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#!/usr/bin/env python
# Copyright 2008 Orbitz WorldWide
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# This module is an implementation of the Whisper database API
# Here is the basic layout of a whisper data file
#
# File = Header,Data
# Header = Metadata,ArchiveInfo+
# Metadata = aggregationType,maxRetention,xFilesFactor,archiveCount
# ArchiveInfo = Offset,SecondsPerPoint,Points
# Data = Archive+
# Archive = Point+
# Point = timestamp,value
import os, struct, time, operator, itertools
try:
import fcntl
CAN_LOCK = True
except ImportError:
CAN_LOCK = False
LOCK = False
CACHE_HEADERS = False
AUTOFLUSH = False
__headerCache = {}
longFormat = "!L"
longSize = struct.calcsize(longFormat)
floatFormat = "!f"
floatSize = struct.calcsize(floatFormat)
valueFormat = "!d"
valueSize = struct.calcsize(valueFormat)
pointFormat = "!Ld"
pointSize = struct.calcsize(pointFormat)
metadataFormat = "!2LfL"
metadataSize = struct.calcsize(metadataFormat)
archiveInfoFormat = "!3L"
archiveInfoSize = struct.calcsize(archiveInfoFormat)
aggregationTypeToMethod = dict({
1: 'average',
2: 'sum',
3: 'last',
4: 'max',
5: 'min'
})
aggregationMethodToType = dict([[v,k] for k,v in aggregationTypeToMethod.items()])
aggregationMethods = aggregationTypeToMethod.values()
debug = startBlock = endBlock = lambda *a,**k: None
UnitMultipliers = {
'seconds' : 1,
'minutes' : 60,
'hours' : 3600,
'days' : 86400,
'weeks' : 86400 * 7,
'years' : 86400 * 365
}
def getUnitString(s):
if 'seconds'.startswith(s): return 'seconds'
if 'minutes'.startswith(s): return 'minutes'
if 'hours'.startswith(s): return 'hours'
if 'days'.startswith(s): return 'days'
if 'weeks'.startswith(s): return 'weeks'
if 'years'.startswith(s): return 'years'
raise ValueError("Invalid unit '%s'" % s)
def parseRetentionDef(retentionDef):
import re
(precision, points) = retentionDef.strip().split(':')
if precision.isdigit():
precision = int(precision) * UnitMultipliers[getUnitString('s')]
else:
precision_re = re.compile(r'^(\d+)([a-z]+)$')
match = precision_re.match(precision)
if match:
precision = int(match.group(1)) * UnitMultipliers[getUnitString(match.group(2))]
else:
raise ValueError("Invalid precision specification '%s'" % precision)
if points.isdigit():
points = int(points)
else:
points_re = re.compile(r'^(\d+)([a-z]+)$')
match = points_re.match(points)
if match:
points = int(match.group(1)) * UnitMultipliers[getUnitString(match.group(2))] / precision
else:
raise ValueError("Invalid retention specification '%s'" % points)
return (precision, points)
class WhisperException(Exception):
"""Base class for whisper exceptions."""
class InvalidConfiguration(WhisperException):
"""Invalid configuration."""
class InvalidAggregationMethod(WhisperException):
"""Invalid aggregation method."""
class InvalidTimeInterval(WhisperException):
"""Invalid time interval."""
class TimestampNotCovered(WhisperException):
"""Timestamp not covered by any archives in this database."""
class CorruptWhisperFile(WhisperException):
def __init__(self, error, path):
Exception.__init__(self, error)
self.error = error
self.path = path
def __repr__(self):
return "<CorruptWhisperFile[%s] %s>" % (self.path, self.error)
def __str__(self):
return "%s (%s)" % (self.error, self.path)
def enableDebug():
global open, debug, startBlock, endBlock
class open(file):
def __init__(self,*args,**kwargs):
file.__init__(self,*args,**kwargs)
self.writeCount = 0
self.readCount = 0
def write(self,data):
self.writeCount += 1
debug('WRITE %d bytes #%d' % (len(data),self.writeCount))
return file.write(self,data)
def read(self,bytes):
self.readCount += 1
debug('READ %d bytes #%d' % (bytes,self.readCount))
return file.read(self,bytes)
def debug(message):
print 'DEBUG :: %s' % message
__timingBlocks = {}
def startBlock(name):
__timingBlocks[name] = time.time()
def endBlock(name):
debug("%s took %.5f seconds" % (name,time.time() - __timingBlocks.pop(name)))
def __readHeader(fh):
info = __headerCache.get(fh.name)
if info:
return info
originalOffset = fh.tell()
fh.seek(0)
packedMetadata = fh.read(metadataSize)
try:
(aggregationType,maxRetention,xff,archiveCount) = struct.unpack(metadataFormat,packedMetadata)
except:
raise CorruptWhisperFile("Unable to read header", fh.name)
archives = []
for i in xrange(archiveCount):
packedArchiveInfo = fh.read(archiveInfoSize)
try:
(offset,secondsPerPoint,points) = struct.unpack(archiveInfoFormat,packedArchiveInfo)
except:
raise CorruptWhisperFile("Unable to read archive%d metadata" % i, fh.name)
archiveInfo = {
'offset' : offset,
'secondsPerPoint' : secondsPerPoint,
'points' : points,
'retention' : secondsPerPoint * points,
'size' : points * pointSize,
}
archives.append(archiveInfo)
fh.seek(originalOffset)
info = {
'aggregationMethod' : aggregationTypeToMethod.get(aggregationType, 'average'),
'maxRetention' : maxRetention,
'xFilesFactor' : xff,
'archives' : archives,
}
if CACHE_HEADERS:
__headerCache[fh.name] = info
return info
def setAggregationMethod(path, aggregationMethod):
"""setAggregationMethod(path,aggregationMethod)
path is a string
aggregationMethod specifies the method to use when propogating data (see ``whisper.aggregationMethods``)
"""
fh = open(path,'r+b')
if LOCK:
fcntl.flock( fh.fileno(), fcntl.LOCK_EX )
packedMetadata = fh.read(metadataSize)
try:
(aggregationType,maxRetention,xff,archiveCount) = struct.unpack(metadataFormat,packedMetadata)
except:
raise CorruptWhisperFile("Unable to read header", fh.name)
try:
newAggregationType = struct.pack( longFormat, aggregationMethodToType[aggregationMethod] )
except KeyError:
raise InvalidAggregationMethod("Unrecognized aggregation method: %s" %
aggregationMethod)
fh.seek(0)
fh.write(newAggregationType)
if AUTOFLUSH:
fh.flush()
os.fsync(fh.fileno())
if CACHE_HEADERS and fh.name in __headerCache:
del __headerCache[fh.name]
fh.close()
return aggregationTypeToMethod.get(aggregationType, 'average')
def validateArchiveList(archiveList):
""" Validates an archiveList.
An ArchiveList must:
1. Have at least one archive config. Example: (60, 86400)
2. No archive may be a duplicate of another.
3. Higher precision archives' precision must evenly divide all lower precision archives' precision.
4. Lower precision archives must cover larger time intervals than higher precision archives.
5. Each archive must have at least enough points to consolidate to the next archive
Returns True or False
"""
if not archiveList:
raise InvalidConfiguration("You must specify at least one archive configuration!")
archiveList.sort(key=lambda a: a[0]) #sort by precision (secondsPerPoint)
for i,archive in enumerate(archiveList):
if i == len(archiveList) - 1:
break
nextArchive = archiveList[i+1]
if not archive[0] < nextArchive[0]:
raise InvalidConfiguration("A Whisper database may not configured having"
"two archives with the same precision (archive%d: %s, archive%d: %s)" %
(i, archive, i + 1, nextArchive))
if nextArchive[0] % archive[0] != 0:
raise InvalidConfiguration("Higher precision archives' precision "
"must evenly divide all lower precision archives' precision "
"(archive%d: %s, archive%d: %s)" %
(i, archive[0], i + 1, nextArchive[0]))
retention = archive[0] * archive[1]
nextRetention = nextArchive[0] * nextArchive[1]
if not nextRetention > retention:
raise InvalidConfiguration("Lower precision archives must cover "
"larger time intervals than higher precision archives "
"(archive%d: %s seconds, archive%d: %s seconds)" %
(i, archive[1], i + 1, nextArchive[1]))
archivePoints = archive[1]
pointsPerConsolidation = nextArchive[0] / archive[0]
if not archivePoints >= pointsPerConsolidation:
raise InvalidConfiguration("Each archive must have at least enough points "
"to consolidate to the next archive (archive%d consolidates %d of "
"archive%d's points but it has only %d total points)" %
(i + 1, pointsPerConsolidation, i, archivePoints))
def create(path,archiveList,xFilesFactor=None,aggregationMethod=None,sparse=False):
"""create(path,archiveList,xFilesFactor=0.5,aggregationMethod='average')
path is a string
archiveList is a list of archives, each of which is of the form (secondsPerPoint,numberOfPoints)
xFilesFactor specifies the fraction of data points in a propagation interval that must have known values for a propagation to occur
aggregationMethod specifies the function to use when propogating data (see ``whisper.aggregationMethods``)
"""
# Set default params
if xFilesFactor is None:
xFilesFactor = 0.5
if aggregationMethod is None:
aggregationMethod = 'average'
#Validate archive configurations...
validateArchiveList(archiveList)
#Looks good, now we create the file and write the header
if os.path.exists(path):
raise InvalidConfiguration("File %s already exists!" % path)
fh = open(path,'wb')
if LOCK:
fcntl.flock( fh.fileno(), fcntl.LOCK_EX )
aggregationType = struct.pack( longFormat, aggregationMethodToType.get(aggregationMethod, 1) )
oldest = sorted([secondsPerPoint * points for secondsPerPoint,points in archiveList])[-1]
maxRetention = struct.pack( longFormat, oldest )
xFilesFactor = struct.pack( floatFormat, float(xFilesFactor) )
archiveCount = struct.pack(longFormat, len(archiveList))
packedMetadata = aggregationType + maxRetention + xFilesFactor + archiveCount
fh.write(packedMetadata)
headerSize = metadataSize + (archiveInfoSize * len(archiveList))
archiveOffsetPointer = headerSize
for secondsPerPoint,points in archiveList:
archiveInfo = struct.pack(archiveInfoFormat, archiveOffsetPointer, secondsPerPoint, points)
fh.write(archiveInfo)
archiveOffsetPointer += (points * pointSize)
if sparse:
fh.seek(archiveOffsetPointer - headerSize - 1)
fh.write("\0")
else:
# If not creating the file sparsely, then fill the rest of the file with
# zeroes.
remaining = archiveOffsetPointer - headerSize
chunksize = 16384
zeroes = '\x00' * chunksize
while remaining > chunksize:
fh.write(zeroes)
remaining -= chunksize
fh.write(zeroes[:remaining])
if AUTOFLUSH:
fh.flush()
os.fsync(fh.fileno())
fh.close()
def __aggregate(aggregationMethod, knownValues):
if aggregationMethod == 'average':
return float(sum(knownValues)) / float(len(knownValues))
elif aggregationMethod == 'sum':
return float(sum(knownValues))
elif aggregationMethod == 'last':
return knownValues[len(knownValues)-1]
elif aggregationMethod == 'max':
return max(knownValues)
elif aggregationMethod == 'min':
return min(knownValues)
else:
raise InvalidAggregationMethod("Unrecognized aggregation method %s" %
aggregationMethod)
def __propagate(fh,header,timestamp,higher,lower):
aggregationMethod = header['aggregationMethod']
xff = header['xFilesFactor']
lowerIntervalStart = timestamp - (timestamp % lower['secondsPerPoint'])
lowerIntervalEnd = lowerIntervalStart + lower['secondsPerPoint']
fh.seek(higher['offset'])
packedPoint = fh.read(pointSize)
(higherBaseInterval,higherBaseValue) = struct.unpack(pointFormat,packedPoint)
if higherBaseInterval == 0:
higherFirstOffset = higher['offset']
else:
timeDistance = lowerIntervalStart - higherBaseInterval
pointDistance = timeDistance / higher['secondsPerPoint']
byteDistance = pointDistance * pointSize
higherFirstOffset = higher['offset'] + (byteDistance % higher['size'])
higherPoints = lower['secondsPerPoint'] / higher['secondsPerPoint']
higherSize = higherPoints * pointSize
relativeFirstOffset = higherFirstOffset - higher['offset']
relativeLastOffset = (relativeFirstOffset + higherSize) % higher['size']
higherLastOffset = relativeLastOffset + higher['offset']
fh.seek(higherFirstOffset)
if higherFirstOffset < higherLastOffset: #we don't wrap the archive
seriesString = fh.read(higherLastOffset - higherFirstOffset)
else: #We do wrap the archive
higherEnd = higher['offset'] + higher['size']
seriesString = fh.read(higherEnd - higherFirstOffset)
fh.seek(higher['offset'])
seriesString += fh.read(higherLastOffset - higher['offset'])
#Now we unpack the series data we just read
byteOrder,pointTypes = pointFormat[0],pointFormat[1:]
points = len(seriesString) / pointSize
seriesFormat = byteOrder + (pointTypes * points)
unpackedSeries = struct.unpack(seriesFormat, seriesString)
#And finally we construct a list of values
neighborValues = [None] * points
currentInterval = lowerIntervalStart
step = higher['secondsPerPoint']
for i in xrange(0,len(unpackedSeries),2):
pointTime = unpackedSeries[i]
if pointTime == currentInterval:
neighborValues[i/2] = unpackedSeries[i+1]
currentInterval += step
#Propagate aggregateValue to propagate from neighborValues if we have enough known points
knownValues = [v for v in neighborValues if v is not None]
if not knownValues:
return False
knownPercent = float(len(knownValues)) / float(len(neighborValues))
if knownPercent >= xff: #we have enough data to propagate a value!
aggregateValue = __aggregate(aggregationMethod, knownValues)
myPackedPoint = struct.pack(pointFormat,lowerIntervalStart,aggregateValue)
fh.seek(lower['offset'])
packedPoint = fh.read(pointSize)
(lowerBaseInterval,lowerBaseValue) = struct.unpack(pointFormat,packedPoint)
if lowerBaseInterval == 0: #First propagated update to this lower archive
fh.seek(lower['offset'])
fh.write(myPackedPoint)
else: #Not our first propagated update to this lower archive
timeDistance = lowerIntervalStart - lowerBaseInterval
pointDistance = timeDistance / lower['secondsPerPoint']
byteDistance = pointDistance * pointSize
lowerOffset = lower['offset'] + (byteDistance % lower['size'])
fh.seek(lowerOffset)
fh.write(myPackedPoint)
return True
else:
return False
def update(path,value,timestamp=None):
"""update(path,value,timestamp=None)
path is a string
value is a float
timestamp is either an int or float
"""
value = float(value)
fh = open(path,'r+b')
return file_update(fh, value, timestamp)
def file_update(fh, value, timestamp):
if LOCK:
fcntl.flock( fh.fileno(), fcntl.LOCK_EX )
header = __readHeader(fh)
now = int( time.time() )
if timestamp is None:
timestamp = now
timestamp = int(timestamp)
diff = now - timestamp
if not ((diff < header['maxRetention']) and diff >= 0):
raise TimestampNotCovered("Timestamp not covered by any archives in "
"this database.")
for i,archive in enumerate(header['archives']): #Find the highest-precision archive that covers timestamp
if archive['retention'] < diff: continue
lowerArchives = header['archives'][i+1:] #We'll pass on the update to these lower precision archives later
break
#First we update the highest-precision archive
myInterval = timestamp - (timestamp % archive['secondsPerPoint'])
myPackedPoint = struct.pack(pointFormat,myInterval,value)
fh.seek(archive['offset'])
packedPoint = fh.read(pointSize)
(baseInterval,baseValue) = struct.unpack(pointFormat,packedPoint)
if baseInterval == 0: #This file's first update
fh.seek(archive['offset'])
fh.write(myPackedPoint)
baseInterval,baseValue = myInterval,value
else: #Not our first update
timeDistance = myInterval - baseInterval
pointDistance = timeDistance / archive['secondsPerPoint']
byteDistance = pointDistance * pointSize
myOffset = archive['offset'] + (byteDistance % archive['size'])
fh.seek(myOffset)
fh.write(myPackedPoint)
#Now we propagate the update to lower-precision archives
higher = archive
for lower in lowerArchives:
if not __propagate(fh, header, myInterval, higher, lower):
break
higher = lower
if AUTOFLUSH:
fh.flush()
os.fsync(fh.fileno())
fh.close()
def update_many(path,points):
"""update_many(path,points)
path is a string
points is a list of (timestamp,value) points
"""
if not points: return
points = [ (int(t),float(v)) for (t,v) in points]
points.sort(key=lambda p: p[0],reverse=True) #order points by timestamp, newest first
fh = open(path,'r+b')
return file_update_many(fh, points)
def file_update_many(fh, points):
if LOCK:
fcntl.flock( fh.fileno(), fcntl.LOCK_EX )
header = __readHeader(fh)
now = int( time.time() )
archives = iter( header['archives'] )
currentArchive = archives.next()
currentPoints = []
for point in points:
age = now - point[0]
while currentArchive['retention'] < age: #we can't fit any more points in this archive
if currentPoints: #commit all the points we've found that it can fit
currentPoints.reverse() #put points in chronological order
__archive_update_many(fh,header,currentArchive,currentPoints)
currentPoints = []
try:
currentArchive = archives.next()
except StopIteration:
currentArchive = None
break
if not currentArchive:
break #drop remaining points that don't fit in the database
currentPoints.append(point)
if currentArchive and currentPoints: #don't forget to commit after we've checked all the archives
currentPoints.reverse()
__archive_update_many(fh,header,currentArchive,currentPoints)
if AUTOFLUSH:
fh.flush()
os.fsync(fh.fileno())
fh.close()
def __archive_update_many(fh,header,archive,points):
step = archive['secondsPerPoint']
alignedPoints = [ (timestamp - (timestamp % step), value)
for (timestamp,value) in points ]
#Create a packed string for each contiguous sequence of points
packedStrings = []
previousInterval = None
currentString = ""
for (interval,value) in alignedPoints:
if interval == previousInterval: continue
if (not previousInterval) or (interval == previousInterval + step):
currentString += struct.pack(pointFormat,interval,value)
previousInterval = interval
else:
numberOfPoints = len(currentString) / pointSize
startInterval = previousInterval - (step * (numberOfPoints-1))
packedStrings.append( (startInterval,currentString) )
currentString = struct.pack(pointFormat,interval,value)
previousInterval = interval
if currentString:
numberOfPoints = len(currentString) / pointSize
startInterval = previousInterval - (step * (numberOfPoints-1))
packedStrings.append( (startInterval,currentString) )
#Read base point and determine where our writes will start
fh.seek(archive['offset'])
packedBasePoint = fh.read(pointSize)
(baseInterval,baseValue) = struct.unpack(pointFormat,packedBasePoint)
if baseInterval == 0: #This file's first update
baseInterval = packedStrings[0][0] #use our first string as the base, so we start at the start
#Write all of our packed strings in locations determined by the baseInterval
for (interval,packedString) in packedStrings:
timeDistance = interval - baseInterval
pointDistance = timeDistance / step
byteDistance = pointDistance * pointSize
myOffset = archive['offset'] + (byteDistance % archive['size'])
fh.seek(myOffset)
archiveEnd = archive['offset'] + archive['size']
bytesBeyond = (myOffset + len(packedString)) - archiveEnd
if bytesBeyond > 0:
fh.write( packedString[:-bytesBeyond] )
assert fh.tell() == archiveEnd, "archiveEnd=%d fh.tell=%d bytesBeyond=%d len(packedString)=%d" % (archiveEnd,fh.tell(),bytesBeyond,len(packedString))
fh.seek( archive['offset'] )
fh.write( packedString[-bytesBeyond:] ) #safe because it can't exceed the archive (retention checking logic above)
else:
fh.write(packedString)
#Now we propagate the updates to lower-precision archives
higher = archive
lowerArchives = [arc for arc in header['archives'] if arc['secondsPerPoint'] > archive['secondsPerPoint']]
for lower in lowerArchives:
fit = lambda i: i - (i % lower['secondsPerPoint'])
lowerIntervals = [fit(p[0]) for p in alignedPoints]
uniqueLowerIntervals = set(lowerIntervals)
propagateFurther = False
for interval in uniqueLowerIntervals:
if __propagate(fh, header, interval, higher, lower):
propagateFurther = True
if not propagateFurther:
break
higher = lower
def info(path):
"""info(path)
path is a string
"""
fh = open(path,'rb')
info = __readHeader(fh)
fh.close()
return info
def fetch(path,fromTime,untilTime=None):
"""fetch(path,fromTime,untilTime=None)
path is a string
fromTime is an epoch time
untilTime is also an epoch time, but defaults to now
"""
fh = open(path,'rb')
return file_fetch(fh, fromTime, untilTime)
def file_fetch(fh, fromTime, untilTime):
header = __readHeader(fh)
now = int( time.time() )
if untilTime is None:
untilTime = now
fromTime = int(fromTime)
untilTime = int(untilTime)
oldestTime = now - header['maxRetention']
if fromTime < oldestTime:
fromTime = oldestTime
if not (fromTime < untilTime):
raise InvalidTimeInterval("Invalid time interval")
if untilTime > now:
untilTime = now
if untilTime < fromTime:
untilTime = now
diff = now - fromTime
for archive in header['archives']:
if archive['retention'] >= diff:
break
fromInterval = int( fromTime - (fromTime % archive['secondsPerPoint']) ) + archive['secondsPerPoint']
untilInterval = int( untilTime - (untilTime % archive['secondsPerPoint']) ) + archive['secondsPerPoint']
fh.seek(archive['offset'])
packedPoint = fh.read(pointSize)
(baseInterval,baseValue) = struct.unpack(pointFormat,packedPoint)
if baseInterval == 0:
step = archive['secondsPerPoint']
points = (untilInterval - fromInterval) / step
timeInfo = (fromInterval,untilInterval,step)
valueList = [None] * points
return (timeInfo,valueList)
#Determine fromOffset
timeDistance = fromInterval - baseInterval
pointDistance = timeDistance / archive['secondsPerPoint']
byteDistance = pointDistance * pointSize
fromOffset = archive['offset'] + (byteDistance % archive['size'])
#Determine untilOffset
timeDistance = untilInterval - baseInterval
pointDistance = timeDistance / archive['secondsPerPoint']
byteDistance = pointDistance * pointSize
untilOffset = archive['offset'] + (byteDistance % archive['size'])
#Read all the points in the interval
fh.seek(fromOffset)
if fromOffset < untilOffset: #If we don't wrap around the archive
seriesString = fh.read(untilOffset - fromOffset)
else: #We do wrap around the archive, so we need two reads
archiveEnd = archive['offset'] + archive['size']
seriesString = fh.read(archiveEnd - fromOffset)
fh.seek(archive['offset'])
seriesString += fh.read(untilOffset - archive['offset'])
#Now we unpack the series data we just read (anything faster than unpack?)
byteOrder,pointTypes = pointFormat[0],pointFormat[1:]
points = len(seriesString) / pointSize
seriesFormat = byteOrder + (pointTypes * points)
unpackedSeries = struct.unpack(seriesFormat, seriesString)
#And finally we construct a list of values (optimize this!)
valueList = [None] * points #pre-allocate entire list for speed
currentInterval = fromInterval
step = archive['secondsPerPoint']
for i in xrange(0,len(unpackedSeries),2):
pointTime = unpackedSeries[i]
if pointTime == currentInterval:
pointValue = unpackedSeries[i+1]
valueList[i/2] = pointValue #in-place reassignment is faster than append()
currentInterval += step
fh.close()
timeInfo = (fromInterval,untilInterval,step)
return (timeInfo,valueList)
def merge(path_from, path_to, step=1<<12):
headerFrom = info(path_from)
archives = headerFrom['archives']
archives.sort(key=operator.itemgetter('retention'), reverse=True)
# Start from maxRetention of the oldest file, and skip forward at max 'step'
# points at a time.
fromTime = int(time.time()) - headerFrom['maxRetention']
for archive in archives:
pointsRemaining = archive['points']
while pointsRemaining:
pointsToRead = step
if pointsRemaining < step:
pointsToRead = pointsRemaining
pointsRemaining -= pointsToRead
untilTime = fromTime + (pointsToRead * archive['secondsPerPoint'])
(timeInfo, values) = fetch(path_from, fromTime, untilTime)
(start, end, archive_step) = timeInfo
pointsToWrite = list(itertools.ifilter(
lambda points: points[1] is not None,
itertools.izip(xrange(start, end, archive_step), values)))
pointsToWrite.sort(key=lambda p: p[0],reverse=True) #order points by timestamp, newest first
update_many(path_to, pointsToWrite)
fromTime = untilTime