Commit 654cce1e authored by Christopher Dykes's avatar Christopher Dykes Committed by Facebook Github Bot

Refactor stats to use the same type for indexes

Summary:
This refactors folly/stats/* to use a single type for indexes rather than `size_t`, `int`, `unsigned int`, `uint64_t` and `int64_t` depending on where you looked.
This also has the result of getting MSVC to not complain about implicit sign conversions and implicit truncations.

Reviewed By: simpkins

Differential Revision: D4282174

fbshipit-source-id: 8529be34dce8ad18bc64395330bbdf2cd7305be4
parent 16c6735f
......@@ -37,26 +37,25 @@ HistogramBuckets<T, BucketT>::HistogramBuckets(ValueType bucketSize,
// Deliberately make this a signed type, because we're about
// to compare it against max-min, which is nominally signed, too.
int numBuckets = (max - min) / bucketSize;
int64_t numBuckets = int64_t((max - min) / bucketSize);
// Round up if the bucket size does not fit evenly
if (numBuckets * bucketSize < max - min) {
++numBuckets;
}
// Add 2 for the extra 'below min' and 'above max' buckets
numBuckets += 2;
buckets_.assign(numBuckets, defaultBucket);
buckets_.assign(size_t(numBuckets), defaultBucket);
}
template <typename T, typename BucketType>
unsigned int HistogramBuckets<T, BucketType>::getBucketIdx(
ValueType value) const {
size_t HistogramBuckets<T, BucketType>::getBucketIdx(ValueType value) const {
if (value < min_) {
return 0;
} else if (value >= max_) {
return buckets_.size() - 1;
} else {
// the 1 is the below_min bucket
return ((value - min_) / bucketSize_) + 1;
return size_t(((value - min_) / bucketSize_) + 1);
}
}
......@@ -65,7 +64,7 @@ template <typename CountFn>
uint64_t HistogramBuckets<T, BucketType>::computeTotalCount(
CountFn countFromBucket) const {
uint64_t count = 0;
for (unsigned int n = 0; n < buckets_.size(); ++n) {
for (size_t n = 0; n < buckets_.size(); ++n) {
count += countFromBucket(const_cast<const BucketType&>(buckets_[n]));
}
return count;
......@@ -73,19 +72,20 @@ uint64_t HistogramBuckets<T, BucketType>::computeTotalCount(
template <typename T, typename BucketType>
template <typename CountFn>
unsigned int HistogramBuckets<T, BucketType>::getPercentileBucketIdx(
size_t HistogramBuckets<T, BucketType>::getPercentileBucketIdx(
double pct,
CountFn countFromBucket,
double* lowPct, double* highPct) const {
double* lowPct,
double* highPct) const {
CHECK_GE(pct, 0.0);
CHECK_LE(pct, 1.0);
unsigned int numBuckets = buckets_.size();
auto numBuckets = buckets_.size();
// Compute the counts in each bucket
std::vector<uint64_t> counts(numBuckets);
uint64_t totalCount = 0;
for (unsigned int n = 0; n < numBuckets; ++n) {
for (size_t n = 0; n < numBuckets; ++n) {
uint64_t bucketCount =
countFromBucket(const_cast<const BucketType&>(buckets_[n]));
counts[n] = bucketCount;
......@@ -114,7 +114,7 @@ unsigned int HistogramBuckets<T, BucketType>::getPercentileBucketIdx(
double prevPct = 0.0;
double curPct = 0.0;
uint64_t curCount = 0;
unsigned int idx;
size_t idx;
for (idx = 0; idx < numBuckets; ++idx) {
if (counts[idx] == 0) {
// skip empty buckets
......@@ -149,8 +149,8 @@ T HistogramBuckets<T, BucketType>::getPercentileEstimate(
// Find the bucket where this percentile falls
double lowPct;
double highPct;
unsigned int bucketIdx = getPercentileBucketIdx(pct, countFromBucket,
&lowPct, &highPct);
size_t bucketIdx =
getPercentileBucketIdx(pct, countFromBucket, &lowPct, &highPct);
if (lowPct == 0.0 && highPct == 0.0) {
// Invalid range -- the buckets must all be empty
// Return the default value for ValueType.
......@@ -235,12 +235,12 @@ T HistogramBuckets<T, BucketType>::getPercentileEstimate(
// Assume that the data points lower than the median of this bucket
// are uniformly distributed between low and avg
double pctThroughSection = (pct - lowPct) / (medianPct - lowPct);
return low + ((avg - low) * pctThroughSection);
return T(low + ((avg - low) * pctThroughSection));
} else {
// Assume that the data points greater than the median of this bucket
// are uniformly distributed between avg and high
double pctThroughSection = (pct - medianPct) / (highPct - medianPct);
return avg + ((high - avg) * pctThroughSection);
return T(avg + ((high - avg) * pctThroughSection));
}
}
......@@ -254,7 +254,7 @@ std::string Histogram<T>::debugString() const {
", bucketSize: ", buckets_.getBucketSize(),
", min: ", buckets_.getMin(), ", max: ", buckets_.getMax(), "\n");
for (unsigned int i = 0; i < buckets_.getNumBuckets(); ++i) {
for (size_t i = 0; i < buckets_.getNumBuckets(); ++i) {
folly::toAppend(" ", buckets_.getBucketMin(i), ": ",
buckets_.getByIndex(i).count, "\n",
&ret);
......@@ -265,7 +265,7 @@ std::string Histogram<T>::debugString() const {
template <typename T>
void Histogram<T>::toTSV(std::ostream& out, bool skipEmptyBuckets) const {
for (unsigned int i = 0; i < buckets_.getNumBuckets(); ++i) {
for (size_t i = 0; i < buckets_.getNumBuckets(); ++i) {
// Do not output empty buckets in order to reduce data file size.
if (skipEmptyBuckets && getBucketByIndex(i).count == 0) {
continue;
......
......@@ -17,11 +17,12 @@
#pragma once
#include <cstddef>
#include <cstdint>
#include <limits>
#include <ostream>
#include <stdexcept>
#include <string>
#include <vector>
#include <stdexcept>
#include <folly/CPortability.h>
#include <folly/detail/Stats.h>
......@@ -77,12 +78,12 @@ class HistogramBuckets {
* plus 2 extra buckets, one for handling values less than min, and one for
* values greater than max.
*/
unsigned int getNumBuckets() const {
size_t getNumBuckets() const {
return buckets_.size();
}
/* Returns the bucket index into which the given value would fall. */
unsigned int getBucketIdx(ValueType value) const;
size_t getBucketIdx(ValueType value) const;
/* Returns the bucket for the specified value */
BucketType& getByValue(ValueType value) {
......@@ -100,12 +101,12 @@ class HistogramBuckets {
* Note that index 0 is the bucket for all values less than the specified
* minimum. Index 1 is the first bucket in the specified bucket range.
*/
BucketType& getByIndex(unsigned int idx) {
BucketType& getByIndex(size_t idx) {
return buckets_[idx];
}
/* Returns the bucket at the specified index. */
const BucketType& getByIndex(unsigned int idx) const {
const BucketType& getByIndex(size_t idx) const {
return buckets_[idx];
}
......@@ -116,7 +117,7 @@ class HistogramBuckets {
* [bucketMin, bucketMin + bucketSize), or [bucketMin, max), if the overall
* max is smaller than bucketMin + bucketSize.
*/
ValueType getBucketMin(unsigned int idx) const {
ValueType getBucketMin(size_t idx) const {
if (idx == 0) {
return std::numeric_limits<ValueType>::min();
}
......@@ -134,7 +135,7 @@ class HistogramBuckets {
* [bucketMin, bucketMin + bucketSize), or [bucketMin, max), if the overall
* max is smaller than bucketMin + bucketSize.
*/
ValueType getBucketMax(unsigned int idx) const {
ValueType getBucketMax(size_t idx) const {
if (idx == buckets_.size() - 1) {
return std::numeric_limits<ValueType>::max();
}
......@@ -171,7 +172,8 @@ class HistogramBuckets {
* data point.
*/
template <typename CountFn>
unsigned int getPercentileBucketIdx(double pct,
size_t getPercentileBucketIdx(
double pct,
CountFn countFromBucket,
double* lowPct = nullptr,
double* highPct = nullptr) const;
......@@ -302,7 +304,7 @@ class Histogram {
/* Remove all data points from the histogram */
void clear() {
for (unsigned int i = 0; i < buckets_.getNumBuckets(); i++) {
for (size_t i = 0; i < buckets_.getNumBuckets(); i++) {
buckets_.getByIndex(i).clear();
}
}
......@@ -318,7 +320,7 @@ class Histogram {
throw std::invalid_argument("Cannot subtract input histogram.");
}
for (unsigned int i = 0; i < buckets_.getNumBuckets(); i++) {
for (size_t i = 0; i < buckets_.getNumBuckets(); i++) {
buckets_.getByIndex(i) -= hist.buckets_.getByIndex(i);
}
}
......@@ -334,7 +336,7 @@ class Histogram {
throw std::invalid_argument("Cannot merge from input histogram.");
}
for (unsigned int i = 0; i < buckets_.getNumBuckets(); i++) {
for (size_t i = 0; i < buckets_.getNumBuckets(); i++) {
buckets_.getByIndex(i) += hist.buckets_.getByIndex(i);
}
}
......@@ -349,7 +351,7 @@ class Histogram {
throw std::invalid_argument("Cannot copy from input histogram.");
}
for (unsigned int i = 0; i < buckets_.getNumBuckets(); i++) {
for (size_t i = 0; i < buckets_.getNumBuckets(); i++) {
buckets_.getByIndex(i) = hist.buckets_.getByIndex(i);
}
}
......@@ -367,12 +369,12 @@ class Histogram {
return buckets_.getMax();
}
/* Returns the number of buckets */
unsigned int getNumBuckets() const {
size_t getNumBuckets() const {
return buckets_.getNumBuckets();
}
/* Returns the specified bucket (for reading only!) */
const Bucket& getBucketByIndex(int idx) const {
const Bucket& getBucketByIndex(size_t idx) const {
return buckets_.getByIndex(idx);
}
......@@ -383,7 +385,7 @@ class Histogram {
* [bucketMin, bucketMin + bucketSize), or [bucketMin, max), if the overall
* max is smaller than bucketMin + bucketSize.
*/
ValueType getBucketMin(unsigned int idx) const {
ValueType getBucketMin(size_t idx) const {
return buckets_.getBucketMin(idx);
}
......@@ -394,7 +396,7 @@ class Histogram {
* [bucketMin, bucketMin + bucketSize), or [bucketMin, max), if the overall
* max is smaller than bucketMin + bucketSize.
*/
ValueType getBucketMax(unsigned int idx) const {
ValueType getBucketMax(size_t idx) const {
return buckets_.getBucketMax(idx);
}
......@@ -414,7 +416,8 @@ class Histogram {
* The lowest and highest percentile data points in returned bucket will be
* returned in the lowPct and highPct arguments, if they are non-NULL.
*/
unsigned int getPercentileBucketIdx(double pct,
size_t getPercentileBucketIdx(
double pct,
double* lowPct = nullptr,
double* highPct = nullptr) const {
// We unfortunately can't use lambdas here yet;
......
......@@ -46,8 +46,7 @@ template class TimeseriesHistogram<int64_t>;
// are implemented using template methods. Instantiate the default versions of
// these methods too, so anyone using them won't also need to explicitly
// include Histogram-defs.h
template unsigned int detail::HistogramBuckets<
int64_t, Histogram<int64_t>::Bucket>::
template size_t detail::HistogramBuckets<int64_t, Histogram<int64_t>::Bucket>::
getPercentileBucketIdx<Histogram<int64_t>::CountFromBucket>(
double pct,
Histogram<int64_t>::CountFromBucket countFromBucket,
......
......@@ -74,7 +74,7 @@ template <typename VT, typename CT>
void MultiLevelTimeSeries<VT, CT>::addValue(
TimePoint now,
const ValueType& val,
int64_t times) {
uint64_t times) {
addValueAggregated(now, val * times, times);
}
......@@ -82,7 +82,7 @@ template <typename VT, typename CT>
void MultiLevelTimeSeries<VT, CT>::addValueAggregated(
TimePoint now,
const ValueType& total,
int64_t nsamples) {
uint64_t nsamples) {
if (cachedTime_ != now) {
flush();
cachedTime_ = now;
......
......@@ -98,9 +98,8 @@ class MultiLevelTimeSeries {
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
const Level& getLevel(int level) const {
CHECK(level >= 0);
CHECK_LT(size_t(level), levels_.size());
const Level& getLevel(size_t level) const {
CHECK_LT(level, levels_.size());
return levels_[level];
}
......@@ -158,7 +157,7 @@ class MultiLevelTimeSeries {
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
ValueType sum(int level) const {
ValueType sum(size_t level) const {
return getLevel(level).sum();
}
......@@ -173,8 +172,8 @@ class MultiLevelTimeSeries {
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
template <typename ReturnType=double>
ReturnType avg(int level) const {
template <typename ReturnType = double>
ReturnType avg(size_t level) const {
return getLevel(level).template avg<ReturnType>();
}
......@@ -187,7 +186,7 @@ class MultiLevelTimeSeries {
* not been called recently.
*/
template <typename ReturnType = double, typename Interval = Duration>
ReturnType rate(int level) const {
ReturnType rate(size_t level) const {
return getLevel(level).template rate<ReturnType, Interval>();
}
......@@ -198,7 +197,7 @@ class MultiLevelTimeSeries {
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
int64_t count(int level) const {
uint64_t count(size_t level) const {
return getLevel(level).count();
}
......@@ -210,14 +209,14 @@ class MultiLevelTimeSeries {
* not been called recently.
*/
template <typename ReturnType = double, typename Interval = Duration>
ReturnType countRate(int level) const {
ReturnType countRate(size_t level) const {
return getLevel(level).template countRate<ReturnType, Interval>();
}
/*
* Return the sum of all the data points currently tracked at this level.
*
* This method is identical to sum(int level) above but takes in the
* This method is identical to sum(size_t level) above but takes in the
* duration that the user is interested in querying as the parameter.
*
* Note: you should generally call update() or flush() before accessing the
......@@ -232,7 +231,7 @@ class MultiLevelTimeSeries {
* Return the average (sum / count) of all the data points currently tracked
* at this level.
*
* This method is identical to avg(int level) above but takes in the
* This method is identical to avg(size_t level) above but takes in the
* duration that the user is interested in querying as the parameter.
*
* Note: you should generally call update() or flush() before accessing the
......@@ -248,7 +247,7 @@ class MultiLevelTimeSeries {
* Return the rate (sum divided by elaspsed time) of the all data points
* currently tracked at this level.
*
* This method is identical to rate(int level) above but takes in the
* This method is identical to rate(size_t level) above but takes in the
* duration that the user is interested in querying as the parameter.
*
* Note: you should generally call update() or flush() before accessing the
......@@ -263,21 +262,21 @@ class MultiLevelTimeSeries {
/*
* Return the number of data points currently tracked at this level.
*
* This method is identical to count(int level) above but takes in the
* This method is identical to count(size_t level) above but takes in the
* duration that the user is interested in querying as the parameter.
*
* Note: you should generally call update() or flush() before accessing the
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
int64_t count(Duration duration) const {
uint64_t count(Duration duration) const {
return getLevelByDuration(duration).count();
}
/*
* Return the count divided by the elapsed time tracked at this level.
*
* This method is identical to countRate(int level) above but takes in the
* This method is identical to countRate(size_t level) above but takes in the
* duration that the user is interested in querying as the parameter.
*
* Note: you should generally call update() or flush() before accessing the
......@@ -352,7 +351,7 @@ class MultiLevelTimeSeries {
* data. Otherwise you may be reading stale data if update() or flush() has
* not been called recently.
*/
int64_t count(TimePoint start, TimePoint end) const {
uint64_t count(TimePoint start, TimePoint end) const {
return getLevel(start).count(start, end);
}
......@@ -374,14 +373,14 @@ class MultiLevelTimeSeries {
/*
* Adds the value 'val' at time 'now' to all levels.
*/
void addValue(TimePoint now, const ValueType& val, int64_t times);
void addValue(TimePoint now, const ValueType& val, uint64_t times);
/*
* Adds the value 'total' at time 'now' to all levels as the sum of
* 'nsamples' samples.
*/
void
addValueAggregated(TimePoint now, const ValueType& total, int64_t nsamples);
addValueAggregated(TimePoint now, const ValueType& total, uint64_t nsamples);
/*
* Update all the levels to the specified time, doing all the necessary
......@@ -417,11 +416,11 @@ class MultiLevelTimeSeries {
void addValue(Duration now, const ValueType& value) {
addValue(TimePoint(now), value);
}
void addValue(Duration now, const ValueType& value, int64_t times) {
void addValue(Duration now, const ValueType& value, uint64_t times) {
addValue(TimePoint(now), value, times);
}
void
addValueAggregated(Duration now, const ValueType& total, int64_t nsamples) {
addValueAggregated(Duration now, const ValueType& total, uint64_t nsamples) {
addValueAggregated(TimePoint(now), total, nsamples);
}
......
......@@ -45,7 +45,7 @@ template <typename T, typename CT, typename C>
void TimeseriesHistogram<T, CT, C>::addValue(
TimePoint now,
const ValueType& value,
int64_t times) {
uint64_t times) {
buckets_.getByValue(value).addValue(now, value, times);
maybeHandleSingleUniqueValue(value);
}
......@@ -59,7 +59,7 @@ void TimeseriesHistogram<T, CT, C>::addValues(
CHECK_EQ(hist.getBucketSize(), getBucketSize());
CHECK_EQ(hist.getNumBuckets(), getNumBuckets());
for (unsigned int n = 0; n < hist.getNumBuckets(); ++n) {
for (size_t n = 0; n < hist.getNumBuckets(); ++n) {
const typename folly::Histogram<ValueType>::Bucket& histBucket =
hist.getBucketByIndex(n);
Bucket& myBucket = buckets_.getByIndex(n);
......@@ -86,7 +86,7 @@ void TimeseriesHistogram<T, CT, C>::maybeHandleSingleUniqueValue(
}
template <typename T, typename CT, typename C>
T TimeseriesHistogram<T, CT, C>::getPercentileEstimate(double pct, int level)
T TimeseriesHistogram<T, CT, C>::getPercentileEstimate(double pct, size_t level)
const {
if (singleUniqueValue_) {
return firstValue_;
......@@ -111,13 +111,14 @@ T TimeseriesHistogram<T, CT, C>::getPercentileEstimate(
}
template <typename T, typename CT, typename C>
int TimeseriesHistogram<T, CT, C>::getPercentileBucketIdx(double pct, int level)
const {
size_t TimeseriesHistogram<T, CT, C>::getPercentileBucketIdx(
double pct,
size_t level) const {
return buckets_.getPercentileBucketIdx(pct / 100.0, CountFromLevel(level));
}
template <typename T, typename CT, typename C>
int TimeseriesHistogram<T, CT, C>::getPercentileBucketIdx(
size_t TimeseriesHistogram<T, CT, C>::getPercentileBucketIdx(
double pct,
TimePoint start,
TimePoint end) const {
......@@ -140,7 +141,7 @@ void TimeseriesHistogram<T, CT, C>::update(TimePoint now) {
}
template <typename T, typename CT, typename C>
std::string TimeseriesHistogram<T, CT, C>::getString(int level) const {
std::string TimeseriesHistogram<T, CT, C>::getString(size_t level) const {
std::string result;
for (size_t i = 0; i < buckets_.getNumBuckets(); i++) {
......@@ -178,9 +179,9 @@ std::string TimeseriesHistogram<T, CT, C>::getString(
template <class T, class CT, class C>
void TimeseriesHistogram<T, CT, C>::computeAvgData(
ValueType* total,
int64_t* nsamples,
int level) const {
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
uint64_t* nsamples,
size_t level) const {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
const auto& levelObj = buckets_.getByIndex(b).getLevel(level);
*total += levelObj.sum();
*nsamples += levelObj.count();
......@@ -190,10 +191,10 @@ void TimeseriesHistogram<T, CT, C>::computeAvgData(
template <class T, class CT, class C>
void TimeseriesHistogram<T, CT, C>::computeAvgData(
ValueType* total,
int64_t* nsamples,
uint64_t* nsamples,
TimePoint start,
TimePoint end) const {
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
const auto& levelObj = buckets_.getByIndex(b).getLevel(start);
*total += levelObj.sum(start, end);
*nsamples += levelObj.count(start, end);
......@@ -204,8 +205,8 @@ template <typename T, typename CT, typename C>
void TimeseriesHistogram<T, CT, C>::computeRateData(
ValueType* total,
Duration* elapsed,
int level) const {
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
size_t level) const {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
const auto& levelObj = buckets_.getByIndex(b).getLevel(level);
*total += levelObj.sum();
*elapsed = std::max(*elapsed, levelObj.elapsed());
......@@ -218,7 +219,7 @@ void TimeseriesHistogram<T, CT, C>::computeRateData(
Duration* elapsed,
TimePoint start,
TimePoint end) const {
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
const auto& level = buckets_.getByIndex(b).getLevel(start);
*total += level.sum(start, end);
*elapsed = std::max(*elapsed, level.elapsed(start, end));
......
......@@ -93,40 +93,42 @@ class TimeseriesHistogram {
ValueType getMax() const { return buckets_.getMax(); }
/* Return the number of levels of the Timeseries object in each bucket */
int getNumLevels() const {
size_t getNumLevels() const {
return buckets_.getByIndex(0).numLevels();
}
/* Return the number of buckets */
int getNumBuckets() const { return buckets_.getNumBuckets(); }
size_t getNumBuckets() const {
return buckets_.getNumBuckets();
}
/*
* Return the threshold of the bucket for the given index in range
* [0..numBuckets). The bucket will have range [thresh, thresh + bucketSize)
* or [thresh, max), whichever is shorter.
*/
ValueType getBucketMin(int bucketIdx) const {
ValueType getBucketMin(size_t bucketIdx) const {
return buckets_.getBucketMin(bucketIdx);
}
/* Return the actual timeseries in the given bucket (for reading only!) */
const ContainerType& getBucket(int bucketIdx) const {
const ContainerType& getBucket(size_t bucketIdx) const {
return buckets_.getByIndex(bucketIdx);
}
/* Total count of values at the given timeseries level (all buckets). */
int64_t count(int level) const {
int64_t total = 0;
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
uint64_t count(size_t level) const {
uint64_t total = 0;
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
total += buckets_.getByIndex(b).count(level);
}
return total;
}
/* Total count of values added during the given interval (all buckets). */
int64_t count(TimePoint start, TimePoint end) const {
int64_t total = 0;
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
uint64_t count(TimePoint start, TimePoint end) const {
uint64_t total = 0;
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
total += buckets_.getByIndex(b).count(start, end);
}
return total;
......@@ -135,7 +137,7 @@ class TimeseriesHistogram {
/* Total sum of values at the given timeseries level (all buckets). */
ValueType sum(int level) const {
ValueType total = ValueType();
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
total += buckets_.getByIndex(b).sum(level);
}
return total;
......@@ -144,7 +146,7 @@ class TimeseriesHistogram {
/* Total sum of values added during the given interval (all buckets). */
ValueType sum(TimePoint start, TimePoint end) const {
ValueType total = ValueType();
for (unsigned int b = 0; b < buckets_.getNumBuckets(); ++b) {
for (size_t b = 0; b < buckets_.getNumBuckets(); ++b) {
total += buckets_.getByIndex(b).sum(start, end);
}
return total;
......@@ -154,7 +156,7 @@ class TimeseriesHistogram {
template <typename ReturnType = double>
ReturnType avg(int level) const {
auto total = ValueType();
int64_t nsamples = 0;
uint64_t nsamples = 0;
computeAvgData(&total, &nsamples, level);
return folly::detail::avgHelper<ReturnType>(total, nsamples);
}
......@@ -163,7 +165,7 @@ class TimeseriesHistogram {
template <typename ReturnType = double>
ReturnType avg(TimePoint start, TimePoint end) const {
auto total = ValueType();
int64_t nsamples = 0;
uint64_t nsamples = 0;
computeAvgData(&total, &nsamples, start, end);
return folly::detail::avgHelper<ReturnType>(total, nsamples);
}
......@@ -173,7 +175,7 @@ class TimeseriesHistogram {
* This is the sum of all values divided by the time interval (in seconds).
*/
template <typename ReturnType = double>
ReturnType rate(int level) const {
ReturnType rate(size_t level) const {
auto total = ValueType();
Duration elapsed(0);
computeRateData(&total, &elapsed, level);
......@@ -207,7 +209,7 @@ class TimeseriesHistogram {
/* Add a value into the histogram with timestamp 'now' */
void addValue(TimePoint now, const ValueType& value);
/* Add a value the given number of times with timestamp 'now' */
void addValue(TimePoint now, const ValueType& value, int64_t times);
void addValue(TimePoint now, const ValueType& value, uint64_t times);
/*
* Add all of the values from the specified histogram.
......@@ -241,11 +243,11 @@ class TimeseriesHistogram {
* average and the known bound is equal to the distance between the average
* and the unknown bound.
*/
ValueType getPercentileEstimate(double pct, int level) const;
ValueType getPercentileEstimate(double pct, size_t level) const;
/*
* Return an estimate of the value at the given percentile in the histogram
* in the given historical interval. Please see the documentation for
* getPercentileEstimate(int pct, int level) for the explanation of the
* getPercentileEstimate(double pct, size_t level) for the explanation of the
* estimation algorithm.
*/
ValueType getPercentileEstimate(double pct, TimePoint start, TimePoint end)
......@@ -256,20 +258,22 @@ class TimeseriesHistogram {
* given timeseries level). This index can then be used to retrieve either
* the bucket threshold, or other data from inside the bucket.
*/
int getPercentileBucketIdx(double pct, int level) const;
size_t getPercentileBucketIdx(double pct, size_t level) const;
/*
* Return the bucket index that the given percentile falls into (in the
* given historical interval). This index can then be used to retrieve either
* the bucket threshold, or other data from inside the bucket.
*/
int getPercentileBucketIdx(double pct, TimePoint start, TimePoint end) const;
size_t getPercentileBucketIdx(double pct, TimePoint start, TimePoint end)
const;
/* Get the bucket threshold for the bucket containing the given pct. */
int getPercentileBucketMin(double pct, int level) const {
ValueType getPercentileBucketMin(double pct, size_t level) const {
return getBucketMin(getPercentileBucketIdx(pct, level));
}
/* Get the bucket threshold for the bucket containing the given pct. */
int getPercentileBucketMin(double pct, TimePoint start, TimePoint end) const {
ValueType getPercentileBucketMin(double pct, TimePoint start, TimePoint end)
const {
return getBucketMin(getPercentileBucketIdx(pct, start, end));
}
......@@ -278,11 +282,11 @@ class TimeseriesHistogram {
* Format is: BUCKET [',' BUCKET ...]
* Where: BUCKET == bucketMin ':' count ':' avg
*/
std::string getString(int level) const;
std::string getString(size_t level) const;
/*
* Print out serialized data for all buckets in the historical interval.
* For format, please see getString(int level).
* For format, please see getString(size_t level).
*/
std::string getString(TimePoint start, TimePoint end) const;
......@@ -299,7 +303,7 @@ class TimeseriesHistogram {
void addValue(Duration now, const ValueType& value) {
addValue(TimePoint(now), value);
}
void addValue(Duration now, const ValueType& value, int64_t times) {
void addValue(Duration now, const ValueType& value, uint64_t times) {
addValue(TimePoint(now), value, times);
}
void addValues(Duration now, const folly::Histogram<ValueType>& values) {
......@@ -309,14 +313,14 @@ class TimeseriesHistogram {
private:
typedef ContainerType Bucket;
struct CountFromLevel {
explicit CountFromLevel(int level) : level_(level) {}
explicit CountFromLevel(size_t level) : level_(level) {}
uint64_t operator()(const ContainerType& bucket) const {
return bucket.count(level_);
}
private:
int level_;
size_t level_;
};
struct CountFromInterval {
explicit CountFromInterval(TimePoint start, TimePoint end)
......@@ -332,14 +336,14 @@ class TimeseriesHistogram {
};
struct AvgFromLevel {
explicit AvgFromLevel(int level) : level_(level) {}
explicit AvgFromLevel(size_t level) : level_(level) {}
ValueType operator()(const ContainerType& bucket) const {
return bucket.template avg<ValueType>(level_);
}
private:
int level_;
size_t level_;
};
template <typename ReturnType>
......@@ -364,13 +368,13 @@ class TimeseriesHistogram {
*/
void maybeHandleSingleUniqueValue(const ValueType& value);
void computeAvgData(ValueType* total, int64_t* nsamples, int level) const;
void computeAvgData(ValueType* total, uint64_t* nsamples, size_t level) const;
void computeAvgData(
ValueType* total,
int64_t* nsamples,
uint64_t* nsamples,
TimePoint start,
TimePoint end) const;
void computeRateData(ValueType* total, Duration* elapsed, int level) const;
void computeRateData(ValueType* total, Duration* elapsed, size_t level) const;
void computeRateData(
ValueType* total,
Duration* elapsed,
......
......@@ -77,7 +77,7 @@ TEST(TimeseriesHistogram, Percentile) {
EXPECT_EQ(10, h.getMin());
EXPECT_EQ(110, h.getMax());
for (int i = 0; i < h.getNumBuckets(); ++i) {
for (size_t i = 0; i < h.getNumBuckets(); ++i) {
EXPECT_EQ(4, h.getBucket(i).numLevels());
}
......@@ -133,7 +133,7 @@ TEST(TimeseriesHistogram, String) {
CHECK_EQ(IntMTMHTS::NUM_LEVELS, hist.getNumLevels());
for (int level = 0; level < hist.getNumLevels(); ++level) {
for (size_t level = 0; level < hist.getNumLevels(); ++level) {
EXPECT_EQ(kStringValues1[level], hist.getString(level));
}
......@@ -150,7 +150,7 @@ TEST(TimeseriesHistogram, String) {
CHECK_EQ(IntMTMHTS::NUM_LEVELS, hist.getNumLevels());
for (int level = 0; level < hist.getNumLevels(); ++level) {
for (size_t level = 0; level < hist.getNumLevels(); ++level) {
EXPECT_EQ(kStringValues2[level], hist.getString(level));
}
}
......@@ -172,7 +172,7 @@ TEST(TimeseriesHistogram, Clear) {
// check clearing
hist.clear();
for (int b = 0; b < hist.getNumBuckets(); ++b) {
for (size_t b = 0; b < hist.getNumBuckets(); ++b) {
EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::MINUTE));
EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
EXPECT_EQ(0, hist.getBucket(b).count(IntMTMHTS::HOUR));
......@@ -217,7 +217,7 @@ TEST(TimeseriesHistogram, Basic) {
EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
}
for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
for (size_t b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
EXPECT_EQ(600, hist.getBucket(b).count(IntMTMHTS::MINUTE));
EXPECT_EQ(6000, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::HOUR));
......@@ -296,7 +296,7 @@ TEST(TimeseriesHistogram, Basic) {
EXPECT_EQ(expected, hist.getPercentileBucketMin(pct, IntMTMHTS::ALLTIME));
}
for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
for (size_t b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
EXPECT_EQ(600 * 2, hist.getBucket(b).count(IntMTMHTS::MINUTE));
EXPECT_EQ(6000 * 2, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
EXPECT_EQ(36000 * 2, hist.getBucket(b).count(IntMTMHTS::HOUR));
......@@ -346,7 +346,7 @@ TEST(TimeseriesHistogram, Basic) {
hist.getBucket(hist.getNumBuckets() - 1).count(
IntMTMHTS::ALLTIME));
for (int b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
for (size_t b = 1; (b + 1) < hist.getNumBuckets(); ++b) {
EXPECT_EQ(600, hist.getBucket(b).count(IntMTMHTS::MINUTE));
EXPECT_EQ(6000, hist.getBucket(b).count(IntMTMHTS::TEN_MINUTE));
EXPECT_EQ(36000, hist.getBucket(b).count(IntMTMHTS::HOUR));
......
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