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Commit d1415305 authored by chad.hanna's avatar chad.hanna
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gstlal_data_server: new dataserver code

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gstlal-ugly/share/dataserver/gstlal_data_server_latest_by_job → gstlal-ugly/share/dataserver/gstlal_data_server
+ 216
− 182
View file @ d1415305
......@@ -47,17 +47,29 @@ def parse_form(form):
if "type" in form:
datatype = form["type"]
datatype = form["type"][0]
else:
datatype = "max"
# FIXME don't hard code, get from URL
#base_path = "/home/gstlalcbctest/engineering/10/S6/bns"
#jobdirs = ["by_job/%04d" % i for i in range(10)]
base_path = "/home/gstlalcbc/observing/2/online/trigs"
jobdirs = ["by_job/%04d" % i for i in range(182)]
if "id" in form:
idstart, idend = [int(i) for i in form["id"][0].split(",")]
else:
idstart = 0
idend = 32
if "dir" in form:
base_path = form["dir"][0]
else:
base_path = "/home/gstlalcbc/observing/3/online/sept_opa/trigs"
return reqId, query, query_time, duration, datatype, base_path, jobdirs
if "ifos" in form:
ifos = form["ifos"][0].split(",")
else:
ifos = ["H1", "L1", "V1"]
jobdirs = ["by_job/%04d" % i for i in range(idstart, idend+1)]
return reqId, query, query_time, duration, datatype, base_path, jobdirs, ifos
def gps_by_level(t, level):
......@@ -86,7 +98,7 @@ print "Cache-Control: max-age=10"
print
reqId, query, query_time, duration, datatype, base_path, jobdirs = parse_form(form)
reqId, query, query_time, duration, datatype, base_path, jobdirs, ifos = parse_form(form)
#
# "SQL" parser. FIXME. First, google query langauge isn't really SQL and
......@@ -106,12 +118,9 @@ def read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs
try:
fname = "%s/%s/%s/%s/%s/%s.hdf5" % (base_path, rootdir, partial_path, jobdir, datatype, route)
f = h5py.File(fname, "r")
#this_data = numpy.hstack((this_data, numpy.array(f["data"])))
#this_time = numpy.hstack((this_time, numpy.array(f["time"])))
this_data = numpy.hstack((numpy.array(f["data"]), this_data))
this_time = numpy.hstack((numpy.array(f["time"]), this_time))
f.close()
#print fname, len(this_data), len(this_time)
except IOError:
pass
# refuse to look back more than 100 directories and stop once you have enough data
......@@ -132,55 +141,112 @@ def read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs
# latency, SNR, FAR, likelihood
#
def stats_by_node(routes, query_time, duration, base_path, jobdirs, thisdatatype):
data = {}
for ifo, thisroute in routes:
# get the max time and the stats on the data
data[ifo] = [(max(x[1]), x[0].split("/")[-1], stats_on_data(x[2])) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = thisdatatype)]
description = [("job", "string")]
for ifo in routes:
if ifo == "":
ifo = "combined"
thisdesc = [
("%s %d" % (ifo, float(max(data["%s_" % ifo])[0]), "number")),
("", "number"),
("", "number"),
("", "number")
]
description.extend(thisdesc)
data_table = gviz_api.DataTable(description)
thisdata = []
for tup in zip(*[data[k] for k in routes]):
row = [tup[0][1]]
for t in tup[1:]:
row += list(t[2])
thisdata.append(row)
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
def status_by_node(routes, query_time, duration, base_path, jobdirs, thisdatatype):
data = {}
description = [("job", "string")]
ifostrs = [x[0] for x in routes]
for (ifo, thisroute) in routes:
thisroute = "%s%s" % (ifo, route)
# get the max time and the stats on the data
data[ifo] = [(float(x[1][-1]), x[0].split("/")[-1], float(x[2][-1])) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = thisdatatype)]
description.append(("%s %d" % (ifo, float(max(data[ifo])[0])), "number"))
data_table = gviz_api.DataTable(description)
thisdata = []
for tup in zip(*[data[k] for (k,_) in routes]):
row = [tup[0][1]]
for t in tup:
row += [t[2]]
thisdata.append(row)
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
def node_is_all(route, query_time, duration, base_path, jobdirs, thisdatatype):
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = thisdatatype).next()
out_data = [[float(t),float(d)] for t,d in zip(this_time, this_data)]
description = [("time", "number"), ("%d" % float(this_time[-1]), "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "time", req_id = reqId)
sys.exit()
def nodes_now(route, query_time, duration, base_path, jobdirs, thisdatatype):
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = thisdatatype).next()
description = [(label, "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData([[float(this_data[-1])]])
print data_table.ToJSonResponse(req_id = reqId)
sys.exit()
def scatter_by_node(routes, query_time, duration, base_path, jobdirs, thisdatatype):
data = {}
description = [("time", "number")]
ifostrs = [x[0] for x in routes]
#print routes, query_time, duration
for (ifo, thisroute) in routes:
# get the max time and the stats on the data
data[ifo] = [(x[1], x[0].split("/")[-1], x[2], x[1][-1]) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = thisdatatype)]
description.append((ifo, "number"))
data_table = gviz_api.DataTable(description)
thisdata = []
#FIXME make tootips bin number
tmp = []
for ifo in ifostrs:
tmp += [data[ifo][0][0],data[ifo][0][2]]
for tup in zip(*tmp):
row = [float(tup[0])]
for n in range(len(tup) / 2):
row += [float(tup[1+2*n])]
thisdata.append(row)
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
for route, label, thisdatatype in (("latency_history", "Latency (s)", "max"), ("far_history", "FAR (Hz)", "min"), ("likelihood_history", "L", "max")):
if route in query:
if "stats by node" in query:
# get the max time and the stats on the data
data = [(max(x[1]), x[0].split("/")[-1], stats_on_data(x[2])) for x in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs, datatype = thisdatatype)]
description = [
("job", "string"),
("%d" % float(max(data)[0]), "number"),
("j", "number"),
("", "number"),
("", "number")
]
data_table = gviz_api.DataTable(description)
data_table.LoadData([[x[1]]+list(x[2]) for x in data])
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
stats_by_node([("", route)], query_time, duration, base_path, jobdirs, thisdatatype)
if "status by node" in query:
# get the max time and the stats on the data
data = [(float(x[1][-1]), x[0].split("/")[-1], float(x[2][-1])) for x in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs, datatype = thisdatatype)]
description = [
("job", "string"),
("%d" % float(max(data)[0]), "number")
]
data_table = gviz_api.DataTable(description)
data_table.LoadData([[x[1], x[2]] for x in data])
print [[x[1], x[2]] for x in data]
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
status_by_node([("", route)], query_time, duration, base_path, jobdirs, thisdatatype)
if "where node is all" in query:
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = thisdatatype).next()
out_data = [[float(t),float(d)] for t,d in zip(this_time, this_data)]
description = [("time", "number"), ("%d" % float(this_time[-1]), "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "time", req_id = reqId)
sys.exit()
node_is_all(route, query_time, duration, base_path, jobdirs, thisdatatype)
if "now" in query:
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = thisdatatype).next()
description = [(label, "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData([[float(this_data[-1])]])
print data_table.ToJSonResponse(req_id = reqId)
sys.exit()
nodes_now(route, query_time, duration, base_path, jobdirs, thisdatatype)
#
# SNR history is special
......@@ -189,93 +255,28 @@ for route, label, thisdatatype in (("latency_history", "Latency (s)", "max"), ("
for route, label in (("snr_history", "SNR"),):
if route in query:
ifostrs = ["%s_" % ifo for ifo in ifos] + [""]
routes = [(ifo, "%s%s" %(ifo, route)) for ifo in ifostrs]
if "stats by node" in query:
data = {}
for ifo in ("", "H1_", "L1_"):
thisroute = "%s%s" % (ifo, route)
# get the max time and the stats on the data
data[ifo] = [(max(x[1]), x[0].split("/")[-1], stats_on_data(x[2])) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = "max")]
description = [
("job", "string"),
("H1 %d" % float(max(data["H1_"])[0]), "number"),
("", "number"),
("", "number"),
("", "number"),
("L1 %d" % float(max(data["L1_"])[0]), "number"),
("", "number"),
("", "number"),
("", "number"),
("combined %d" % float(max(data[""])[0]), "number"),
("", "number"),
("", "number"),
("", "number")
]
data_table = gviz_api.DataTable(description)
thisdata = [[x[1]] + list(x[2]) + list(y[2]) + list(z[2]) for x,y,z in zip(data["H1_"], data["L1_"], data[""])]
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
stats_by_node(routes, query_time, duration, base_path, jobdirs, "max")
if "status by node" in query:
data = {}
for ifo in ("", "H1_", "L1_"):
thisroute = "%s%s" % (ifo, route)
# get the max time and the stats on the data
data[ifo] = [(float(x[1][-1]), x[0].split("/")[-1], float(x[2][-1])) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = "max")]
description = [
("job", "string"),
("H1 %d" % float(max(data["H1_"])[0]), "number"),
("L1 %d" % float(max(data["L1_"])[0]), "number"),
("combined %d" % float(max(data[""])[0]), "number")
]
data_table = gviz_api.DataTable(description)
thisdata = [ [x[1], x[2], y[2], z[2]] for x,y,z in zip(data["H1_"], data["L1_"], data[""])]
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
status_by_node(routes, query_time, duration, base_path, jobdirs, "max")
if "scatter by node" in query:
data = {}
for ifo in ("", "H1_", "L1_"):
thisroute = "%s%s" % (ifo, route)
# get the max time and the stats on the data
#data[ifo] = [(x[1], x[0].split("/")[-1], x[2], x[1][-1]) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = "max")]
data[ifo] = [(x[1], x[0].split("/")[-1], x[2], x[1][-1]) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, [""], datatype = "max")]
description = [
("time", "number"),
("H1", "number"),
("L1", "number")
]
data_table = gviz_api.DataTable(description)
thisdata = []
#FIXME make tootips bin number
for (this_time, this_job, this_data, max_time) in data["H1_"]:
thisdata.extend([[float(t),float(d),None] for t,d in zip(this_time, this_data)])
for (this_time, this_job, this_data, max_time) in data["L1_"]:
thisdata.extend([[float(t),None,float(d)] for t,d in zip(this_time, this_data)])
data_table.LoadData(thisdata)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
# FIXME for some reason when we include [""], which is
# the combined SNR, it only shows the history up to a
# few thousand seconds old... Maybe make a separtate
# network SNR plot?
ifostrs = ["%s_" % ifo for ifo in ifos]
routes = [(ifo, "%s%s" %(ifo, route)) for ifo in ifostrs]
scatter_by_node(routes, query_time, duration, base_path, [""], "max")
if "where node is all" in query:
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = "max").next()
out_data = [[float(t),float(d)] for t,d in zip(this_time, this_data)]
description = [("time", "number"), ("%d" % float(this_time[-1]), "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "time", req_id = reqId)
sys.exit()
node_is_all(route, query_time, duration, base_path, [""], "max")
if "now" in query:
_, this_time, this_data = read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = [""], datatype = "max").next()
description = [(label, "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData([[float(this_data[-1])]])
print data_table.ToJSonResponse(req_id = reqId)
sys.exit()
nodes_now(route, query_time, duration, base_path, [""], "max")
#
......@@ -286,28 +287,22 @@ for route, x, y, units in (("horizon_history", "time", "horizon", "(Mpc)"), ("no
if route in query:
latest = {}
if "now" in query:
for ifo, this_time, this_data in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = ["H1", "L1"], rootdir = "dq", datatype = "max"):
for ifo, this_time, this_data in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = ifos, rootdir = "dq", datatype = "max"):
latest[ifo] = float(this_time[-1]), float(this_data[-1])
# convert to range
out_data = [[float(latest["H1"][1])/2.25, float(latest["L1"][1])/2.25]]
description = [
("H1 %s" % (units,), "number"),
("L1 %s" % (units,), "number")
]
out_data = [[float(latest[ifo][1]) / 2.25 for ifo in ifos]]
description = [("%s %s" % (ifo, units), "number") for ifo in ifos]
else:
out_data = []; H1L1time = {}; H1L1data = {}
out_data = []; IFOtime = {}; IFOdata = {}
# FIXME don't harcode
for ifo, this_time, this_data in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = ["H1", "L1"], rootdir = "dq", datatype = "max"):
for ifo, this_time, this_data in read_aggregated_data_by_job(route, query_time, duration, base_path, jobdirs = ifos, rootdir = "dq", datatype = "max"):
# convert to range
H1L1data[ifo] = interp1d(this_time, this_data / 2.25, kind = "nearest", bounds_error = False, fill_value=0.)
H1L1time[ifo] = this_time
for t in numpy.sort(numpy.hstack((H1L1time["H1"], H1L1time["L1"]))):
out_data.append([float(t), float(H1L1data["H1"](t)), float(H1L1data["L1"](t))])
description = [
(x, "number"),
("H1 %s @ %d" % (units, float(H1L1time["H1"][-1])), "number"),
("L1 %s @ %d" % (units, float(H1L1time["L1"][-1])), "number")
]
IFOdata[ifo] = interp1d(this_time, this_data / 2.25, kind = "nearest", bounds_error = False, fill_value=0.)
IFOtime[ifo] = this_time
for t in numpy.sort(numpy.hstack([IFOtime[i] for i in ifos])):
out_data.append([float(t)] + [float(IFOdata[ifo](t)) for ifo in ifos])
description = [(x, "number")]
description.extend([("%s %s @ %d" % (ifo, units, float(IFOtime[ifo][-1])), "number") for ifo in ifos])
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
......@@ -323,7 +318,7 @@ for route, label in (("_state_vector_on_off_gap", "(s)"), ("_strain_add_drop", "
out_data = []
if "status by node" in query:
jobs = []; this_time = {}; this_data = {};
for ifo in ("H1", "L1"):
for ifo in ifos:
for job, t, d in read_aggregated_data_by_job("%s%s" % (ifo, route), None, None, base_path, jobdirs = jobdirs, rootdir = "aggregator", datatype = ""):
this_time.setdefault(ifo, []).append(t[-1])
this_data.setdefault(ifo, []).append(d[-1])
......@@ -331,13 +326,24 @@ for route, label in (("_state_vector_on_off_gap", "(s)"), ("_strain_add_drop", "
# FIXME the 16 comes from the 16 Hz sample rate
# used for state vectors in ALIGO. if that
# changes this needs to change too
for job, H1d, L1d in zip(jobs, this_data["H1"], this_data["L1"]):
out_data.append([job, H1d / 16., L1d/ 16.])
description = [
("job", "string"),
("H1 %d" % float(max(this_time["H1"])), "number"),
("L1 %d" % float(max(this_time["L1"])), "number"),
]
tmp = [jobs] + [this_data[ifo] for ifo in ifos]
# HACK for virgo sample rate being different
if "V1" in ifos:
V1idx = ifos.index("V1")
else:
V1idx = -1
for tup in zip(*tmp):
row = [tup[0]]
for idx, t in enumerate(tup[1:]):
if idx == V1idx:
row += [t]
else:
row += [t / 16.]
out_data.append(row)
description = [("job", "string")]
for ifo in ifos:
tmp = "%s %d" % (ifo, float(max(this_time[ifo])))
description.append((tmp, "number"))
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
......@@ -345,13 +351,16 @@ for route, label in (("_state_vector_on_off_gap", "(s)"), ("_strain_add_drop", "
if "now" in query:
minuptime = 10000000.
for ifo in ("H1", "L1"):
for ifo in ifos:
for job, t, d in read_aggregated_data_by_job("%s%s" % (ifo, route), None, None, base_path, jobdirs = jobdirs, rootdir = "aggregator", datatype = ""):
# FIXME the 16 comes from the 16 Hz sample rate
# used for state vectors in ALIGO. if that
# changes this needs to change too
# FIXME return hours for this query because google gauges don't support axis transformations
minuptime = min(minuptime, float(d[-1]/16.)/3600. )
if ifo != "V1":
minuptime = min(minuptime, float(d[-1]/16.) / 3600.)
else:
minuptime = min(minuptime, float(d[-1]) / 3600.)
out_data.append([minuptime])
description = [
("uptime (h)", "number")
......@@ -416,11 +425,11 @@ if "time_since_last" in query:
#
freq = numpy.array([])
datadict = {"H1": numpy.array([]), "L1": numpy.array([])}
datadict = dict((ifo, numpy.array([])) for ifo in ifos)
out_data = []
lowestdir = gps_by_level(query_time, 6)
if "psd" in query:
for ifo in ("H1", "L1"):
for ifo in ifos:
if "now" in query:
fname = "%s/dq/%s/psd.hdf5" % (base_path, ifo)
else:
......@@ -436,37 +445,45 @@ if "psd" in query:
psd_time = 0
pass
# FIXME don't harcode
for f, H1asd, L1asd in zip(freq, datadict["H1"], datadict["L1"]):
out_data.append([float(f), float(H1asd), float(L1asd)])
description = [
("freq", "number"),
("H1 ASD @ %d" % psd_time, "number"),
("L1 ASD @ %d" % psd_time, "number")
]
tmp = [freq]
tmp.extend([datadict[ifo] for ifo in ifos])
for tup in zip(*tmp):
row = [float(tup[0])]
for t in tup[1:]:
row += [float(t)]
out_data.append(row)
description = [("freq", "number")]
for ifo in ifos:
description.append(("%s ASD @ %d" % (ifo, psd_time), "number"))
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(req_id = reqId)
if "time_since_trigger" in query:
route = "snr_history"
data = {}
nowtime = now()
for ifo in ("", "H1_", "L1_"):
ifostrs = ["%s_" % ifo for ifo in ifos] + [""]
for ifo in ifostrs:
thisroute = "%s%s" % (ifo, route)
# get the max time and the stats on the data
data[ifo] = [(float(max(x[1])), x[0].split("/")[-1]) for x in read_aggregated_data_by_job(thisroute, query_time, duration, base_path, jobdirs, datatype = "max", age = 1e6)]
print data["H1_"]
description = [
("job", "string"),
("H1 %d" % float(max(data["H1_"])[0]), "number"),
("L1 %d" % float(max(data["L1_"])[0]), "number"),
("combined %d" % float(max(data[""])[0]), "number"),
]
description = [("job", "string")]
for ifo in ifos:
description.append(("%s %d" % (ifo, float(max(data["%s_" % ifo])[0])), "number"))
description.append(("combined %d" % float(max(data[""])[0]), "number"))
data_table = gviz_api.DataTable(description)
thisdata = [[x[1]] + [nowtime - x[0]] + [nowtime - y[0]] + [nowtime - z[0]] for x,y,z in zip(data["H1_"], data["L1_"], data[""])]
data_table.LoadData(thisdata)
this_data = []
tmp = [data[ifo] for ifo in ifostrs]
for tup in zip(*tmp):
row = [tup[0][1]]
for t in tup[1:]:
row += [nowtime - t[0]]
this_data.append(row)
data_table.LoadData(this_data)
print data_table.ToJSonResponse(order_by = "job", req_id = reqId)
sys.exit()
......@@ -487,7 +504,7 @@ if "nagios" in query:
# really should be much faster
status = [x for x in delay if x > 600.]
if len(status) > 0:
print json.dumps({"nagios_shib_scraper_ver": 0.1, "status_intervals":[{"num_status": 2, "txt_status": "%d jobs more than 3 mins behind" % len(status)}]}, sort_keys=True, indent=4, separators=(',', ': '))
print json.dumps({"nagios_shib_scraper_ver": 0.1, "status_intervals":[{"num_status": 2, "txt_status": "%d jobs more than 10 mins behind" % len(status)}]}, sort_keys=True, indent=4, separators=(',', ': '))
else:
print >>sys.stdout, json.dumps({"nagios_shib_scraper_ver": 0.1, "status_intervals":[{"num_status": 0 , "txt_status": "OK: Max delay: %f s" % max(delay)}]}, sort_keys=True, indent=4, separators=(',', ': '))
......@@ -496,6 +513,10 @@ if "nagios" in query:
# FIXME, just a hardcoded POS
# FIXME counts now, turn into VT
bnsrootdir = "U_dVdzo1pz_bns_normal_low_spin_online_injections_O2A_v1_aggregator"
nsbhrootdir = "U_dVdzo1pz_nsbh05_isotropic_online_injections_O2A_v1_aggregator"
bbhrootdir = "U_dVdzo1pz_lnm_online_injections_O2A_v1_aggregator"
if "vt" in query:
nowtime = now()
......@@ -503,9 +524,6 @@ if "vt" in query:
O2_start = 1164556817
duration = nowtime - O2_start
bnsrootdir = "U_dVdzo1pz_bns_normal_low_spin_online_injections_O2A_v1_aggregator"
nsbhrootdir = "U_dVdzo1pz_nsbh05_isotropic_online_injections_O2A_v1_aggregator"
bbhrootdir = "U_dVdzo1pz_lnm_online_injections_O2A_v1_aggregator"
dvt = {}
dvt["bns"] = 0.240829 / (652333 + 11566878)
......@@ -537,3 +555,19 @@ if "vt" in query:
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "time", req_id = reqId)
# Injection FAR time series
if "far_inj_history" in query:
nowtime = now()
time = []
data = []
for key, rootdir in (("bns", bnsrootdir), ("nsbh", nsbhrootdir), ("bbh", bbhrootdir)):
for job, this_time, this_data in read_aggregated_data_by_job("far_history", nowtime, duration, base_path, jobdirs = [""], rootdir = rootdir, datatype = "min", age = 1e6, level = 5):
time.extend(this_time)
data.extend(this_data)
out_data = [[float(t),float(d)] for t,d in zip(time, data)]
description = [("time", "number"), ("%d" % float(time[-1]), "number")]
data_table = gviz_api.DataTable(description)
data_table.LoadData(out_data)
print data_table.ToJSonResponse(order_by = "time", req_id = reqId)
sys.exit()
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