def defaultTests(columns="", verbosity="default"):
""" create and run a set of standard test scenarios """
# note the key background parameters
m = Model("")
misc = ", %d/%ds, %s/%s/s" % (m.time_timeout, m.time_detect,
printSize(m.rate_mirror, 1000),
printSize(m.rate_flush, 1000))
# create a list of tests to be run
mlist = list()
# run tests for all the interesting combinations
for cp in (1, 2, 3):
for primary in (" v", "nv"):
sList = ["none"] if cp == 1 else [" v", "nv", "symmetric"]
for secondary in sList:
# suppress irrelevent combinations
if primary == "nv" and secondary == " v":
continue
# figure out how to caption this configuration
if secondary == "symmetric":
desc = ("symmetric: %d %s cp" % (cp, primary))
elif (cp > 1):
desc = ("prim: %s %d %s cp" %
(primary, cp - 1, secondary))
else:
desc = "prim: %s 0 cp" % (primary)
# instantiate the model
m = Model(desc + misc)
m.copies = cp
m.nv_1 = (primary == "nv")
m.cache_1 = 4 * GB
if secondary == "symmetric":
m.symmetric = True
m.cache_1 *= cp
m.nv_2 = (primary == "nv")
m.cache_2 = 0
elif cp > 1:
m.nv_2 = (secondary == "nv")
m.cache_2 = 40 * GB
mlist.append(m)
# run all the specified models
run(mlist, columns, verbosity)
def printParms(fmt, disk, raid, rados, site, multi):
"""
print out the parameters associated with a test
"""
if disk is not None:
print "Disk Modeling Parameters"
print " size: %10s" % printSize(disk.size)
print(" FIT rate: %10d (MTBF = %s)" %
(disk.fits, printTime(mttf(disk.fits))))
print " NRE rate: %10.1E" % disk.nre
if raid is not None:
print "RAID parameters"
print " replace: %16s" % printTime(raid.delay)
if raid.speed > 0:
print(" recovery rate: %7s/s (%s)" %
(printSize(raid.speed),
printTime(raid.rebuild_time())))
print " NRE model: %10s" % raid.nre_model
print " object size: %10s" % printSize(raid.objsize)
if rados is not None:
print "RADOS parameters"
print " auto mark-out: %14s" % printTime(rados.delay)
print(" recovery rate: %8s/s (%s/drive)" %
(printSize(rados.speed),
printTime(rados.rebuild_time(rados.speed))))
print " osd fullness: %7d%%" % (rados.full * 100)
print " declustering: %7d PG/OSD" % rados.pgs
print " NRE model: %10s" % rados.nre_model
print " object size: %7s" % \
printSize(rados.objsize, unit=1024)
print " stripe length:%7d" % rados.stripe
if site is not None:
print "Site parameters"
s = 0 if multi is None else multi.sites
if site.fits == 0:
print " disasters: IGNORED"
else:
tf = mttf(site.fits)
print(" disaster rate: %12s (%d FITS)" %
(printTime(tf), site.fits))
if site.replace == 0:
print " site recovery: NEVER"
else:
print " site recovery: %11s" % printTime(site.replace)
if multi is not None:
print(" recovery rate: %8s/s (%s/PG)" %
(printSize(multi.speed),
printTime(multi.rados.rebuild_time(multi.speed))))
if multi.latency == 0:
print " replication: synchronous"
else:
print(" replication: asynchronous (%s delay)" %
(fmt.printTime(multi.latency)))
def run(models, columns="", verbosity="default",
capacity=1*PiB, period=1*YEAR):
""" execute a single model and print out the results
models -- list of models to be run
columns -- what optional columns to include
verbosity -- what kind of output we want
capacity -- total system capacity (bytes)
period -- modeled time period (hours)
"""
# figure out what optional fields to include
showTr = False # FIX get from columns
showBW = False # FIX get from columns
# define the column headings
heads = [
"configuration", "<p,s>/PiB", "durability", "Ploss"
]
legends = [
"configuration being modeled",
"<primaries, secondaries> per petabyte",
"probability of object survival*",
"probability of loss*",
]
# consider the optional fields
if showBW:
heads.append("BW(recov)")
legends.append("peak recovery bandwidth")
if showTr:
heads.append("T(recov)")
legends.append("max detect/recovery time")
# figure out the longest description
maxlen = len(heads[0])
for m in models:
l = len(m.descr)
if l > maxlen:
maxlen = l
format = ColumnPrint(heads, maxdesc=maxlen)
# figure out what output he wants
parm1 = True # basic parameters at front
descr = True # descriptions of columns
headings = True # column headings
parms = True # all parameters for every model
debug = False # diagnostic output
if verbosity == "parameters": # per-test parameters
parm1 = False
descr = False
elif verbosity == "headings": # output and headings
parm1 = False
parms = False
descr = False
elif verbosity == "data": # minimal - just the output
parm1 = False
parms = False
descr = False
headings = False
elif verbosity == "all": # pretty much everyting
debug = True
parm1 = False
elif verbosity == "debug": # debug only
debug = True
headings = False
parm1 = False
parms = False
descr = False
else:
parms = False
# print out basic parameters (assumed not to change)
if parm1:
printParms(models[0], None, None)
# print out column legends
if descr:
print ""
print "Column legends:"
s = printTime(period)
i = 1
while i <= len(legends):
l = legends[i - 1]
if l.endswith('*'):
print "\t%d %s (per %s)" % (i, l, s)
else:
print "\t%d %s" % (i, l)
i += 1
# print out column headings
if headings:
format.printHeadings()
for m in models:
# compute sizes and rates
sizes = Sizes(m, capacity, debug)
rates = Rates(m, debug)
# print out the model parameters
if parms:
printParms(m, sizes, rates)
# compute and print the reliability
results = Results(m, sizes, rates, period, debug)
s = list()
s.append(m.descr)
if m.symmetric:
s.append("<%d>" % (sizes.n_primary))
else:
s.append("<%d,%d>" % (sizes.n_primary, sizes.n_secondary))
s.append(printDurability(results.durability))
s.append(printProbability(results.p_loss))
bw = max(results.bw_sfail, results.bw_pfail)
if showBW:
s.append("n/a" if bw == 0 else printSize(bw, 1000) + "/s")
if showTr:
s.append("n/a" if bw == 0 else printFloat(results.Trecov)+"s")
format.printLine(s)