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moar refactor

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This commit is contained in:
Oskar Thoren 2019-10-16 15:50:53 +08:00
parent ac4087d25a
commit 4da6dcf7c1
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GPG Key ID: B2ECCFD3BC2EF77E
1 changed files with 32 additions and 58 deletions
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90
whisper_scalability/whisper.py
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@ -44,6 +44,22 @@ def load_color_fmt(load, string):
def print_header(string):
print bcolors.HEADER + string + bcolors.ENDC + "\n"
def print_assumptions(xs):
print "Assumptions:"
for x in xs:
print x
print ""
def usage_str(load_users_fn, n_users):
load = load_users_fn(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users_fn(n_users)) + "/day")
def print_usage(load_users):
print usage_str(load_users, 100)
print usage_str(load_users, 100 * 100)
print usage_str(load_users, 100 * 100 * 100)
print ""
# Assumptions
#-----------------------------------------------------------
@ -116,55 +132,34 @@ a12 = "- A12. Bloom filter elements, i.e. topics, (n) (static): " + str(bloom_el
a13 = "- A13. Bloom filter optimal k choice (sensitive to m, n)"
a14 = "- A14. Bloom filter false positive proportion of full traffic, p=" + str(bloom_false_positive)
def print_assumptions(xs):
print "Assumptions:"
for x in xs:
print x
# Cases
#-----------------------------------------------------------
# Case 1: only receiving messages meant for you
def case1():
def load_users(n_users):
return envelope_size * envelopes_per_message * \
received_messages_per_day
def usage_str(n_users):
load = load_users(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users(n_users)) + "/day")
print_header("Case 1. Only receiving messages meant for you")
print_assumptions([a1, a2, a3, a4])
print ""
print usage_str(100)
print usage_str(100 * 100)
print usage_str(100 * 100 * 100)
print ""
print_usage(load_users)
print("------------------------------------------------------------")
# Case 2: receiving all messages
def case2():
# Case 2: receiving all messages
def load_users(n_users):
return envelope_size * envelopes_per_message * \
received_messages_per_day * n_users
def usage_str(n_users):
load = load_users(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users(n_users)) + "/day")
print_header("Case 2. Receiving messages for everyone")
print_assumptions([a1, a2, a3, a5])
print ""
print usage_str(100)
print usage_str(100 * 100)
print usage_str(100 * 100 * 100)
print ""
print_usage(load_users)
print("------------------------------------------------------------")
# Case 3: all private messages go over one discovery topic
def case3():
# Case 3: all private messages go over one discovery topic
# Public scales per usage, all private messages are received
# over one discovery topic
@ -177,22 +172,13 @@ def case3():
load_public * (1 - private_message_proportion)
return total_load
def usage_str(n_users):
load = load_users(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users(n_users)) + "/day")
print_header("Case 3. All private messages go over one discovery topic")
print_assumptions([a1, a2, a3, a6, a7, a8])
print ""
print usage_str(100)
print usage_str(100 * 100)
print usage_str(100 * 100 * 100)
print ""
print_usage(load_users)
print("------------------------------------------------------------")
# Case 4: all private messages are partitioned into shards
def case4():
# Case 4: all private messages are partitioned into shards
def load_users(n_users):
if n_users < n_partitions:
@ -209,21 +195,13 @@ def case4():
load_public * (1 - private_message_proportion)
return total_load
def usage_str(n_users):
load = load_users(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users(n_users)) + "/day")
print_header("Case 4. All private messages are partitioned into shards")
print_assumptions([a1, a2, a3, a6, a7, a9])
print ""
print usage_str(100)
print usage_str(100 * 100)
print usage_str(100 * 100 * 100)
print ""
print_usage(load_users)
print("------------------------------------------------------------")
# Case 5: all messages are passed through a bloom filter with a certain false positive rate
def case5():
# Case 5: all messages are passed through a bloom filter with a certain false positive rate
def load_users(n_users):
if n_users < n_partitions:
@ -246,28 +224,24 @@ def case5():
return total_load + false_positive_load
def usage_str(n_users):
load = load_users(n_users)
return load_color_fmt(load, "For " + magnitude_fmt(n_users) + " users, receiving bandwidth is " + sizeof_fmt(load_users(n_users)) + "/day")
print_header("Case 5. Case 4 + All messages are passed through bloom filter with false positive rate")
print_assumptions([a1, a2, a3, a6, a7, a9, a10, a11, a12, a13, a14])
print ""
print usage_str(100)
print usage_str(100 * 100)
print usage_str(100 * 100 * 100)
print ""
print_usage(load_users)
print("------------------------------------------------------------")
# Run cases
#-----------------------------------------------------------
case1()
case2()
case3()
case4()
case5()
# Ok, let's get serious. What assumptions do we need to encode?
# Also, what did I observe? I observed 15GB/m = 500mb per day.
# Misc notes
#-----------------------------------------------------------
# What did I observe? I observed 15GB/m = 500mb per day.
# Things to encode:
# - Noisy topic