def get_graph(node, options):
g = jsapi.QueryGraph()
#we don't use this here
# start_ts = parse_ts(options.start_ts)
#coral_fidxs['Referrer_URL'],
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], coral_fidxs['nbytes'], \
coral_fidxs['dl_utime'], len(coral_types) ]
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
round.set_cfg("wait_for_catch_up", "false")
f.instantiate_on(node)
local_raw_cube = define_raw_cube(g, options.cube_name, node,
parsed_field_offsets, True)
if not options.full_url:
url_to_dom = jsapi.URLToDomain(g, field=coral_fidxs['URL_requested'])
g.chain([f, csvp, round, url_to_dom, local_raw_cube])
else:
g.chain([f, csvp, round, local_raw_cube])
return g
def parse_setup():
(serv_addr, serv_port), file_to_parse = js_client_config.arg_config()
k2 = 20 # how many to pull to top level
k = 10 # how many to display
# specify the query fields that this computation is interested in
#which_coral_fields = [coral_fidxs['URL_requested']]
agg_field_idx = coral_fidxs['URL_requested']
g = jsapi.QueryGraph()
f = jsapi.FileRead(g, file_to_parse, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
grab_domain = jsapi.GenericParse(g, DOMAIN_CAPTURE,
coral_types[agg_field_idx],
field_to_parse=agg_field_idx,
keep_unparsed=False)
pull_k2 = jsapi.TimeSubscriber(g, {}, 2000, "-count", k2)
local_cube = g.add_cube("coral_results")
local_cube.add_dim("Requested_domains", Element.STRING, 0)
# index past end of tuple is a magic API to the "count" aggregate that tells
# it to assume a count of 1
local_cube.add_agg("count", jsapi.Cube.AggType.COUNT, 1)
local_cube.set_overwrite(True) # fresh results
g.chain([f, csvp, grab_domain, local_cube, pull_k2])
cr = ClientDataReader(raw_data=True)
g.connectExternal(pull_k2, cr.prep_to_receive_data())
remote_deploy(serv_addr, serv_port, g, cube=local_cube)
return cr
def test_CSVParse_validate(self):
qGraph = jsapi.QueryGraph()
reader = jsapi.FileRead(qGraph, "file name")
csvprs = jsapi.CSVParse(qGraph, "ISDDDIIDSISIISD")
qGraph.connect(reader, csvprs)
try:
qGraph.validate_schemas()
except SchemaError as ex:
self.fail("Should not throw, but got: " + str(ex))
def test_CVSParse_validate_bad(self):
qGraph = jsapi.QueryGraph()
reader = jsapi.FileRead(qGraph, "file name")
csv_types = "IIIII"
csvprs = jsapi.CSVParse(qGraph, csv_types)
# should fail because the outschema of the previous CSVParse has an int
# as its first element, while CVSParse currently needs a string as the
# first element. this will probably change when CVSParse supports parsing
# an arbritrarily indexed tuple, but the validation will be quite similar;
# probably:
# assert 'S' != csv_types[3] # note that this is a real assert, not a test
# csvprs_fail = jsapi.CSVParse(qgraph, csv_types, field_to_parse=3)
csvprs_fail = jsapi.CSVParse(qGraph, "DDSS")
qGraph.connect(reader, csvprs)
qGraph.connect(csvprs, csvprs_fail)
self.assertRaises(SchemaError, qGraph.validate_schemas)
# a hack for exceptions with types. This unittest function is new in python
# 2.7, so will fail in 2.6 or earlier...
self.assertRaisesRegexp(SchemaError, '[.\s]*requires a string[.\s]*',
qGraph.validate_schemas)
def get_graph(source_nodes, root_node, options):
ECHO_RESULTS = not options.no_echo
g = jsapi.QueryGraph()
BOUND = 100
start_ts = parse_ts(options.start_ts)
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], coral_fidxs['nbytes'], coral_fidxs['dl_utime'],
len(coral_fidxs) ]
global_results = g.add_cube("global_slow")
define_schema_for_raw_cube(global_results, parsed_field_offsets)
global_results.instantiate_on(root_node)
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
g.connect(congest_logger, global_results)
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 1000)
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
# pull_q.set_cfg("rollup_levels", "8,1")
# pull_q.set_cfg("simulation_rate",1)
pull_q.set_cfg("window_offset", 6 * 1000) #but trailing by a few
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([global_results, pull_q, echo])
for node, i in numbered(source_nodes, False):
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
round.set_cfg("wait_for_catch_up", "true")
f.instantiate_on(node)
filter = jsapi.RatioFilter(g, numer=coral_fidxs['dl_utime'], \
denom = coral_fidxs['nbytes'], bound = BOUND)
g.chain([f, csvp, round, filter, congest_logger])
return g
def test_cubeFilterSubscriber(self):
qGraph = jsapi.QueryGraph()
src = jsapi.RandSource(qGraph, 1, 2)
local_cube = qGraph.add_cube("results")
local_cube.add_dim("state", Element.STRING, 0)
local_cube.add_agg("count", jsapi.Cube.AggType.COUNT, 2)
filter = jsapi.FilterSubscriber(qGraph, cube_field=2, level_in_field=0)
#out-schema from filter should be S,T, matching source
ex = jsapi.ExtendOperator(qGraph, "i", ["a count"])
eval_op = jsapi.RandEval(qGraph)
qGraph.chain([src, ex, local_cube, filter, eval_op])
reader = jsapi.FileRead(qGraph, "file name")
csv_parse = jsapi.CSVParse(qGraph, types="I", fields_to_keep="all")
qGraph.chain([reader, csv_parse, filter])
try:
qGraph.validate_schemas()
except SchemaError as ex:
self.fail("should not throw, but got " + str(ex))
def get_graph(source_nodes, root_node, options):
g = jsapi.QueryGraph()
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_anamolous_quant")
central_cube.instantiate_on(root_node)
define_quant_cube(central_cube)
pull_q = jsapi.TimeSubscriber(g, {}, 1000)
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
# pull_q.set_cfg("rollup_levels", "8,1")
# pull_q.set_cfg("simulation_rate",1)
pull_q.set_cfg("window_offset", 6 * 1000) #but trailing by a few
q_op = jsapi.Quantile(g, 0.95, field=1)
g.chain([central_cube, pull_q, q_op])
thresh_cube = g.add_cube("global_coral_anamalous_thresh")
thresh_cube.add_dim("time", CubeSchema.Dimension.TIME_CONTAINMENT, 0)
thresh_cube.add_agg("thresh", jsapi.Cube.AggType.COUNT, 1)
thresh_cube.set_overwrite(True)
thresh_cube.instantiate_on(root_node)
if not options.no_echo:
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([q_op, echo, thresh_cube])
else:
g.chain([q_op, thresh_cube])
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], coral_fidxs['nbytes'], coral_fidxs['dl_utime'], len(coral_types) ]
global_results = g.add_cube("global_anomalous")
define_schema_for_raw_cube(global_results, parsed_field_offsets)
global_results.instantiate_on(root_node)
FILTER_FIELD = coral_fidxs['nbytes']
for node in source_nodes:
################ First do the data loading part
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
round.set_cfg("wait_for_catch_up", "true")
f.instantiate_on(node)
local_raw_cube = g.add_cube("local_coral_anamolous_all")
define_schema_for_raw_cube(local_raw_cube, parsed_field_offsets)
pass_raw = jsapi.FilterSubscriber(
g) # to pass through to the summary and q-cube
to_summary = jsapi.ToSummary(g, field=FILTER_FIELD, size=100)
local_q_cube = g.add_cube("local_coral_anamolous_quant")
define_quant_cube(local_q_cube,
[coral_fidxs['timestamp'], FILTER_FIELD])
g.chain([
f, csvp, round, local_raw_cube, pass_raw, to_summary, local_q_cube
])
pull_from_local = jsapi.TimeSubscriber(g, {}, 1000)
pull_from_local.instantiate_on(node)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset", 2000) #but trailing by a few
local_q_cube.instantiate_on(node)
pull_from_local.instantiate_on(node)
g.chain([local_q_cube, pull_from_local, central_cube])
################ Now do the second phase
passthrough = jsapi.FilterSubscriber(g)
passthrough.instantiate_on(root_node)
filter = jsapi.FilterSubscriber(g,
cube_field=FILTER_FIELD,
level_in_field=1)
filter.instantiate_on(node)
g.chain([thresh_cube, passthrough, filter])
g.chain([local_raw_cube, filter, global_results])
return g
def get_graph(source_nodes, root_node, options):
g= jsapi.QueryGraph()
ANALYZE = not options.load_only
LOADING = not options.analyze_only
ECHO_RESULTS = not options.no_echo
MULTIROUND = options.multiround
HASH_SAMPLE = options.hash_sample
LOCAL_THRESH = options.local_thresh
if not LOADING and not ANALYZE:
print "can't do neither load nor analysis"
sys.exit(0)
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_urls")
central_cube.instantiate_on(root_node)
define_cube(central_cube)
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 5000 , sort_order="-count", num_results=10)
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
pull_q.set_cfg("rollup_levels", "6,0,1") # every five seconds to match subscription. Roll up counts.
pull_q.set_cfg("simulation_rate", 1)
pull_q.set_cfg("window_offset", 6* 1000) #but trailing by a few
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([central_cube,pull_q, echo] )
add_latency_measure(g, central_cube, root_node, tti=4, hti=5, latencylog=options.latencylog)
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
congest_logger.set_cfg("field", 3)
if MULTIROUND:
tput_merge = jsapi.MultiRoundCoord(g)
tput_merge.set_cfg("start_ts", start_ts)
tput_merge.set_cfg("window_offset", 5 * 1000)
tput_merge.set_cfg("ts_field", 0)
tput_merge.set_cfg("num_results", 10)
tput_merge.set_cfg("sort_column", "-count")
tput_merge.set_cfg("min_window_size", 5)
tput_merge.set_cfg("rollup_levels", "10,0,1") # roll up response codes
tput_merge.instantiate_on(root_node)
pull_q.set_cfg("window_offset", 10* 1000) #but trailing by a few
g.connect(tput_merge, congest_logger)
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], len(coral_types) ]
for node, i in numbered(source_nodes, not LOADING):
if not options.full_url:
table_prefix = "local_coral_domains";
else:
table_prefix = "local_coral_urls";
table_prefix += "_"+options.warp_factor;
local_cube = g.add_cube(table_prefix+("_%d" %i))
define_cube(local_cube, parsed_field_offsets)
print "cube output dimensions:", local_cube.get_output_dimensions()
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
if not options.full_url:
url_to_dom = jsapi.URLToDomain(g, field=coral_fidxs['URL_requested'])
g.chain( [f, csvp, round, url_to_dom, local_cube] )
else:
g.chain( [f, csvp, round, local_cube] )
f.instantiate_on(node)
else:
local_cube.set_overwrite(False)
if MULTIROUND:
pull_from_local = jsapi.MultiRoundClient(g)
else:
query_rate = 1000 if ANALYZE else 3600 * 1000
pull_from_local = jsapi.VariableCoarseningSubscriber(g, {}, query_rate)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("max_window_size", options.max_rollup)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset", 2000) #but trailing by a few
pull_from_local.set_cfg("sort_order", "-count")
pull_from_local.instantiate_on(node)
local_cube.instantiate_on(node)
# count_logger = jsapi.CountLogger(g, field=3)
timestamp_op= jsapi.TimestampOperator(g, "ms")
hostname_extend_op = jsapi.ExtendOperator(g, "s", ["${HOSTNAME}"]) #used as dummy hostname for latency tracker
hostname_extend_op.instantiate_on(node)
lastOp = g.chain([local_cube, pull_from_local])
if HASH_SAMPLE:
v = jsapi.VariableSampling(g, field=2, type='S')
v.set_cfg("steps", options.steps)
# print "connecting ",
lastOp = g.connect(lastOp, v)
g.add_policy( [pull_from_local, v] )
elif LOCAL_THRESH:
v = jsapi.WindowLenFilter(g)
v.set_cfg("err_field", 3)
# print "connecting ",
lastOp = g.connect(lastOp, v)
g.add_policy( [pull_from_local, v] )
g.chain( [lastOp,timestamp_op, hostname_extend_op])
#output: 0=>time, 1=>response_code, 2=> url 3=> count, 4=> timestamp at source, 5=> hostname
if MULTIROUND:
g.connect(hostname_extend_op, tput_merge)
else:
g.connect(hostname_extend_op, congest_logger)
timestamp_cube_op= jsapi.TimestampOperator(g, "ms")
timestamp_cube_op.instantiate_on(root_node)
g.chain ( [congest_logger, timestamp_cube_op, central_cube])
#input to central cube : 0=>time, 1=>response_code, 2=> url 3=> count, 4=> timestamp at source, 5=> hostname 6=> timestamp at union
if options.bw_cap:
congest_logger.set_inlink_bwcap(float(options.bw_cap))
return g
def get_graph(source_nodes, root_node, options):
ECHO_RESULTS = not options.no_echo
ANALYZE = not options.load_only
LOADING = not options.analyze_only
g= jsapi.QueryGraph()
start_ts = parse_ts(options.start_ts)
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
global_respcodes = g.add_cube("global_respcodes")
define_schema_for_cube(global_respcodes)
global_respcodes.instantiate_on(root_node)
global_ratios = g.add_cube("global_ratios")
define_schema_for_cube(global_ratios)
global_ratios.add_agg("ratio", jsapi.Cube.AggType.MIN_D, 4)
global_ratios.instantiate_on(root_node)
pull_resp = jsapi.TimeSubscriber(g, {}, 1000)
pull_resp.set_cfg("ts_field", 0)
pull_resp.set_cfg("start_ts", start_ts)
pull_resp.set_cfg("rollup_levels", "8,1,1")
pull_resp.set_cfg("simulation_rate",1)
pull_resp.set_cfg("window_offset", 5* 1000)
compute_ratio = jsapi.SeqToRatio(g, url_field = 2, total_field = 3, respcode_field = 1)
g.chain( [congest_logger, global_respcodes, pull_resp, compute_ratio, global_ratios] )
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 1000, num_results= 5, sort_order="-ratio")
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
pull_q.set_cfg("rollup_levels", "8,1,1")
pull_q.set_cfg("simulation_rate",1)
pull_q.set_cfg("window_offset", 12* 1000) #but trailing by a few
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain( [global_ratios, pull_q, echo] )
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], len(coral_fidxs) ]
for node, i in numbered(source_nodes, False):
table_prefix = "local_coral_respcodes";
table_prefix += "_"+options.warp_factor;
local_cube = g.add_cube(table_prefix+("_%d" %i))
define_schema_for_cube(local_cube, parsed_field_offsets)
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
round.set_cfg("wait_for_catch_up", "true")
f.instantiate_on(node)
url_to_dom = jsapi.URLToDomain(g, field=coral_fidxs['URL_requested'])
g.chain( [f, csvp, round, url_to_dom, local_cube ] )
else:
local_cube.set_overwrite(False)
query_rate = 1000 if ANALYZE else 3600 * 1000
pull_from_local = jsapi.TimeSubscriber(g, {}, query_rate)
pull_from_local.instantiate_on(node)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset", 2000) #but trailing by a few
local_cube.instantiate_on(node)
pull_from_local.instantiate_on(node)
g.chain( [local_cube, pull_from_local, congest_logger] )
return g
def get_graph(source_nodes, root_node, options):
g = jsapi.QueryGraph()
ANALYZE = not options.load_only
LOADING = not options.analyze_only
ECHO_RESULTS = not options.no_echo
if not LOADING and not ANALYZE:
print "can't do neither load nor analysis"
sys.exit(0)
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_quant")
central_cube.instantiate_on(root_node)
define_cube(central_cube)
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 1000) #every two seconds
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("latency_ts_field", 7)
pull_q.set_cfg("start_ts", start_ts)
pull_q.set_cfg("rollup_levels", "8,1")
pull_q.set_cfg("simulation_rate", 1)
pull_q.set_cfg("window_offset", 6 * 1000) #but trailing by a few
count_op = jsapi.SummaryToCount(g, 2)
q_op = jsapi.Quantile(g, 0.95, 3)
q_op2 = jsapi.Quantile(g, 0.95, 2)
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([central_cube, pull_q, count_op, q_op, q_op2, echo])
latency_measure_op = jsapi.LatencyMeasureSubscriber(g,
time_tuple_index=4,
hostname_tuple_index=5,
interval_ms=100)
#use field
echo_op = jsapi.Echo(g)
echo_op.set_cfg("file_out", options.latencylog)
echo_op.instantiate_on(root_node)
g.chain([central_cube, latency_measure_op, echo_op])
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['nbytes'], coral_fidxs['dl_utime'], len(coral_types) ]
for node, i in numbered(source_nodes, not LOADING):
local_cube = g.add_cube("local_coral_quant_%d" % i)
define_cube(local_cube, parsed_field_offsets)
print "cube output dimensions:", local_cube.get_output_dimensions()
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
to_summary1 = jsapi.ToSummary(g,
field=parsed_field_offsets[2],
size=5000)
to_summary2 = jsapi.ToSummary(g,
field=parsed_field_offsets[3],
size=5000)
g.chain([f, csvp, round, to_summary1, to_summary2, local_cube])
f.instantiate_on(node)
else:
local_cube.set_overwrite(False)
query_rate = 1000 if ANALYZE else 3600 * 1000
if options.no_backoff:
pull_from_local = jsapi.TimeSubscriber(g, {}, query_rate)
else:
pull_from_local = jsapi.VariableCoarseningSubscriber(
g, {}, query_rate)
pull_from_local.instantiate_on(node)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset", 2000) #but trailing by a few
# pull_from_local.set_cfg("rollup_levels", "8,1")
# pull_from_local.set_cfg("window_size", "5000")
local_cube.instantiate_on(node)
count_logger = jsapi.CountLogger(g, field=4)
timestamp_op = jsapi.TimestampOperator(g, "ms")
count_extend_op = jsapi.ExtendOperator(g, "i",
["1"]) #why is this here? -asr?
count_extend_op.instantiate_on(
node) # TODO should get a real hostname here
timestamp_cube_op = jsapi.TimestampOperator(g, "ms")
timestamp_cube_op.instantiate_on(root_node)
g.chain([
local_cube, pull_from_local, count_logger, timestamp_op,
count_extend_op, timestamp_cube_op, central_cube
])
if options.bw_cap:
timestamp_cube_op.set_inlink_bwcap(float(options.bw_cap))
# g.chain([local_cube, pull_from_local, count_op, q_op, q_op2, echo] )
return g
def get_graph(source_nodes, root_node, options):
g = jsapi.QueryGraph()
ANALYZE = not options.load_only
LOADING = not options.analyze_only
ECHO_RESULTS = not options.no_echo
MULTIROUND = options.multiround
HASH_SAMPLE = options.hash_sample
if not LOADING and not ANALYZE:
print "can't do neither load nor analysis"
sys.exit(0)
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_ua")
central_cube.instantiate_on(root_node)
define_cube(central_cube)
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {},
5000,
sort_order="-count",
num_results=10)
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
pull_q.set_cfg("rollup_levels", "8,1")
pull_q.set_cfg("simulation_rate", 1)
pull_q.set_cfg("window_offset", 6 * 1000) #but trailing by a few
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([central_cube, pull_q, echo])
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
congest_logger.set_cfg("field", 3)
if MULTIROUND:
tput_merge = jsapi.MultiRoundCoord(g)
tput_merge.set_cfg("start_ts", start_ts)
tput_merge.set_cfg("window_offset", 5 * 1000)
tput_merge.set_cfg("ts_field", 0)
tput_merge.set_cfg("num_results", 10)
tput_merge.set_cfg("sort_column", "-count")
tput_merge.set_cfg("min_window_size", 5)
# tput_merge.set_cfg("rollup_levels", "8,1") # roll up time
tput_merge.instantiate_on(root_node)
pull_q.set_cfg("window_offset", 10 * 1000) #but trailing by a few
g.connect(tput_merge, congest_logger)
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['HTTP_stat'],\
coral_fidxs['URL_requested'], len(coral_types) ]
for node, i in numbered(source_nodes, not LOADING):
table_prefix = "local_coral_ua"
table_prefix += "_" + options.warp_factor
local_cube = g.add_cube(table_prefix + ("_%d" % i))
define_cube(local_cube, parsed_field_offsets)
print "cube output dimensions:", local_cube.get_output_dimensions()
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
if not options.full_url:
url_to_dom = jsapi.URLToDomain(
g, field=coral_fidxs['URL_requested'])
g.chain([f, csvp, round, url_to_dom, local_cube])
else:
g.chain([f, csvp, round, local_cube])
f.instantiate_on(node)
else:
local_cube.set_overwrite(False)
if MULTIROUND:
pull_from_local = jsapi.MultiRoundClient(g)
else:
query_rate = 1000 if ANALYZE else 3600 * 1000
pull_from_local = jsapi.VariableCoarseningSubscriber(
g, {}, query_rate)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("max_window_size", options.max_rollup)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset",
2000) #but trailing by a few
pull_from_local.instantiate_on(node)
local_cube.instantiate_on(node)
lastOp = g.chain([local_cube, pull_from_local, congest_logger])
g.chain([congest_logger, central_cube])
return g
def get_graph(source_nodes, root_node, options):
g = jsapi.QueryGraph()
ANALYZE = not options.load_only
LOADING = not options.analyze_only
ECHO_RESULTS = not options.no_echo
ONE_LAYER = True
if not LOADING and not ANALYZE:
print "can't do neither load nor analysis"
sys.exit(0)
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_bw")
central_cube.instantiate_on(root_node)
if ONE_LAYER:
define_cube(central_cube)
else:
define_cube(central_cube, [0, 2, 1])
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 1000) #every two seconds
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
# pull_q.set_cfg("rollup_levels", "8,1")
pull_q.set_cfg("simulation_rate", 1)
pull_q.set_cfg("window_offset", 4 * 1000) #but trailing by a few
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([central_cube, pull_q, echo])
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
g.connect(congest_logger, central_cube)
if not ONE_LAYER:
n_to_intermediate, intermediates = get_intermediates(source_nodes)
intermed_cubes = []
for n, i in zip(intermediates, range(0, len(intermediates))):
med_cube = g.add_cube("med_coral_bw_%i" % i)
med_cube.instantiate_on(n)
med_cube.add_dim("time", CubeSchema.Dimension.TIME_CONTAINMENT, 0)
med_cube.add_agg("sizes", jsapi.Cube.AggType.COUNT, 2)
intermed_cubes.append(med_cube)
connect_to_root(g, med_cube, n, congest_logger, start_ts)
for node, i in numbered(source_nodes, not LOADING):
local_cube = g.add_cube("local_coral_bw_%d" % i)
local_cube.add_dim("time", CubeSchema.Dimension.TIME_CONTAINMENT,
coral_fidxs['timestamp'])
local_cube.add_agg("sizes", jsapi.Cube.AggType.COUNT,
coral_fidxs['nbytes'])
print "cube output dimensions:", local_cube.get_output_dimensions()
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
g.chain([f, csvp, round, local_cube])
f.instantiate_on(node)
else:
local_cube.set_overwrite(False)
if ONE_LAYER:
print node
my_root = congest_logger
else:
print "multi-layer not yet implemented"
sys.exit(0)
intermed_id = n_to_intermediate[node]
my_root = intermed_cubes[intermed_id]
connect_to_root(g, local_cube, node, my_root, start_ts, ANALYZE)
return g
def get_graph(source_nodes, root_node, options):
g = jsapi.QueryGraph()
ANALYZE = not options.load_only
LOADING = not options.analyze_only
ECHO_RESULTS = not options.no_echo
if not LOADING and not ANALYZE:
print "can't do neither load nor analysis"
sys.exit(0)
start_ts = parse_ts(options.start_ts)
central_cube = g.add_cube("global_coral_bw")
central_cube.instantiate_on(root_node)
define_cube(central_cube)
if ECHO_RESULTS:
pull_q = jsapi.TimeSubscriber(g, {}, 1000) #every two seconds
pull_q.set_cfg("ts_field", 0)
pull_q.set_cfg("start_ts", start_ts)
# pull_q.set_cfg("rollup_levels", "8,1")
pull_q.set_cfg("simulation_rate", 1)
pull_q.set_cfg("window_offset", 4 * 1000) #but trailing by a few
q_op = jsapi.Quantile(g, 0.95, 1)
echo = jsapi.Echo(g)
echo.instantiate_on(root_node)
g.chain([central_cube, pull_q, q_op, echo])
congest_logger = jsapi.AvgCongestLogger(g)
congest_logger.instantiate_on(root_node)
g.connect(congest_logger, central_cube)
parsed_field_offsets = [coral_fidxs['timestamp'], coral_fidxs['nbytes']]
for node, i in numbered(source_nodes, not LOADING):
local_cube = g.add_cube("local_coral_quant_%d" % i)
define_cube(local_cube, parsed_field_offsets)
print "cube output dimensions:", local_cube.get_output_dimensions()
if LOADING:
f = jsapi.FileRead(g, options.fname, skip_empty=True)
csvp = jsapi.CSVParse(g, coral_types)
csvp.set_cfg("discard_off_size", "true")
round = jsapi.TimeWarp(g, field=1, warp=options.warp_factor)
to_summary1 = jsapi.ToSummary(g,
field=parsed_field_offsets[1],
size=100)
g.chain([f, csvp, round, to_summary1, local_cube])
f.instantiate_on(node)
else:
local_cube.set_overwrite(False)
query_rate = 1000 if ANALYZE else 3600 * 1000
pull_from_local = jsapi.TimeSubscriber(g, {}, query_rate)
pull_from_local.instantiate_on(node)
pull_from_local.set_cfg("simulation_rate", 1)
pull_from_local.set_cfg("ts_field", 0)
pull_from_local.set_cfg("start_ts", start_ts)
pull_from_local.set_cfg("window_offset", 2000) #but trailing by a few
# pull_from_local.set_cfg("rollup_levels", "8,1")
# pull_from_local.set_cfg("window_size", "5000")
local_cube.instantiate_on(node)
g.chain([local_cube, pull_from_local, congest_logger])
return g
