modules/predict: turn off prediction by setting empty period

modules/predict/README.rst

@@ -28,6 +28,8 @@ Example configuration
 
 Defaults are 15 minutes window, 6 hours period.
 
+.. tip:: Use period 0 to turn off prediction and just do prefetching of expiring records.
+
 Exported metrics
 ^^^^^^^^^^^^^^^^
 

modules/predict/predict.lua

 -- Speculative prefetching for repetitive and soon-expiring records to reduce latency.
 -- @module predict
--- @field queue table of scheduled records
--- @field queue_max maximum length of the queue
--- @field window length of the coalescing window
+-- @field queue queue of scheduled queries
+-- @field queue_len number of scheduled queries
+-- @field period length of prediction history (number of windows)
+-- @field window length of the prediction window
 local predict = {
 	queue = {},
 	queue_len = 0,
 	batch = 0,
-	epoch = 0,
 	period = 24,
 	window = 15,
 	log = {},
@@ -15,6 +15,7 @@ local predict = {
 
 -- Calculate current epoch (which window fits current time)
 local function current_epoch()
+	if not predict.period or predict.period <= 1 then return nil end
 	return (os.date('%H')*(60/predict.window) +
 		math.floor(os.date('%M')/predict.window)) % predict.period + 1
 end
@@ -70,7 +71,7 @@ end
 
 -- Sample current epoch, return number of sampled queries
 function predict.sample(epoch_now)
-	if not epoch_now then return end
+	if not epoch_now then return 0, 0 end
 	local queries = stats.frequent()
 	stats.clear_frequent()
 	local queued = 0
@@ -93,6 +94,7 @@ end
 
 -- Predict queries for the upcoming epoch
 local function generate(epoch_now)
+	if not epoch_now then return 0 end
 	local queued = 0
 	local period = predict.period + 1
 	for i = 1, predict.period / 2 - 1 do
@@ -110,7 +112,6 @@ local function generate(epoch_now)
 	return queued
 end
 
--- Process current epoch
 function predict.process(ev)
 	-- Start a new epoch, or continue sampling
 	predict.ev_sample = nil
@@ -118,6 +119,7 @@ function predict.process(ev)
 	local nr_learned, nr_queued = predict.sample(epoch_now)
 	-- End of epoch, predict next
 	if predict.epoch ~= epoch_now then
+		stats['predict.epoch'] = epoch_now
 		predict.epoch = epoch_now
 		nr_queued = nr_queued + generate(epoch_now)
 	end
@@ -132,14 +134,13 @@ function predict.process(ev)
 		end
 	end
 	predict.ev_sample = event.after(next_event(), predict.process)
-	stats['predict.epoch'] = epoch_now
 	stats['predict.queue'] = predict.queue_len
 	stats['predict.learned'] = nr_learned
 	collectgarbage()
 end
 
 function predict.init(module)
-	if predict.window > 0 and predict.period > 0 then
+	if predict.window > 0 then
 		predict.epoch = current_epoch()
 		predict.ev_sample = event.after(next_event(), predict.process)
 	end