From c3d899867b26192562d9e4797e09f73842df241d Mon Sep 17 00:00:00 2001
From: Ebus-at-dockstar <ebus@dockstar>
Date: Fri, 8 Mar 2013 01:46:12 +0100
Subject: flush every 30sec

---
 ebus/webhdf/__init__.py | 23 ++++++++++++++++++-----
 1 file changed, 18 insertions(+), 5 deletions(-)

(limited to 'ebus/webhdf')

diff --git a/ebus/webhdf/__init__.py b/ebus/webhdf/__init__.py
index c1f34dd..f661800 100644
--- a/ebus/webhdf/__init__.py
+++ b/ebus/webhdf/__init__.py
@@ -14,9 +14,10 @@ import bottle
 import ebus.datastore
 
 datastore = ebus.datastore.Datastore("hdf-data")
-
 app = bottle.Bottle("ebus")
 
+lastflush = -1
+
 @app.route('/')
 def index_file():
     return static_files("index.html")
@@ -39,6 +40,9 @@ def sensor_data_get(name):
 @app.put('/sensor/:name')
 @app.put('/sensor/:name/:timestamp')
 def sensor_data_put(name,timestamp=None):
+    FLUSH_INTERVAL=30 #sec
+    global lastflush
+
     if not timestamp: timestamp = int(time.time())
     try:
         value = bottle.request.POST.value
@@ -55,9 +59,16 @@ def sensor_data_put(name,timestamp=None):
         else:
             return {'error':'INVALID_TYPE', msg:'Type {0} is invalid'.format(type)}
 
-        datastore.addValue(name, timestamp, value, klass, flush=True)
-	msg = "Stored {0} of type {1} with timestamp {2} to {3}".format(value,type,timestamp,name)
+	msg = "Storing {0} of type {1} with timestamp {2} to {3}".format(value,type,timestamp,name)
 	logging.info(msg)
+
+        datastore.addValue(name, timestamp, value, klass, flush=False)
+
+        if time.time() - FLUSH_INTERVAL > lastflush:
+	    logging.info("call datastore.flush()")
+            datastore.flush()
+	    lastflush = time.time()
+
         return {'error':None,'msg':msg}
     except Exception,e:
 	logging.error("Error: " + "{0} name={1} value={2} type={3}".format(e, name, value, type))
@@ -68,6 +79,7 @@ def sensor_data_put(name,timestamp=None):
 @app.route('/sensor/:name/:startdate/:enddate')
 def sensor_name_start_end(name,startdate,enddate):
     SAMPLING_STEPSIZE=500
+    NUMBER_OF_VALUES=250
     try:
         startdate, enddate = int(startdate), int(enddate)
 	logging.info("/sensor/ start={0} end={1}".format(startdate, enddate))
@@ -88,7 +100,7 @@ def sensor_name_start_end(name,startdate,enddate):
 		    diff_avg = numpy.average(diff)
 		    time_period = enddate - startdate
 		    samples = time_period / diff_avg
-		    step = numpy.ceil(samples / 400.0)
+		    step = numpy.ceil(samples / float(NUMBER_OF_VALUES))
 
 		    data = [(x['timestamp'], x['value']) 
 			    for x in table.where("(timestamp >= startdate) & (timestamp <= enddate)", step=step)]
@@ -104,12 +116,13 @@ def sensor_name_start_end(name,startdate,enddate):
 @app.route('/avg/:name/:startdate')
 @app.route('/avg/:name/:startdate/:period')
 def sensor_avg_start(name, startdate, period=60*15): #15min
+    AVG_STEPSIZE=50
     try:
         startdate, enddate = int(startdate), int(time.time())
 	logging.info("/avg/ start={0} end={1}".format(startdate, enddate))
         table=datastore.getTable(name)
         with datastore:
-            sel_rows = table.where("(timestamp >= startdate) & (timestamp <=enddate)")
+            sel_rows = table.where("(timestamp >= startdate) & (timestamp <=enddate)", step=AVG_STEPSIZE)
             f_group = range(startdate, enddate, period)
             data = map(lambda (group_id, grouped_rows): (group_id, numpy.average([row['value'] for row in grouped_rows])),
                     itertools.groupby(sel_rows, lambda t: (t['timestamp']/period)*period))
-- 
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