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Simon MacMullen 2012-11-16 10:45:36 +00:00
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Copyright (c) 2007-2009 IOLA and Ole Laursen
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@ -8,3 +8,10 @@ Sammy is "Copyright (c) 2008 Aaron Quint, Quirkey NYC, LLC" and is
covered by the MIT license. It was downloaded from
http://code.quirkey.com/sammy/
ExplorerCanvas is "Copyright 2006 Google Inc" and is covered by the
Apache License version 2.0. It was downloaded from
http://code.google.com/p/explorercanvas/
Flot is "Copyright (c) 2007-2009 IOLA and Ole Laursen" and is covered
by the MIT license. It was downloaded from
http://code.google.com/p/flot/

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@ -140,27 +140,52 @@ lookup_element(Table, Key, Pos) ->
result_or_error([]) -> error;
result_or_error(S) -> S.
rates(Stats, Timestamp, OldStats, OldTimestamp, Keys) ->
append_samples(Stats, Timestamp, Id, Table, Keys) ->
OldStats = lookup_element(Table, Id),
OldTimestamp = lookup_element(Table, Id, 3),
Stats ++ [R || Key <- Keys,
R <- [rate(Stats, Timestamp, OldStats, OldTimestamp, Key)],
R <- [append_sample(Stats, Timestamp,
OldStats, OldTimestamp, Key)],
R =/= unknown].
rate(Stats, Timestamp, OldStats, OldTimestamp, Key) ->
case OldTimestamp == [] orelse not proplists:is_defined(Key, OldStats) of
true -> unknown;
false -> Diff = pget(Key, Stats) - pget(Key, OldStats),
Name = details_key(Key),
Interval = timer:now_diff(Timestamp, OldTimestamp),
Rate = Diff / (Interval / 1000000),
{Name, [{rate, Rate},
{interval, Interval},
{last_event,
rabbit_mgmt_format:timestamp_ms(Timestamp)}]}
append_sample(Stats, TS, OldStats, OldTS, Key) ->
KeyDetails = details_key(Key),
case {pget(Key, Stats), pget(Key, OldStats), pget(KeyDetails, OldStats)} of
{unknown, _, _} -> unknown;
{_, unknown, _} -> unknown;
{New, Old, unknown} -> OldMS = rabbit_mgmt_format:timestamp_ms(OldTS),
MS = rabbit_mgmt_format:timestamp_ms(TS),
{KeyDetails,
[[{sample, New}, {timestamp, MS}],
[{sample, Old}, {timestamp, OldMS}]]};
{New, _, Samples} -> MS = rabbit_mgmt_format:timestamp_ms(TS),
{KeyDetails,
[[{sample, New}, {timestamp, MS}] |
remove_old_samples(MS, Samples)]}
end.
sum(List, Keys) ->
lists:foldl(fun (I0, I1) -> gs_update(I0, I1, Keys) end,
gs_update([], [], Keys), List).
%% TODO be less crude
-define(MAX_SAMPLE_AGE, 60000).
remove_old_samples(Now, Samples) ->
Cutoff = Now - ?MAX_SAMPLE_AGE,
[Sample || Sample <- Samples,
pget(timestamp, Sample) > Cutoff].
sum(Keys, List) ->
[{Key, sum2(Key, List)} || Key <- Keys].
sum2(Key, List) ->
case is_details(Key) of
true ->
%% TODO this is a bit crude
[{rate, lists:foldl(fun (Stats, T) ->
T + pget(rate, pget(Key, Stats, []), 0)
end, 0, List)}];
false ->
lists:foldl(fun (Stats, T) ->
T + pget(Key, Stats, 0)
end, 0, List)
end.
%% List = [{ [{channel, Pid}, ...], [{deliver, 123}, ...] } ...]
group_sum([], List) ->
@ -186,25 +211,36 @@ gs_update(Item0, Item1, Keys) ->
[{Key, gs_update_add(Key, pget(Key, Item0), pget(Key, Item1))} ||
Key <- Keys].
-define(SAMPLE_COMBINE_WINDOW, 5000).
gs_update_add(Key, Item0, Item1) ->
case is_details(Key) of
true ->
I0 = if_unknown(Item0, []),
I1 = if_unknown(Item1, []),
%% TODO if I0 and I1 are from different channels then should we not
%% just throw away interval / last_event?
[{rate, pget(rate, I0, 0) + pget(rate, I1, 0)},
{interval, gs_max(interval, I0, I1)},
{last_event, gs_max(last_event, I0, I1)}];
%% TODO this could *ahem* probably be more efficient
%% TODO apportion across samples
%% TODO if I0 and I1 are from different channels then
%% should we do this at all?
Tree = lists:foldl(
fun ([{sample, S},
{timestamp, T}], D) ->
K = (T div ?SAMPLE_COMBINE_WINDOW) *
?SAMPLE_COMBINE_WINDOW,
case gb_trees:lookup(K, D) of
{value, S1} -> gb_trees:update(K, S + S1, D);
none -> gb_trees:insert(K, S, D)
end
end, gb_trees:empty(), I0 ++ I1),
[[{sample, S},
{timestamp, T}] || {T, S} <- lists:reverse(
gb_trees:to_list(Tree))];
false ->
I0 = if_unknown(Item0, 0),
I1 = if_unknown(Item1, 0),
I0 + I1
end.
gs_max(Key, I0, I1) ->
erlang:max(pget(Key, I0, 0), pget(Key, I1, 0)).
if_unknown(unknown, Def) -> Def;
if_unknown(Val, _Def) -> Val.
@ -273,7 +309,7 @@ handle_call({get_overview, User}, _From, State = #state{tables = Tables}) ->
Qs0 = [rabbit_mgmt_format:queue(Q) || V <- VHosts,
Q <- rabbit_amqqueue:list(V)],
Qs1 = basic_queue_stats(Qs0, State),
QueueTotals = sum(Qs1, ?OVERVIEW_QUEUE_STATS),
QueueTotals = sum(?OVERVIEW_QUEUE_STATS, Qs1),
Filter = fun(Id, Name) ->
lists:member(pget(vhost, pget(Name, Id)), VHosts)
@ -283,7 +319,7 @@ handle_call({get_overview, User}, _From, State = #state{tables = Tables}) ->
[], [R || R = {Id, _, _}
<- ets:tab2list(orddict:fetch(Type, Tables)),
Filter(augment_msg_stats(format_id(Id), State),
Name)], State)
Name)])
end,
Publish = F(channel_exchange_stats, exchange),
Consume = F(channel_queue_stats, queue_details),
@ -305,7 +341,7 @@ handle_call({get_overview, User}, _From, State = #state{tables = Tables}) ->
X <- rabbit_exchange:list(V)])},
{connections, F2(created_events(connection_stats, Tables))},
{channels, F2(created_events(channel_stats, Tables))}],
reply([{message_stats, Publish ++ Consume},
reply([{message_stats, calculate_rates(Publish ++ Consume, State)},
{queue_totals, QueueTotals},
{object_totals, ObjectTotals}], State);
@ -434,9 +470,7 @@ handle_stats(TName, Stats0, Timestamp, Funs,
Stats0, ?FINE_STATS_TYPES),
Table = orddict:fetch(TName, Tables),
Id = {id(Stats), stats},
OldStats = lookup_element(Table, Id),
OldTimestamp = lookup_element(Table, Id, 3),
Stats1 = rates(Stats, Timestamp, OldStats, OldTimestamp, RatesKeys),
Stats1 = append_samples(Stats, Timestamp, Id, Table, RatesKeys),
Stats2 = proplists:delete(pid, rabbit_mgmt_format:format(Stats1, Funs)),
ets:insert(Table, {Id, Stats2, Timestamp}),
{ok, State}.
@ -455,36 +489,26 @@ handle_consumer(Fun, Props,
Fun(Table, {pget(queue, P), pget(channel, P)}, P),
{ok, State}.
handle_fine_stats(Type, Props, Timestamp, State = #state{tables = Tables}) ->
handle_fine_stats(Type, Props, Timestamp, #state{tables = Tables}) ->
case pget(Type, Props) of
unknown ->
ok;
AllFineStats ->
ChPid = id(Props),
Table = orddict:fetch(Type, Tables),
IdsStatsTS =
[{Ids,
Stats,
lookup_element(Table, fine_stats_key(ChPid, Ids)),
lookup_element(Table, fine_stats_key(ChPid, Ids), 3)} ||
{Ids, Stats} <- AllFineStats],
delete_fine_stats(Type, ChPid, State),
[handle_fine_stat(ChPid, Ids, Stats, Timestamp,
OldStats, OldTimestamp, Table) ||
{Ids, Stats, OldStats, OldTimestamp} <- IdsStatsTS]
[handle_fine_stat(
fine_stats_id(ChPid, Ids), Stats, Timestamp, Table) ||
{Ids, Stats} <- AllFineStats]
end.
handle_fine_stat(ChPid, Ids, Stats, Timestamp,
OldStats, OldTimestamp,
Table) ->
Id = fine_stats_key(ChPid, Ids),
handle_fine_stat(Id, Stats, Timestamp, Table) ->
Total = lists:sum([V || {K, V} <- Stats, lists:member(K, ?DELIVER_GET)]),
Stats1 = case Total of
0 -> Stats;
_ -> [{deliver_get, Total}|Stats]
end,
Res = rates(Stats1, Timestamp, OldStats, OldTimestamp, ?FINE_STATS),
Res = append_samples(Stats1, Timestamp, Id, Table, ?FINE_STATS),
ets:insert(Table, {Id, Res, Timestamp}).
delete_fine_stats(Type, ChPid, #state{tables = Tables}) ->
@ -492,9 +516,9 @@ delete_fine_stats(Type, ChPid, #state{tables = Tables}) ->
ets:match_delete(Table, {{ChPid, '_'}, '_', '_'}),
ets:match_delete(Table, {{ChPid, '_', '_'}, '_', '_'}).
fine_stats_key(ChPid, {QPid, X}) -> {ChPid, id(QPid), X};
fine_stats_key(ChPid, QPid) when is_pid(QPid) -> {ChPid, id(QPid)};
fine_stats_key(ChPid, X) -> {ChPid, X}.
fine_stats_id(ChPid, {QPid, X}) -> {ChPid, id(QPid), X};
fine_stats_id(ChPid, QPid) when is_pid(QPid) -> {ChPid, id(QPid)};
fine_stats_id(ChPid, X) -> {ChPid, X}.
created_event(Names, Type, Tables) ->
Table = orddict:fetch(Type, Tables),
@ -508,12 +532,12 @@ created_events(Type, Tables) ->
[Facts || {{_, create}, Facts, _Name}
<- ets:tab2list(orddict:fetch(Type, Tables))].
get_fine_stats(Type, GroupBy, State = #state{tables = Tables}) ->
get_fine_stats(Type, GroupBy, #state{tables = Tables}) ->
get_fine_stats_from_list(
GroupBy, ets:tab2list(orddict:fetch(Type, Tables)), State).
GroupBy, ets:tab2list(orddict:fetch(Type, Tables))).
get_fine_stats_from_list(GroupBy, List, State) ->
All = [{format_id(Id), zero_old_rates(Stats, State)} ||
get_fine_stats_from_list(GroupBy, List) ->
All = [{format_id(Id), Stats} ||
{Id, Stats, _Timestamp} <- List],
group_sum(GroupBy, All).
@ -534,7 +558,7 @@ merge_stats(Objs, Funs) ->
basic_stats_fun(Type, IdProperty, State = #state{tables = Tables}) ->
Table = orddict:fetch(Type, Tables),
fun (Props) ->
zero_old_rates(
calculate_rates(
lookup_element(Table, {pget(IdProperty, Props), stats}), State)
end.
@ -567,8 +591,8 @@ augment_fine_stats(Dict, State) when element(1, Dict) == dict ->
[[{stats, augment_fine_stats(Stats, State)} |
augment_msg_stats([IdTuple], State)]
|| {IdTuple, Stats} <- dict:to_list(Dict)];
augment_fine_stats(Stats, _State) ->
Stats.
augment_fine_stats(Stats, State) ->
calculate_rates(Stats, State).
consumer_details_fun(PatternFun, State = #state{tables = Tables}) ->
Table = orddict:fetch(consumers, Tables),
@ -580,16 +604,32 @@ consumer_details_fun(PatternFun, State = #state{tables = Tables}) ->
ets:match(Table, {Pattern, '$1'}))]}]
end.
zero_old_rates(Stats, State) -> [maybe_zero_rate(S, State) || S <- Stats].
calculate_rates(Stats, State) -> [calculate_rate(S, State) || S <- Stats].
maybe_zero_rate({Key, Val}, #state{interval = Interval}) ->
calculate_rate({Key, Val}, #state{interval = Interval}) ->
case is_details(Key) of
true -> Age = rabbit_misc:now_ms() - pget(last_event, Val),
{Key, case Age > Interval * 1.5 of
true -> pset(rate, 0, Val);
false -> Val
end};
false -> {Key, Val}
true ->
case length(Val) > 1 of
true ->
[[{sample, S3}, {timestamp, T3}],
[{sample, S2}, {timestamp, T2}] | _] = Val,
{Inst, Avg} =
case rabbit_misc:now_ms() - T3 > Interval * 1.5 of
true -> {0, 0};
false -> [{sample, S1},
{timestamp, T1}] = lists:last(Val),
{(S3 - S2) * 1000 / (T3 - T2),
(S3 - S1) * 1000 / (T3 - T1)}
end,
{Key, [{rate, Inst},
{interval, T3 - T2},
{avg_rate, Avg},
{samples, Val}]};
false ->
{Key, [{samples, Val}]}
end;
false ->
{Key, Val}
end.
is_details(Key) -> lists:suffix("_details", atom_to_list(Key)).

2
deps/rabbitmq_management/test/src/rabbit_mgmt_test_db.erl vendored
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@ -345,7 +345,7 @@ assert_equal(Item, PList1, PList2) ->
assert_rate(Exp, Stats) ->
Interval = pget(interval, Stats),
Rate = pget(rate, Stats),
CorrectedRate = Interval / 5000000 * Rate,
CorrectedRate = Interval / 5000 * Rate,
case abs(Exp - CorrectedRate) < 0.00001 of
true -> ok;
_ -> throw({expected, Exp, got, Rate, corrected, CorrectedRate})