From: david-sarah Date: Mon, 27 Feb 2012 19:03:17 +0000 (+0000) Subject: Suppress a warning from win32eventreactor on Windows (patch v2). fixes #1681 X-Git-Url: https://git.rkrishnan.org/components/com_hotproperty/css/reliability?a=commitdiff_plain;h=916d26e7103208fa207259d62ce453a5a8b9acd0;p=tahoe-lafs%2Ftahoe-lafs.git Suppress a warning from win32eventreactor on Windows (patch v2). fixes #1681 --- diff --git a/misc/operations_helpers/provisioning/provisioning.py b/misc/operations_helpers/provisioning/provisioning.py deleted file mode 100644 index 37acd16d..00000000 --- a/misc/operations_helpers/provisioning/provisioning.py +++ /dev/null @@ -1,776 +0,0 @@ - -from nevow import inevow, rend, loaders, tags as T -import math -import util - -# factorial and binomial copied from -# http://mail.python.org/pipermail/python-list/2007-April/435718.html - -def div_ceil(n, d): - """ - The smallest integer k such that k*d >= n. - """ - return (n/d) + (n%d != 0) - -def factorial(n): - """factorial(n): return the factorial of the integer n. - factorial(0) = 1 - factorial(n) with n<0 is -factorial(abs(n)) - """ - result = 1 - for i in xrange(1, abs(n)+1): - result *= i - assert n >= 0 - return result - -def binomial(n, k): - assert 0 <= k <= n - if k == 0 or k == n: - return 1 - # calculate n!/k! as one product, avoiding factors that - # just get canceled - P = k+1 - for i in xrange(k+2, n+1): - P *= i - # if you are paranoid: - # C, rem = divmod(P, factorial(n-k)) - # assert rem == 0 - # return C - return P//factorial(n-k) - -class ProvisioningTool(rend.Page): - addSlash = True - docFactory = loaders.xmlfile(util.sibling("provisioning.xhtml")) - - def render_forms(self, ctx, data): - req = inevow.IRequest(ctx) - - def getarg(name, astype=int): - if req.method != "POST": - return None - if name in req.fields: - return astype(req.fields[name].value) - return None - return self.do_forms(getarg) - - - def do_forms(self, getarg): - filled = getarg("filled", bool) - - def get_and_set(name, options, default=None, astype=int): - current_value = getarg(name, astype) - i_select = T.select(name=name) - for (count, description) in options: - count = astype(count) - if ((current_value is not None and count == current_value) or - (current_value is None and count == default)): - o = T.option(value=str(count), selected="true")[description] - else: - o = T.option(value=str(count))[description] - i_select = i_select[o] - if current_value is None: - current_value = default - return current_value, i_select - - sections = {} - def add_input(section, text, entry): - if section not in sections: - sections[section] = [] - sections[section].extend([T.div[text, ": ", entry], "\n"]) - - def add_output(section, entry): - if section not in sections: - sections[section] = [] - sections[section].extend([entry, "\n"]) - - def build_section(section): - return T.fieldset[T.legend[section], sections[section]] - - def number(value, suffix=""): - scaling = 1 - if value < 1: - fmt = "%1.2g%s" - elif value < 100: - fmt = "%.1f%s" - elif value < 1000: - fmt = "%d%s" - elif value < 1e6: - fmt = "%.2fk%s"; scaling = 1e3 - elif value < 1e9: - fmt = "%.2fM%s"; scaling = 1e6 - elif value < 1e12: - fmt = "%.2fG%s"; scaling = 1e9 - elif value < 1e15: - fmt = "%.2fT%s"; scaling = 1e12 - elif value < 1e18: - fmt = "%.2fP%s"; scaling = 1e15 - else: - fmt = "huge! %g%s" - return fmt % (value / scaling, suffix) - - user_counts = [(5, "5 users"), - (50, "50 users"), - (200, "200 users"), - (1000, "1k users"), - (10000, "10k users"), - (50000, "50k users"), - (100000, "100k users"), - (500000, "500k users"), - (1000000, "1M users"), - ] - num_users, i_num_users = get_and_set("num_users", user_counts, 50000) - add_input("Users", - "How many users are on this network?", i_num_users) - - files_per_user_counts = [(100, "100 files"), - (1000, "1k files"), - (10000, "10k files"), - (100000, "100k files"), - (1e6, "1M files"), - ] - files_per_user, i_files_per_user = get_and_set("files_per_user", - files_per_user_counts, - 1000) - add_input("Users", - "How many files for each user? (avg)", - i_files_per_user) - - space_per_user_sizes = [(1e6, "1MB"), - (10e6, "10MB"), - (100e6, "100MB"), - (200e6, "200MB"), - (1e9, "1GB"), - (2e9, "2GB"), - (5e9, "5GB"), - (10e9, "10GB"), - (100e9, "100GB"), - (1e12, "1TB"), - (2e12, "2TB"), - (5e12, "5TB"), - ] - # Estimate ~5gb per user as a more realistic case - space_per_user, i_space_per_user = get_and_set("space_per_user", - space_per_user_sizes, - 5e9) - add_input("Users", - "How much data for each user? (avg)", - i_space_per_user) - - sharing_ratios = [(1.0, "1.0x"), - (1.1, "1.1x"), - (2.0, "2.0x"), - ] - sharing_ratio, i_sharing_ratio = get_and_set("sharing_ratio", - sharing_ratios, 1.0, - float) - add_input("Users", - "What is the sharing ratio? (1.0x is no-sharing and" - " no convergence)", i_sharing_ratio) - - # Encoding parameters - encoding_choices = [("3-of-10-5", "3.3x (3-of-10, repair below 5)"), - ("3-of-10-8", "3.3x (3-of-10, repair below 8)"), - ("5-of-10-7", "2x (5-of-10, repair below 7)"), - ("8-of-10-9", "1.25x (8-of-10, repair below 9)"), - ("27-of-30-28", "1.1x (27-of-30, repair below 28"), - ("25-of-100-50", "4x (25-of-100, repair below 50)"), - ] - encoding_parameters, i_encoding_parameters = \ - get_and_set("encoding_parameters", - encoding_choices, "3-of-10-5", str) - encoding_pieces = encoding_parameters.split("-") - k = int(encoding_pieces[0]) - assert encoding_pieces[1] == "of" - n = int(encoding_pieces[2]) - # we repair the file when the number of available shares drops below - # this value - repair_threshold = int(encoding_pieces[3]) - - add_input("Servers", - "What are the default encoding parameters?", - i_encoding_parameters) - - # Server info - num_server_choices = [ (5, "5 servers"), - (10, "10 servers"), - (15, "15 servers"), - (30, "30 servers"), - (50, "50 servers"), - (100, "100 servers"), - (200, "200 servers"), - (300, "300 servers"), - (500, "500 servers"), - (1000, "1k servers"), - (2000, "2k servers"), - (5000, "5k servers"), - (10e3, "10k servers"), - (100e3, "100k servers"), - (1e6, "1M servers"), - ] - num_servers, i_num_servers = \ - get_and_set("num_servers", num_server_choices, 30, int) - add_input("Servers", - "How many servers are there?", i_num_servers) - - # availability is measured in dBA = -dBF, where 0dBF is 100% failure, - # 10dBF is 10% failure, 20dBF is 1% failure, etc - server_dBA_choices = [ (10, "90% [10dBA] (2.4hr/day)"), - (13, "95% [13dBA] (1.2hr/day)"), - (20, "99% [20dBA] (14min/day or 3.5days/year)"), - (23, "99.5% [23dBA] (7min/day or 1.75days/year)"), - (30, "99.9% [30dBA] (87sec/day or 9hours/year)"), - (40, "99.99% [40dBA] (60sec/week or 53min/year)"), - (50, "99.999% [50dBA] (5min per year)"), - ] - server_dBA, i_server_availability = \ - get_and_set("server_availability", - server_dBA_choices, - 20, int) - add_input("Servers", - "What is the server availability?", i_server_availability) - - drive_MTBF_choices = [ (40, "40,000 Hours"), - ] - drive_MTBF, i_drive_MTBF = \ - get_and_set("drive_MTBF", drive_MTBF_choices, 40, int) - add_input("Drives", - "What is the hard drive MTBF?", i_drive_MTBF) - # http://www.tgdaily.com/content/view/30990/113/ - # http://labs.google.com/papers/disk_failures.pdf - # google sees: - # 1.7% of the drives they replaced were 0-1 years old - # 8% of the drives they repalced were 1-2 years old - # 8.6% were 2-3 years old - # 6% were 3-4 years old, about 8% were 4-5 years old - - drive_size_choices = [ (100, "100 GB"), - (250, "250 GB"), - (500, "500 GB"), - (750, "750 GB"), - (1000, "1000 GB"), - (2000, "2000 GB"), - (3000, "3000 GB"), - ] - drive_size, i_drive_size = \ - get_and_set("drive_size", drive_size_choices, 3000, int) - drive_size = drive_size * 1e9 - add_input("Drives", - "What is the capacity of each hard drive?", i_drive_size) - drive_failure_model_choices = [ ("E", "Exponential"), - ("U", "Uniform"), - ] - drive_failure_model, i_drive_failure_model = \ - get_and_set("drive_failure_model", - drive_failure_model_choices, - "E", str) - add_input("Drives", - "How should we model drive failures?", i_drive_failure_model) - - # drive_failure_rate is in failures per second - if drive_failure_model == "E": - drive_failure_rate = 1.0 / (drive_MTBF * 1000 * 3600) - else: - drive_failure_rate = 0.5 / (drive_MTBF * 1000 * 3600) - - # deletion/gc/ownership mode - ownership_choices = [ ("A", "no deletion, no gc, no owners"), - ("B", "deletion, no gc, no owners"), - ("C", "deletion, share timers, no owners"), - ("D", "deletion, no gc, yes owners"), - ("E", "deletion, owner timers"), - ] - ownership_mode, i_ownership_mode = \ - get_and_set("ownership_mode", ownership_choices, - "A", str) - add_input("Servers", - "What is the ownership mode?", i_ownership_mode) - - # client access behavior - access_rates = [ (1, "one file per day"), - (10, "10 files per day"), - (100, "100 files per day"), - (1000, "1k files per day"), - (10e3, "10k files per day"), - (100e3, "100k files per day"), - ] - download_files_per_day, i_download_rate = \ - get_and_set("download_rate", access_rates, - 100, int) - add_input("Users", - "How many files are downloaded per day?", i_download_rate) - download_rate = 1.0 * download_files_per_day / (24*60*60) - - upload_files_per_day, i_upload_rate = \ - get_and_set("upload_rate", access_rates, - 10, int) - add_input("Users", - "How many files are uploaded per day?", i_upload_rate) - upload_rate = 1.0 * upload_files_per_day / (24*60*60) - - delete_files_per_day, i_delete_rate = \ - get_and_set("delete_rate", access_rates, - 10, int) - add_input("Users", - "How many files are deleted per day?", i_delete_rate) - delete_rate = 1.0 * delete_files_per_day / (24*60*60) - - - # the value is in days - lease_timers = [ (1, "one refresh per day"), - (7, "one refresh per week"), - ] - lease_timer, i_lease = \ - get_and_set("lease_timer", lease_timers, - 7, int) - add_input("Users", - "How frequently do clients refresh files or accounts? " - "(if necessary)", - i_lease) - seconds_per_lease = 24*60*60*lease_timer - - check_timer_choices = [ (1, "every week"), - (4, "every month"), - (8, "every two months"), - (16, "every four months"), - ] - check_timer, i_check_timer = \ - get_and_set("check_timer", check_timer_choices, 4, int) - add_input("Users", - "How frequently should we check on each file?", - i_check_timer) - file_check_interval = check_timer * 7 * 24 * 3600 - - - if filled: - add_output("Users", T.div["Total users: %s" % number(num_users)]) - add_output("Users", - T.div["Files per user: %s" % number(files_per_user)]) - file_size = 1.0 * space_per_user / files_per_user - add_output("Users", - T.div["Average file size: ", number(file_size)]) - total_files = num_users * files_per_user / sharing_ratio - - add_output("Grid", - T.div["Total number of files in grid: ", - number(total_files)]) - total_space = num_users * space_per_user / sharing_ratio - add_output("Grid", - T.div["Total volume of plaintext in grid: ", - number(total_space, "B")]) - - total_shares = n * total_files - add_output("Grid", - T.div["Total shares in grid: ", number(total_shares)]) - expansion = float(n) / float(k) - - total_usage = expansion * total_space - add_output("Grid", - T.div["Share data in grid: ", number(total_usage, "B")]) - - if n > num_servers: - # silly configuration, causes Tahoe2 to wrap and put multiple - # shares on some servers. - add_output("Servers", - T.div["non-ideal: more shares than servers" - " (n=%d, servers=%d)" % (n, num_servers)]) - # every file has at least one share on every server - buckets_per_server = total_files - shares_per_server = total_files * ((1.0 * n) / num_servers) - else: - # if nobody is full, then no lease requests will be turned - # down for lack of space, and no two shares for the same file - # will share a server. Therefore the chance that any given - # file has a share on any given server is n/num_servers. - buckets_per_server = total_files * ((1.0 * n) / num_servers) - # since each such represented file only puts one share on a - # server, the total number of shares per server is the same. - shares_per_server = buckets_per_server - add_output("Servers", - T.div["Buckets per server: ", - number(buckets_per_server)]) - add_output("Servers", - T.div["Shares per server: ", - number(shares_per_server)]) - - # how much space is used on the storage servers for the shares? - # the share data itself - share_data_per_server = total_usage / num_servers - add_output("Servers", - T.div["Share data per server: ", - number(share_data_per_server, "B")]) - # this is determined empirically. H=hashsize=32, for a one-segment - # file and 3-of-10 encoding - share_validation_per_server = 266 * shares_per_server - # this could be 423*buckets_per_server, if we moved the URI - # extension into a separate file, but that would actually consume - # *more* space (minimum filesize is 4KiB), unless we moved all - # shares for a given bucket into a single file. - share_uri_extension_per_server = 423 * shares_per_server - - # ownership mode adds per-bucket data - H = 32 # depends upon the desired security of delete/refresh caps - # bucket_lease_size is the amount of data needed to keep track of - # the delete/refresh caps for each bucket. - bucket_lease_size = 0 - client_bucket_refresh_rate = 0 - owner_table_size = 0 - if ownership_mode in ("B", "C", "D", "E"): - bucket_lease_size = sharing_ratio * 1.0 * H - if ownership_mode in ("B", "C"): - # refreshes per second per client - client_bucket_refresh_rate = (1.0 * n * files_per_user / - seconds_per_lease) - add_output("Users", - T.div["Client share refresh rate (outbound): ", - number(client_bucket_refresh_rate, "Hz")]) - server_bucket_refresh_rate = (client_bucket_refresh_rate * - num_users / num_servers) - add_output("Servers", - T.div["Server share refresh rate (inbound): ", - number(server_bucket_refresh_rate, "Hz")]) - if ownership_mode in ("D", "E"): - # each server must maintain a bidirectional mapping from - # buckets to owners. One way to implement this would be to - # put a list of four-byte owner numbers into each bucket, and - # a list of four-byte share numbers into each owner (although - # of course we'd really just throw it into a database and let - # the experts take care of the details). - owner_table_size = 2*(buckets_per_server * sharing_ratio * 4) - - if ownership_mode in ("E",): - # in this mode, clients must refresh one timer per server - client_account_refresh_rate = (1.0 * num_servers / - seconds_per_lease) - add_output("Users", - T.div["Client account refresh rate (outbound): ", - number(client_account_refresh_rate, "Hz")]) - server_account_refresh_rate = (client_account_refresh_rate * - num_users / num_servers) - add_output("Servers", - T.div["Server account refresh rate (inbound): ", - number(server_account_refresh_rate, "Hz")]) - - # TODO: buckets vs shares here is a bit wonky, but in - # non-wrapping grids it shouldn't matter - share_lease_per_server = bucket_lease_size * buckets_per_server - share_ownertable_per_server = owner_table_size - - share_space_per_server = (share_data_per_server + - share_validation_per_server + - share_uri_extension_per_server + - share_lease_per_server + - share_ownertable_per_server) - add_output("Servers", - T.div["Share space per server: ", - number(share_space_per_server, "B"), - " (data ", - number(share_data_per_server, "B"), - ", validation ", - number(share_validation_per_server, "B"), - ", UEB ", - number(share_uri_extension_per_server, "B"), - ", lease ", - number(share_lease_per_server, "B"), - ", ownertable ", - number(share_ownertable_per_server, "B"), - ")", - ]) - - - # rates - client_download_share_rate = download_rate * k - client_download_byte_rate = download_rate * file_size - add_output("Users", - T.div["download rate: shares = ", - number(client_download_share_rate, "Hz"), - " , bytes = ", - number(client_download_byte_rate, "Bps"), - ]) - total_file_check_rate = 1.0 * total_files / file_check_interval - client_check_share_rate = total_file_check_rate / num_users - add_output("Users", - T.div["file check rate: shares = ", - number(client_check_share_rate, "Hz"), - " (interval = %s)" % - number(1 / client_check_share_rate, "s"), - ]) - - client_upload_share_rate = upload_rate * n - # TODO: doesn't include overhead - client_upload_byte_rate = upload_rate * file_size * expansion - add_output("Users", - T.div["upload rate: shares = ", - number(client_upload_share_rate, "Hz"), - " , bytes = ", - number(client_upload_byte_rate, "Bps"), - ]) - client_delete_share_rate = delete_rate * n - - server_inbound_share_rate = (client_upload_share_rate * - num_users / num_servers) - server_inbound_byte_rate = (client_upload_byte_rate * - num_users / num_servers) - add_output("Servers", - T.div["upload rate (inbound): shares = ", - number(server_inbound_share_rate, "Hz"), - " , bytes = ", - number(server_inbound_byte_rate, "Bps"), - ]) - add_output("Servers", - T.div["share check rate (inbound): ", - number(total_file_check_rate * n / num_servers, - "Hz"), - ]) - - server_share_modify_rate = ((client_upload_share_rate + - client_delete_share_rate) * - num_users / num_servers) - add_output("Servers", - T.div["share modify rate: shares = ", - number(server_share_modify_rate, "Hz"), - ]) - - server_outbound_share_rate = (client_download_share_rate * - num_users / num_servers) - server_outbound_byte_rate = (client_download_byte_rate * - num_users / num_servers) - add_output("Servers", - T.div["download rate (outbound): shares = ", - number(server_outbound_share_rate, "Hz"), - " , bytes = ", - number(server_outbound_byte_rate, "Bps"), - ]) - - - total_share_space = num_servers * share_space_per_server - add_output("Grid", - T.div["Share space consumed: ", - number(total_share_space, "B")]) - add_output("Grid", - T.div[" %% validation: %.2f%%" % - (100.0 * share_validation_per_server / - share_space_per_server)]) - add_output("Grid", - T.div[" %% uri-extension: %.2f%%" % - (100.0 * share_uri_extension_per_server / - share_space_per_server)]) - add_output("Grid", - T.div[" %% lease data: %.2f%%" % - (100.0 * share_lease_per_server / - share_space_per_server)]) - add_output("Grid", - T.div[" %% owner data: %.2f%%" % - (100.0 * share_ownertable_per_server / - share_space_per_server)]) - add_output("Grid", - T.div[" %% share data: %.2f%%" % - (100.0 * share_data_per_server / - share_space_per_server)]) - add_output("Grid", - T.div["file check rate: ", - number(total_file_check_rate, - "Hz")]) - - total_drives = max(div_ceil(int(total_share_space), - int(drive_size)), - num_servers) - add_output("Drives", - T.div["Total drives: ", number(total_drives), " drives"]) - drives_per_server = div_ceil(total_drives, num_servers) - add_output("Servers", - T.div["Drives per server: ", drives_per_server]) - - # costs - if drive_size == 3000 * 1e9: - add_output("Servers", T.div["3000GB drive: $250 each"]) - drive_cost = 250 - else: - add_output("Servers", - T.div[T.b["unknown cost per drive, assuming $100"]]) - drive_cost = 100 - - if drives_per_server <= 4: - add_output("Servers", T.div["1U box with <= 4 drives: $1500"]) - server_cost = 1500 # typical 1U box - elif drives_per_server <= 12: - add_output("Servers", T.div["2U box with <= 12 drives: $2500"]) - server_cost = 2500 # 2U box - else: - add_output("Servers", - T.div[T.b["Note: too many drives per server, " - "assuming $3000"]]) - server_cost = 3000 - - server_capital_cost = (server_cost + drives_per_server * drive_cost) - total_server_cost = float(num_servers * server_capital_cost) - add_output("Servers", T.div["Capital cost per server: $", - server_capital_cost]) - add_output("Grid", T.div["Capital cost for all servers: $", - number(total_server_cost)]) - # $70/Mbps/mo - # $44/server/mo power+space - server_bandwidth = max(server_inbound_byte_rate, - server_outbound_byte_rate) - server_bandwidth_mbps = div_ceil(int(server_bandwidth*8), int(1e6)) - server_monthly_cost = 70*server_bandwidth_mbps + 44 - add_output("Servers", T.div["Monthly cost per server: $", - server_monthly_cost]) - add_output("Users", T.div["Capital cost per user: $", - number(total_server_cost / num_users)]) - - # reliability - any_drive_failure_rate = total_drives * drive_failure_rate - any_drive_MTBF = 1 // any_drive_failure_rate # in seconds - any_drive_MTBF_days = any_drive_MTBF / 86400 - add_output("Drives", - T.div["MTBF (any drive): ", - number(any_drive_MTBF_days), " days"]) - drive_replacement_monthly_cost = (float(drive_cost) - * any_drive_failure_rate - *30*86400) - add_output("Grid", - T.div["Monthly cost of replacing drives: $", - number(drive_replacement_monthly_cost)]) - - total_server_monthly_cost = float(num_servers * server_monthly_cost - + drive_replacement_monthly_cost) - - add_output("Grid", T.div["Monthly cost for all servers: $", - number(total_server_monthly_cost)]) - add_output("Users", - T.div["Monthly cost per user: $", - number(total_server_monthly_cost / num_users)]) - - # availability - file_dBA = self.file_availability(k, n, server_dBA) - user_files_dBA = self.many_files_availability(file_dBA, - files_per_user) - all_files_dBA = self.many_files_availability(file_dBA, total_files) - add_output("Users", - T.div["availability of: ", - "arbitrary file = %d dBA, " % file_dBA, - "all files of user1 = %d dBA, " % user_files_dBA, - "all files in grid = %d dBA" % all_files_dBA, - ], - ) - - time_until_files_lost = (n-k+1) / any_drive_failure_rate - add_output("Grid", - T.div["avg time until files are lost: ", - number(time_until_files_lost, "s"), ", ", - number(time_until_files_lost/86400, " days"), - ]) - - share_data_loss_rate = any_drive_failure_rate * drive_size - add_output("Grid", - T.div["share data loss rate: ", - number(share_data_loss_rate,"Bps")]) - - # the worst-case survival numbers occur when we do a file check - # and the file is just above the threshold for repair (so we - # decide to not repair it). The question is then: what is the - # chance that the file will decay so badly before the next check - # that we can't recover it? The resulting probability is per - # check interval. - # Note that the chances of us getting into this situation are low. - P_disk_failure_during_interval = (drive_failure_rate * - file_check_interval) - disk_failure_dBF = 10*math.log10(P_disk_failure_during_interval) - disk_failure_dBA = -disk_failure_dBF - file_survives_dBA = self.file_availability(k, repair_threshold, - disk_failure_dBA) - user_files_survives_dBA = self.many_files_availability( \ - file_survives_dBA, files_per_user) - all_files_survives_dBA = self.many_files_availability( \ - file_survives_dBA, total_files) - add_output("Users", - T.div["survival of: ", - "arbitrary file = %d dBA, " % file_survives_dBA, - "all files of user1 = %d dBA, " % - user_files_survives_dBA, - "all files in grid = %d dBA" % - all_files_survives_dBA, - " (per worst-case check interval)", - ]) - - - - all_sections = [] - all_sections.append(build_section("Users")) - all_sections.append(build_section("Servers")) - all_sections.append(build_section("Drives")) - if "Grid" in sections: - all_sections.append(build_section("Grid")) - - f = T.form(action=".", method="post", enctype="multipart/form-data") - - if filled: - action = "Recompute" - else: - action = "Compute" - - f = f[T.input(type="hidden", name="filled", value="true"), - T.input(type="submit", value=action), - all_sections, - ] - - try: - from allmydata import reliability - # we import this just to test to see if the page is available - _hush_pyflakes = reliability - del _hush_pyflakes - f = [T.div[T.a(href="../reliability")["Reliability Math"]], f] - except ImportError: - pass - - return f - - def file_availability(self, k, n, server_dBA): - """ - The full formula for the availability of a specific file is:: - - 1 - sum([choose(N,i) * p**i * (1-p)**(N-i)] for i in range(k)]) - - Where choose(N,i) = N! / ( i! * (N-i)! ) . Note that each term of - this summation is the probability that there are exactly 'i' servers - available, and what we're doing is adding up the cases where i is too - low. - - This is a nuisance to calculate at all accurately, especially once N - gets large, and when p is close to unity. So we make an engineering - approximation: if (1-p) is very small, then each [i] term is much - larger than the [i-1] term, and the sum is dominated by the i=k-1 - term. This only works for (1-p) < 10%, and when the choose() function - doesn't rise fast enough to compensate. For high-expansion encodings - (3-of-10, 25-of-100), the choose() function is rising at the same - time as the (1-p)**(N-i) term, so that's not an issue. For - low-expansion encodings (7-of-10, 75-of-100) the two values are - moving in opposite directions, so more care must be taken. - - Note that the p**i term has only a minor effect as long as (1-p)*N is - small, and even then the effect is attenuated by the 1-p term. - """ - - assert server_dBA > 9 # >=90% availability to use the approximation - factor = binomial(n, k-1) - factor_dBA = 10 * math.log10(factor) - exponent = n - k + 1 - file_dBA = server_dBA * exponent - factor_dBA - return file_dBA - - def many_files_availability(self, file_dBA, num_files): - """The probability that 'num_files' independent bernoulli trials will - succeed (i.e. we can recover all files in the grid at any given - moment) is p**num_files . Since p is close to unity, we express in p - in dBA instead, so we can get useful precision on q (=1-p), and then - the formula becomes:: - - P_some_files_unavailable = 1 - (1 - q)**num_files - - That (1-q)**n expands with the usual binomial sequence, 1 - nq + - Xq**2 ... + Xq**n . We use the same approximation as before, since we - know q is close to zero, and we get to ignore all the terms past -nq. - """ - - many_files_dBA = file_dBA - 10 * math.log10(num_files) - return many_files_dBA diff --git a/src/allmydata/_auto_deps.py b/src/allmydata/_auto_deps.py index 44d50d76..5bb2b13a 100644 --- a/src/allmydata/_auto_deps.py +++ b/src/allmydata/_auto_deps.py @@ -120,6 +120,7 @@ deprecation_messages = [ user_warning_messages = [ "Hashing uninitialized InterfaceClass instance", + "Reliable disconnection notification requires pywin32 215 or later", ] warning_imports = [