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/*
* include/haproxy/freq_ctr.h
* This file contains macros and inline functions for frequency counters.
*
* Copyright (C) 2000-2020 Willy Tarreau - w@1wt.eu
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation, version 2.1
* exclusively.
*
* This library is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*/
#ifndef _HAPROXY_FREQ_CTR_H
#define _HAPROXY_FREQ_CTR_H
#include <haproxy/api.h>
#include <haproxy/freq_ctr-t.h>
#include <haproxy/intops.h>
#include <haproxy/ticks.h>
#include <haproxy/time.h>
/* exported functions from freq_ctr.c */
ullong freq_ctr_total(const struct freq_ctr *ctr, uint period, int pend);
/* Update a frequency counter by <inc> incremental units. It is automatically
* rotated if the period is over. It is important that it correctly initializes
* a null area. This one works on frequency counters which have a period
* different from one second.
*/
static inline unsigned int update_freq_ctr_period(struct freq_ctr *ctr,
unsigned int period, unsigned int inc)
{
unsigned int curr_tick;
uint32_t now_ms_tmp;
/* atomically update the counter if still within the period, even if
* a rotation is in progress (no big deal).
*/
for (;; __ha_cpu_relax()) {
__ha_barrier_load();
now_ms_tmp = global_now_ms;
curr_tick = ctr->curr_tick;
if (now_ms_tmp - curr_tick < period)
return _HA_ATOMIC_ADD_FETCH(&ctr->curr_ctr, inc);
/* a rotation is needed */
if (!(curr_tick & 1) &&
HA_ATOMIC_CAS(&ctr->curr_tick, &curr_tick, curr_tick | 0x1))
break;
}
/* atomically switch the new period into the old one without losing any
* potential concurrent update.
*/
_HA_ATOMIC_STORE(&ctr->prev_ctr, _HA_ATOMIC_FETCH_SUB(&ctr->curr_ctr, ctr->curr_ctr - inc));
curr_tick += period;
if (likely(now_ms_tmp - curr_tick >= period)) {
/* we missed at least two periods */
_HA_ATOMIC_STORE(&ctr->prev_ctr, 0);
curr_tick = now_ms_tmp;
}
/* release the lock and update the time in case of rotate. */
_HA_ATOMIC_STORE(&ctr->curr_tick, curr_tick & ~1);
return ctr->curr_ctr;
}
/* Update a 1-sec frequency counter by <inc> incremental units. It is automatically
* rotated if the period is over. It is important that it correctly initializes
* a null area.
*/
static inline unsigned int update_freq_ctr(struct freq_ctr *ctr, unsigned int inc)
{
return update_freq_ctr_period(ctr, MS_TO_TICKS(1000), inc);
}
/* Reads a frequency counter taking history into account for missing time in
* current period. The period has to be passed in number of ticks and must
* match the one used to feed the counter. The counter value is reported for
* current global date. The return value has the same precision as one input
* data sample, so low rates over the period will be inaccurate but still
* appropriate for max checking. One trick we use for low values is to specially
* handle the case where the rate is between 0 and 1 in order to avoid flapping
* while waiting for the next event.
*
* For immediate limit checking, it's recommended to use freq_ctr_period_remain()
* instead which does not have the flapping correction, so that even frequencies
* as low as one event/period are properly handled.
*/
static inline uint read_freq_ctr_period(struct freq_ctr *ctr, uint period)
{
ullong total = freq_ctr_total(ctr, period, -1);
return div64_32(total, period);
}
/* same as read_freq_ctr_period() above except that floats are used for the
* output so that low rates can be more precise.
*/
static inline double read_freq_ctr_period_flt(struct freq_ctr *ctr, uint period)
{
ullong total = freq_ctr_total(ctr, period, -1);
return (double)total / (double)period;
}
/* Read a 1-sec frequency counter taking history into account for missing time
* in current period.
*/
static inline unsigned int read_freq_ctr(struct freq_ctr *ctr)
{
return read_freq_ctr_period(ctr, MS_TO_TICKS(1000));
}
/* same as read_freq_ctr() above except that floats are used for the
* output so that low rates can be more precise.
*/
static inline double read_freq_ctr_flt(struct freq_ctr *ctr)
{
return read_freq_ctr_period_flt(ctr, MS_TO_TICKS(1000));
}
/* Returns the number of remaining events that can occur on this freq counter
* while respecting <freq> events per period, and taking into account that
* <pend> events are already known to be pending. Returns 0 if limit was reached.
*/
static inline uint freq_ctr_remain_period(struct freq_ctr *ctr, uint period, uint freq, uint pend)
{
ullong total = freq_ctr_total(ctr, period, pend);
uint avg = div64_32(total, period);
if (avg > freq)
avg = freq;
return freq - avg;
}
/* returns the number of remaining events that can occur on this freq counter
* while respecting <freq> and taking into account that <pend> events are
* already known to be pending. Returns 0 if limit was reached.
*/
static inline unsigned int freq_ctr_remain(struct freq_ctr *ctr, unsigned int freq, unsigned int pend)
{
return freq_ctr_remain_period(ctr, MS_TO_TICKS(1000), freq, pend);
}
/* return the expected wait time in ms before the next event may occur,
* respecting frequency <freq>, and assuming there may already be some pending
* events. It returns zero if we can proceed immediately, otherwise the wait
* time, which will be rounded down 1ms for better accuracy, with a minimum
* of one ms.
*/
static inline uint next_event_delay_period(struct freq_ctr *ctr, uint period, uint freq, uint pend)
{
ullong total = freq_ctr_total(ctr, period, pend);
ullong limit = (ullong)freq * period;
uint wait;
if (total < limit)
return 0;
/* too many events already, let's count how long to wait before they're
* processed. For this we'll subtract from the number of pending events
* the ones programmed for the current period, to know how long to wait
* for the next period. Each event takes period/freq ticks.
*/
total -= limit;
wait = div64_32(total, (freq ? freq : 1));
return MAX(wait, 1);
}
/* Returns the expected wait time in ms before the next event may occur,
* respecting frequency <freq> over 1 second, and assuming there may already be
* some pending events. It returns zero if we can proceed immediately, otherwise
* the wait time, which will be rounded down 1ms for better accuracy, with a
* minimum of one ms.
*/
static inline unsigned int next_event_delay(struct freq_ctr *ctr, unsigned int freq, unsigned int pend)
{
return next_event_delay_period(ctr, MS_TO_TICKS(1000), freq, pend);
}
/* While the functions above report average event counts per period, we are
* also interested in average values per event. For this we use a different
* method. The principle is to rely on a long tail which sums the new value
* with a fraction of the previous value, resulting in a sliding window of
* infinite length depending on the precision we're interested in.
*
* The idea is that we always keep (N-1)/N of the sum and add the new sampled
* value. The sum over N values can be computed with a simple program for a
* constant value 1 at each iteration :
*
* N
* ,---
* \ N - 1 e - 1
* > ( --------- )^x ~= N * -----
* / N e
* '---
* x = 1
*
* Note: I'm not sure how to demonstrate this but at least this is easily
* verified with a simple program, the sum equals N * 0.632120 for any N
* moderately large (tens to hundreds).
*
* Inserting a constant sample value V here simply results in :
*
* sum = V * N * (e - 1) / e
*
* But we don't want to integrate over a small period, but infinitely. Let's
* cut the infinity in P periods of N values. Each period M is exactly the same
* as period M-1 with a factor of ((N-1)/N)^N applied. A test shows that given a
* large N :
*
* N - 1 1
* ( ------- )^N ~= ---
* N e
*
* Our sum is now a sum of each factor times :
*
* N*P P
* ,--- ,---
* \ N - 1 e - 1 \ 1
* > v ( --------- )^x ~= VN * ----- * > ---
* / N e / e^x
* '--- '---
* x = 1 x = 0
*
* For P "large enough", in tests we get this :
*
* P
* ,---
* \ 1 e
* > --- ~= -----
* / e^x e - 1
* '---
* x = 0
*
* This simplifies the sum above :
*
* N*P
* ,---
* \ N - 1
* > v ( --------- )^x = VN
* / N
* '---
* x = 1
*
* So basically by summing values and applying the last result an (N-1)/N factor
* we just get N times the values over the long term, so we can recover the
* constant value V by dividing by N. In order to limit the impact of integer
* overflows, we'll use this equivalence which saves us one multiply :
*
* N - 1 1 x0
* x1 = x0 * ------- = x0 * ( 1 - --- ) = x0 - ----
* N N N
*
* And given that x0 is discrete here we'll have to saturate the values before
* performing the divide, so the value insertion will become :
*
* x0 + N - 1
* x1 = x0 - ------------
* N
*
* A value added at the entry of the sliding window of N values will thus be
* reduced to 1/e or 36.7% after N terms have been added. After a second batch,
* it will only be 1/e^2, or 13.5%, and so on. So practically speaking, each
* old period of N values represents only a quickly fading ratio of the global
* sum :
*
* period ratio
* 1 36.7%
* 2 13.5%
* 3 4.98%
* 4 1.83%
* 5 0.67%
* 6 0.25%
* 7 0.09%
* 8 0.033%
* 9 0.012%
* 10 0.0045%
*
* So after 10N samples, the initial value has already faded out by a factor of
* 22026, which is quite fast. If the sliding window is 1024 samples wide, it
* means that a sample will only count for 1/22k of its initial value after 10k
* samples went after it, which results in half of the value it would represent
* using an arithmetic mean. The benefit of this method is that it's very cheap
* in terms of computations when N is a power of two. This is very well suited
* to record response times as large values will fade out faster than with an
* arithmetic mean and will depend on sample count and not time.
*
* Demonstrating all the above assumptions with maths instead of a program is
* left as an exercise for the reader.
*/
/* Adds sample value <v> to sliding window sum <sum> configured for <n> samples.
* The sample is returned. Better if <n> is a power of two. This function is
* thread-safe.
*/
static inline unsigned int swrate_add(unsigned int *sum, unsigned int n, unsigned int v)
{
unsigned int new_sum, old_sum;
old_sum = *sum;
do {
new_sum = old_sum - (old_sum + n - 1) / n + v;
} while (!_HA_ATOMIC_CAS(sum, &old_sum, new_sum) && __ha_cpu_relax());
return new_sum;
}
/* Adds sample value <v> to sliding window sum <sum> configured for <n> samples.
* The sample is returned. Better if <n> is a power of two. This function is
* thread-safe.
* This function should give better accuracy than swrate_add when number of
* samples collected is lower than nominal window size. In such circumstances
* <n> should be set to 0.
*/
static inline unsigned int swrate_add_dynamic(unsigned int *sum, unsigned int n, unsigned int v)
{
unsigned int new_sum, old_sum;
old_sum = *sum;
do {
new_sum = old_sum - (n ? (old_sum + n - 1) / n : 0) + v;
} while (!_HA_ATOMIC_CAS(sum, &old_sum, new_sum) && __ha_cpu_relax());
return new_sum;
}
/* Adds sample value <v> spanning <s> samples to sliding window sum <sum>
* configured for <n> samples, where <n> is supposed to be "much larger" than
* <s>. The sample is returned. Better if <n> is a power of two. Note that this
* is only an approximate. Indeed, as can be seen with two samples only over a
* 8-sample window, the original function would return :
* sum1 = sum - (sum + 7) / 8 + v
* sum2 = sum1 - (sum1 + 7) / 8 + v
* = (sum - (sum + 7) / 8 + v) - (sum - (sum + 7) / 8 + v + 7) / 8 + v
* ~= 7sum/8 - 7/8 + v - sum/8 + sum/64 - 7/64 - v/8 - 7/8 + v
* ~= (3sum/4 + sum/64) - (7/4 + 7/64) + 15v/8
*
* while the function below would return :
* sum = sum + 2*v - (sum + 8) * 2 / 8
* = 3sum/4 + 2v - 2
*
* this presents an error of ~ (sum/64 + 9/64 + v/8) = (sum+n+1)/(n^s) + v/n
*
* Thus the simplified function effectively replaces a part of the history with
* a linear sum instead of applying the exponential one. But as long as s/n is
* "small enough", the error fades away and remains small for both small and
* large values of n and s (typically < 0.2% measured). This function is
* thread-safe.
*/
static inline unsigned int swrate_add_scaled(unsigned int *sum, unsigned int n, unsigned int v, unsigned int s)
{
unsigned int new_sum, old_sum;
old_sum = *sum;
do {
new_sum = old_sum + v * s - div64_32((unsigned long long)(old_sum + n) * s, n);
} while (!_HA_ATOMIC_CAS(sum, &old_sum, new_sum) && __ha_cpu_relax());
return new_sum;
}
/* Returns the average sample value for the sum <sum> over a sliding window of
* <n> samples. Better if <n> is a power of two. It must be the same <n> as the
* one used above in all additions.
*/
static inline unsigned int swrate_avg(unsigned int sum, unsigned int n)
{
return (sum + n - 1) / n;
}
#endif /* _HAPROXY_FREQ_CTR_H */
/*
* Local variables:
* c-indent-level: 8
* c-basic-offset: 8
* End:
*/