.redis_key .. '_spam_set')
+        redis.call('DEL', tb.redis_key .. '_ham_set')
+      end
+    end
+  end
+  redis.call('ZREMRANGEBYRANK', KEYS[1], 0, card - lim - 1)
+  return to_delete
+else
+  return {}
+end

lualib/redis_scripts/neural_maybe_lock.lua

@@ -0,0 +1,19 @@
+-- Lua script lock ANN for learning
+-- Uses the following keys
+-- key1 - prefix for keys
+-- key2 - current time
+-- key3 - key expire
+-- key4 - hostname
+
+local locked = redis.call('HGET', KEYS[1], 'lock')
+local now = tonumber(KEYS[2])
+if locked then
+  locked = tonumber(locked)
+  local expire = tonumber(KEYS[3])
+  if now > locked and (now - locked) < expire then
+    return {tostring(locked), redis.call('HGET', KEYS[1], 'hostname') or 'unknown'}
+  end
+end
+redis.call('HSET', KEYS[1], 'lock', tostring(now))
+redis.call('HSET', KEYS[1], 'hostname', KEYS[4])
+return 1

lualib/redis_scripts/neural_save_unlock.lua

@@ -0,0 +1,24 @@
+-- Lua script to save and unlock ANN in redis
+-- Uses the following keys
+-- key1 - prefix for ANN
+-- key2 - prefix for profile
+-- key3 - compressed ANN
+-- key4 - profile as JSON
+-- key5 - expire in seconds
+-- key6 - current time
+-- key7 - old key
+-- key8 - ROC Thresholds
+-- key9 - optional PCA
+local now = tonumber(KEYS[6])
+redis.call('ZADD', KEYS[2], now, KEYS[4])
+redis.call('HSET', KEYS[1], 'ann', KEYS[3])
+redis.call('DEL', KEYS[1] .. '_spam_set')
+redis.call('DEL', KEYS[1] .. '_ham_set')
+redis.call('HDEL', KEYS[1], 'lock')
+redis.call('HDEL', KEYS[7], 'lock')
+redis.call('EXPIRE', KEYS[1], tonumber(KEYS[5]))
+redis.call('HSET', KEYS[1], 'roc_thresholds', KEYS[8])
+if KEYS[9] then
+  redis.call('HSET', KEYS[1], 'pca', KEYS[9])
+end
+return 1

lualib/redis_scripts/neural_train_size.lua

@@ -0,0 +1,20 @@
+-- Lua script that checks if we can store a new training vector
+-- Uses the following keys:
+-- key1 - ann key
+-- returns nspam,nham (or nil if locked)
+
+local prefix = KEYS[1]
+local locked = redis.call('HGET', prefix, 'lock')
+if locked then
+  local host = redis.call('HGET', prefix, 'hostname') or 'unknown'
+  return string.format('%s:%s', host, locked)
+end
+local nspam = 0
+local nham = 0
+
+local ret = redis.call('SCARD', prefix .. '_spam_set')
+if ret then nspam = tonumber(ret) end
+ret = redis.call('SCARD', prefix .. '_ham_set')
+if ret then nham = tonumber(ret) end
+
+return {nspam,nham}