foundationdb/flow/TDMetric.actor.h

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/*
* TDMetric.actor.h
*
* This source file is part of the FoundationDB open source project
*
* Copyright 2013-2018 Apple Inc. and the FoundationDB project authors
*
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* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
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* http://www.apache.org/licenses/LICENSE-2.0
*
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* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
// When actually compiled (NO_INTELLISENSE), include the generated version of this file. In intellisense use the source version.
#if defined(NO_INTELLISENSE) && !defined(FLOW_TDMETRIC_ACTOR_G_H)
#define FLOW_TDMETRIC_ACTOR_G_H
#include "flow/TDMetric.actor.g.h"
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#elif !defined(FLOW_TDMETRIC_ACTOR_H)
#define FLOW_TDMETRIC_ACTOR_H
#include "flow/flow.h"
#include "flow/IndexedSet.h"
#include "flow/network.h"
#include "flow/Knobs.h"
#include "flow/genericactors.actor.h"
#include "flow/CompressedInt.h"
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#include <algorithm>
#include <functional>
#include <cmath>
#include "flow/actorcompiler.h" // This must be the last #include.
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struct MetricNameRef {
MetricNameRef() {}
MetricNameRef(const StringRef& type, const StringRef& name, const StringRef &id)
: type(type), name(name), id(id) {
}
MetricNameRef(Arena& a, const MetricNameRef& copyFrom)
: type(a, copyFrom.type), name(a, copyFrom.name), id(a, copyFrom.id) {
}
StringRef type, name, id;
std::string toString() const {
return format("(%s,%s,%s,%s)", type.toString().c_str(), name.toString().c_str(), id.toString().c_str());
}
int expectedSize() const {
return type.expectedSize() + name.expectedSize();
}
};
extern std::string reduceFilename(std::string const &filename);
inline bool operator < (const MetricNameRef& l, const MetricNameRef& r ) {
int cmp = l.type.compare(r.type);
if(cmp == 0) {
cmp = l.name.compare(r.name);
if(cmp == 0)
cmp = l.id.compare(r.id);
}
return cmp < 0;
}
inline bool operator == (const MetricNameRef& l, const MetricNameRef& r ) {
return l.type == r.type && l.name == r.name && l.id == r.id;
}
inline bool operator != (const MetricNameRef& l, const MetricNameRef& r ) {
return !(l == r);
}
struct KeyWithWriter {
Standalone<StringRef> key;
BinaryWriter writer;
int writerOffset;
KeyWithWriter( Standalone<StringRef> const& key, BinaryWriter& writer, int writerOffset = 0) : key(key), writer(std::move(writer)), writerOffset(writerOffset) {}
KeyWithWriter( KeyWithWriter&& r ) : key(std::move(r.key)), writer(std::move(r.writer)), writerOffset(r.writerOffset) {}
void operator=( KeyWithWriter&& r ) { key = std::move(r.key); writer = std::move(r.writer); writerOffset = r.writerOffset; }
StringRef value() {
return StringRef(writer.toStringRef().substr(writerOffset));
}
};
// This is a very minimal interface for getting metric data from the DB which is needed
// to support continuing existing metric data series.
// It's lack of generality is intentional.
class IMetricDB {
public:
virtual ~IMetricDB() {}
// key should be the result of calling metricKey or metricFieldKey with time = 0
virtual Future<Optional<Standalone<StringRef>>> getLastBlock(Standalone<StringRef> key) = 0;
};
// Key generator for metric keys for various things.
struct MetricKeyRef {
MetricKeyRef() : level(-1) {}
MetricKeyRef(Arena& a, const MetricKeyRef& copyFrom)
: prefix(a, copyFrom.prefix), name(a, copyFrom.name), address(a, copyFrom.address),
fieldName(a, copyFrom.fieldName), fieldType(a, copyFrom.fieldType), level(copyFrom.level) {
}
StringRef prefix;
MetricNameRef name;
StringRef address;
StringRef fieldName;
StringRef fieldType;
uint64_t level;
int expectedSize() const {
return prefix.expectedSize() + name.expectedSize() + address.expectedSize() + fieldName.expectedSize() + fieldType.expectedSize();
}
template <typename T> inline MetricKeyRef withField(const T &field) const {
MetricKeyRef mk(*this);
mk.fieldName = field.name();
mk.fieldType = field.typeName();
return mk;
}
const Standalone<StringRef> packLatestKey() const;
const Standalone<StringRef> packDataKey(int64_t time = -1) const;
const Standalone<StringRef> packFieldRegKey() const;
bool isField() const { return fieldName.size() > 0 && fieldType.size() > 0; }
void writeField(BinaryWriter &wr) const;
void writeMetricName(BinaryWriter &wr) const;
};
struct MetricUpdateBatch {
std::vector<KeyWithWriter> inserts;
std::vector<KeyWithWriter> appends;
std::vector<std::pair<Standalone<StringRef>,Standalone<StringRef>>> updates;
std::vector<std::function<Future<Void>(IMetricDB *, MetricUpdateBatch *)>> callbacks;
void clear() {
inserts.clear();
appends.clear();
updates.clear();
callbacks.clear();
}
};
template<typename T>
inline const StringRef metricTypeName() {
// If this function does not compile then T is not a supported metric type
return T::metric_field_type();
}
#define MAKE_TYPENAME(T, S) template<> inline const StringRef metricTypeName<T>() { return LiteralStringRef(S); }
MAKE_TYPENAME(bool, "Bool")
MAKE_TYPENAME(int64_t, "Int64")
MAKE_TYPENAME(double, "Double")
MAKE_TYPENAME(Standalone<StringRef>, "String")
#undef MAKE_TYPENAME
struct BaseMetric;
// The collection of metrics that exist for a single process, at a single address.
class TDMetricCollection {
public:
TDMetricCollection() : currentTimeBytes(0) {}
// Metric Name to reference to its instance
Map<Standalone<MetricNameRef>, Reference<BaseMetric>, MapPair<Standalone<MetricNameRef>, Reference<BaseMetric>>, int> metricMap;
AsyncTrigger metricAdded;
AsyncTrigger metricEnabled;
AsyncTrigger metricRegistrationChanged;
// Initialize the collection. Once this returns true, metric data can be written to a database. Note that metric data can be logged
// before that time, just not written to a database.
bool init() {
// Get and store the local address in the metric collection, but only if it is not 0.0.0.0:0
if( address.size() == 0 ) {
NetworkAddress addr = g_network->getLocalAddress();
if (addr.ip.isValid() && addr.port != 0) address = StringRef(addr.toString());
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}
return address.size() != 0;
}
// Returns the TDMetrics that the calling process should use
static TDMetricCollection* getTDMetrics() {
if(g_network == nullptr)
return nullptr;
return static_cast<TDMetricCollection*>((void*) g_network->global(INetwork::enTDMetrics));
}
Deque<uint64_t> rollTimes;
int64_t currentTimeBytes;
Standalone<StringRef> address;
void checkRoll(uint64_t t, int64_t usedBytes);
bool canLog(int level);
};
struct MetricData {
uint64_t start;
uint64_t rollTime;
uint64_t appendStart;
BinaryWriter writer;
explicit MetricData(uint64_t appendStart = 0) :
writer(AssumeVersion(currentProtocolVersion)),
start(0),
rollTime(std::numeric_limits<uint64_t>::max()),
appendStart(appendStart) {
}
MetricData( MetricData&& r ) noexcept(true) :
start(r.start),
rollTime(r.rollTime),
appendStart(r.appendStart),
writer(std::move(r.writer)) {
}
void operator=( MetricData&& r ) noexcept(true) {
start = r.start; rollTime = r.rollTime; appendStart = r.appendStart; writer = std::move(r.writer);
}
std::string toString();
};
// Some common methods to reduce code redundancy across different metric definitions
template<typename T, typename _ValueType = Void>
struct MetricUtil {
typedef _ValueType ValueType;
typedef T MetricType;
// Looks up a metric by name and id and returns a reference to it if it exists.
// Empty names will not be looked up.
// If create is true then a metric will be created with the given initial value if one could not be found to return.
// If a metric is created and name is not empty then the metric will be placed in the collection.
static Reference<T> getOrCreateInstance(StringRef const& name, StringRef const &id = StringRef(), bool create = false, ValueType initial = ValueType()) {
Reference<T> m;
TDMetricCollection *collection = TDMetricCollection::getTDMetrics();
// If there is a metric collect and this metric has a name then look it up in the collection
bool useMap = collection != nullptr && name.size() > 0;
MetricNameRef mname;
if(useMap) {
mname = MetricNameRef(T::metricType, name, id);
auto mi = collection->metricMap.find(mname);
if(mi != collection->metricMap.end()) {
m = mi->value.castTo<T>();
}
}
// If we don't have a valid metric reference yet and the create flag was set then create one and possibly put it in the map
if(!m && create) {
// Metric not found in collection but create is set then create it in the map
m = Reference<T>(new T(mname, initial));
if(useMap) {
collection->metricMap[mname] = m.template castTo<BaseMetric>();
collection->metricAdded.trigger();
}
}
return m;
}
// Lookup the T metric by name and return its value (or nullptr if it doesn't exist)
static T * lookupMetric(MetricNameRef const &name) {
auto it = T::metricMap().find(name);
if(it != T::metricMap().end())
return it->value;
return nullptr;
}
};
// index_sequence implementation since VS2013 doesn't have it yet
template <size_t... Ints> class index_sequence {
public:
static size_t size() { return sizeof...(Ints); }
};
template <size_t Start, typename Indices, size_t End>
struct make_index_sequence_impl;
template <size_t Start, size_t... Indices, size_t End>
struct make_index_sequence_impl<Start, index_sequence<Indices...>, End> {
typedef typename make_index_sequence_impl<
Start + 1, index_sequence<Indices..., Start>, End>::type type;
};
template <size_t End, size_t... Indices>
struct make_index_sequence_impl<End, index_sequence<Indices...>, End> {
typedef index_sequence<Indices...> type;
};
// The code that actually implements tuple_map
template <size_t I, typename F, typename... Tuples>
auto tuple_zip_invoke(F f, const Tuples &... ts) -> decltype( f(std::get<I>(ts)...) ) {
return f(std::get<I>(ts)...);
}
template <typename F, size_t... Is, typename... Tuples>
auto tuple_map_impl(F f, index_sequence<Is...>, const Tuples &... ts) -> decltype( std::make_tuple(tuple_zip_invoke<Is>(f, ts...)...) ) {
return std::make_tuple(tuple_zip_invoke<Is>(f, ts...)...);
}
// tuple_map( f(a,b), (a1,a2,a3), (b1,b2,b3) ) = (f(a1,b1), f(a2,b2), f(a3,b3))
template <typename F, typename Tuple, typename... Tuples>
auto tuple_map(F f, const Tuple &t, const Tuples &... ts) -> decltype( tuple_map_impl(f, typename make_index_sequence_impl<0, index_sequence<>, std::tuple_size<Tuple>::value>::type(), t, ts...) ) {
return tuple_map_impl(f, typename make_index_sequence_impl<0, index_sequence<>, std::tuple_size<Tuple>::value>::type(), t, ts...);
}
template <class T>
struct Descriptor {
#ifndef NO_INTELLISENSE
using fields = std::tuple<>;
typedef make_index_sequence_impl<0, index_sequence<>, std::tuple_size<fields>::value>::type field_indexes;
static StringRef typeName() {{ return LiteralStringRef(""); }}
#endif
};
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// FieldHeader is a serializable (FIXED SIZE!) and updatable Header type for Metric field levels.
// Update is via += with either a T or another FieldHeader
// Default implementation is sufficient for ints and doubles
template<typename T>
struct FieldHeader {
FieldHeader() : version(1), count(0), sum(0) {}
uint8_t version;
int64_t count;
// sum is a T if T is arithmetic, otherwise it's an int64_t
typename std::conditional<std::is_floating_point<T>::value, double, int64_t>::type sum;
void update(FieldHeader const &h) {
count += h.count;
sum += h.sum;
}
void update(T const &v) {
++count;
sum += v;
}
template<class Ar> void serialize(Ar &ar) {
serializer(ar, version);
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ASSERT(version == 1);
serializer(ar, count, sum);
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}
};
template <> inline void FieldHeader<Standalone<StringRef>>::update(Standalone<StringRef> const &v) {
++count;
sum += v.size();
}
// FieldValueBlockEncoding is a class for reading and writing encoded field values to and from field
// value data blocks. Note that an implementation can be stateful.
// Proper usage requires that a single Encoding instance is used to either write all field values to a metric
// data block or to read all field values from a metric value block. This usage pattern enables enables
// encoding and decoding values as deltas from previous values.
//
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// The default implementation works for ints and writes delta from the previous value.
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template <typename T>
struct FieldValueBlockEncoding {
FieldValueBlockEncoding() : prev(0) {}
inline void write(BinaryWriter &w, T v) {
w << CompressedInt<T>(v - prev);
prev = v;
}
T read(BinaryReader &r) {
CompressedInt<T> v;
r >> v;
prev += v.value;
return prev;
}
T prev;
};
template <>
struct FieldValueBlockEncoding<double> {
inline void write(BinaryWriter &w, double v) {
w << v;
}
double read(BinaryReader &r) {
double v;
r >> v;
return v;
}
};
template <>
struct FieldValueBlockEncoding<bool> {
inline void write(BinaryWriter &w, bool v) {
w.serializeBytes( v ? LiteralStringRef("\x01") : LiteralStringRef("\x00") );
}
bool read(BinaryReader &r) {
uint8_t *v = (uint8_t *)r.readBytes(sizeof(uint8_t));
return *v != 0;
}
};
// Encoder for strings, writes deltas
template <>
struct FieldValueBlockEncoding<Standalone<StringRef>> {
inline void write(BinaryWriter &w, Standalone<StringRef> const &v) {
int reuse = 0;
int stop = std::min(v.size(), prev.size());
while(reuse < stop && v[reuse] == prev[reuse])
++reuse;
w << CompressedInt<int>(reuse) << CompressedInt<int>(v.size() - reuse);
if(v.size() > reuse)
w.serializeBytes(v.substr(reuse));
prev = v;
}
Standalone<StringRef> read(BinaryReader &r) {
CompressedInt<int> reuse;
CompressedInt<int> extra;
r >> reuse >> extra;
ASSERT(reuse.value >= 0 && extra.value >= 0 && reuse.value <= prev.size());
Standalone<StringRef> v = makeString(reuse.value + extra.value);
memcpy(mutateString(v), prev.begin(), reuse.value);
memcpy(mutateString(v) + reuse.value, r.readBytes(extra.value), extra.value);
prev = v;
return v;
}
// Using a Standalone<StringRef> for prev is efficient for writing but not great for reading.
Standalone<StringRef> prev;
};
// Field level for value type of T using header type of Header. Default header type is the default FieldHeader implementation for type T.
template <class T, class Header = FieldHeader<T>, class Encoder = FieldValueBlockEncoding<T>>
struct FieldLevel {
Deque<MetricData> metrics;
int64_t appendUsed;
Header header;
// The previous header and the last timestamp at which an out going MetricData block requires header patching
Optional<Header> previousHeader;
uint64_t lastTimeRequiringHeaderPatch;
Encoder enc;
explicit FieldLevel() : appendUsed(0) {
metrics.emplace_back(MetricData());
metrics.back().writer << header;
}
FieldLevel(FieldLevel &&f)
: metrics(std::move(f.metrics)), appendUsed(f.appendUsed), enc(f.enc), header(f.header),
previousHeader(f.previousHeader), lastTimeRequiringHeaderPatch(f.lastTimeRequiringHeaderPatch) {
}
// update Header, use Encoder to write T v
void log( T v, uint64_t t, bool& overflow, int64_t& bytes ) {
int lastLength = metrics.back().writer.getLength();
if( metrics.back().start == 0 )
metrics.back().start = t;
header.update(v);
enc.write(metrics.back().writer, v);
bytes += metrics.back().writer.getLength() - lastLength;
if(lastLength + appendUsed > FLOW_KNOBS->MAX_METRIC_SIZE)
overflow = true;
}
void nextKey( uint64_t t ) {
// If nothing has actually been written to the current block, don't add a new block,
// just modify this one if needed so that the next log call will set the ts for this block.
auto &m = metrics.back();
if(m.start == 0 && m.appendStart == 0)
return;
// This block would have appended but had no data so just reset it to a non-append block instead of adding a new one
if(m.appendStart != 0 && m.writer.getLength() == 0) {
m.appendStart = 0;
m.writer << header;
enc = Encoder();
return;
}
metrics.back().rollTime = t;
metrics.emplace_back(MetricData());
metrics.back().writer << header;
enc = Encoder();
appendUsed = 0;
}
void rollMetric( uint64_t t ) {
ASSERT(metrics.size());
if(metrics.back().start) {
metrics.back().rollTime = t;
appendUsed += metrics.back().writer.getLength();
if(metrics.back().appendStart)
metrics.emplace_back(MetricData(metrics.back().appendStart));
else
metrics.emplace_back(MetricData(metrics.back().start));
}
}
// Calculate header as of the end of a value block
static Header calculateHeader(StringRef block) {
BinaryReader r(block, AssumeVersion(currentProtocolVersion));
Header h;
r >> h;
Encoder dec;
while(!r.empty()) {
T v = dec.read(r);
h.update(v);
}
return h;
}
// Read header at position, update it with previousHeader, overwrite old header with new header.
static void updateSerializedHeader(StringRef buf, const Header &patch) {
BinaryReader r(buf, AssumeVersion(currentProtocolVersion));
Header h;
r >> h;
h.update(patch);
OverWriter w(mutateString(buf), buf.size(), AssumeVersion(currentProtocolVersion));
w << h;
}
// Flushes data blocks in metrics to batch, optionally patching headers if a header is given
void flushUpdates(MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
while(metrics.size()) {
auto& data = metrics.front();
if(data.start != 0 && data.rollTime <= rollTime) {
// If this data is to be appended, write it to the batch now.
if( data.appendStart ) {
batch.appends.push_back(KeyWithWriter(mk.packDataKey(data.appendStart), data.writer));
} else {
// Otherwise, insert but first, patch the header if this block is old enough
if(data.rollTime <= lastTimeRequiringHeaderPatch) {
ASSERT(previousHeader.present());
FieldLevel<T>::updateSerializedHeader(data.writer.toStringRef(), previousHeader.get());
}
batch.inserts.push_back(KeyWithWriter(mk.packDataKey(data.start), data.writer));
}
if(metrics.size() == 1) {
rollMetric(data.rollTime);
metrics.pop_front();
break;
}
metrics.pop_front();
}
else
break;
}
}
ACTOR static Future<Void> updatePreviousHeader(FieldLevel *self, IMetricDB *db, Standalone<MetricKeyRef> mk, uint64_t rollTime, MetricUpdateBatch *batch) {
Optional<Standalone<StringRef>> block = wait(db->getLastBlock(mk.packDataKey(-1)));
// If the block is present, use it
if(block.present()) {
// Calculate the previous data's final header value
Header oldHeader = calculateHeader(block.get());
// Set the previous header in self to this header for us in patching outgoing blocks
self->previousHeader = oldHeader;
// Update the header in self so the next new block created will be current
self->header.update(oldHeader);
// Any blocks already in the metrics queue will need to be patched at the time that they are
// flushed to the DB (which isn't necessarity part of the current flush) so set the last time
// that requires a patch to the time of the last MetricData in the queue
self->lastTimeRequiringHeaderPatch = self->metrics.back().rollTime;
}
else {
// Otherwise, there is no previous header so no headers need to be updated at all ever.
// Set the previous header to an empty header so that flush() sees that this process
// has already finished, and set lastTimeRequiringHeaderPatch to 0 since no blocks ever need to be patched.
self->previousHeader = Header();
self->lastTimeRequiringHeaderPatch = 0;
}
// Now flush the level data up to the rollTime argument and patch anything older than lastTimeRequiringHeaderPatch
self->flushUpdates(mk, rollTime, *batch);
return Void();
}
// Flush this level's data to the output batch.
// This function must NOT be called again until any callbacks added to batch have been completed.
void flush(const MetricKeyRef &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
// Don't do anything if there is no data in the queue to flush.
if(metrics.empty() || metrics.front().start == 0)
return;
// If the previous header is present then just call flushUpdates now.
if(previousHeader.present())
return flushUpdates(mk, rollTime, batch);
Standalone<MetricKeyRef> mkCopy = mk;
// Previous header is not present so queue a callback which will update it
batch.callbacks.push_back([=](IMetricDB *db, MetricUpdateBatch *batch) mutable -> Future<Void> {
return updatePreviousHeader(this, db, mkCopy, rollTime, batch);
});
}
};
// A field Description to be used for continuous metrics, whose field name and type should never be accessed
struct NullDescriptor {
static StringRef name() { return StringRef(); }
};
// Descriptor must have the methods name() and typeName(). They can be either static or member functions (such as for runtime configurability).
// Descriptor is inherited so that syntatically Descriptor::fn() works in either case and so that an empty Descriptor with static methods
// will take up 0 space. EventField() accepts an optional Descriptor instance.
template <class T, class Descriptor = NullDescriptor, class FieldLevelType = FieldLevel<T>>
struct EventField : public Descriptor {
std::vector<FieldLevelType> levels;
EventField( EventField&& r ) noexcept(true) : Descriptor(r), levels(std::move(r.levels)) {}
void operator=( EventField&& r ) noexcept(true) {
levels = std::move(r.levels);
}
EventField(Descriptor d = Descriptor()) : Descriptor(d) {
}
static StringRef typeName() { return metricTypeName<T>(); }
void init() {
if(levels.size() != FLOW_KNOBS->MAX_METRIC_LEVEL) {
levels.clear();
levels.resize(FLOW_KNOBS->MAX_METRIC_LEVEL);
}
}
void log( T v, uint64_t t, int64_t l, bool& overflow, int64_t& bytes ) {
return levels[l].log(v, t, overflow, bytes);
}
void nextKey( uint64_t t, int level ) {
levels[level].nextKey(t);
}
void nextKeyAllLevels( uint64_t t ) {
for(int64_t i = 0; i < FLOW_KNOBS->MAX_METRIC_LEVEL; i++)
nextKey(t, i);
}
void rollMetric( uint64_t t ) {
for(int i = 0; i < levels.size(); i++) {
levels[i].rollMetric(t);
}
}
void flushField(MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
MetricKeyRef fk = mk.withField(*this);
for(int j = 0; j < levels.size(); ++j) {
fk.level = j;
levels[j].flush(fk, rollTime, batch);
}
}
// Writes and Event metric field registration key
void registerField( const MetricKeyRef &mk, std::vector<Standalone<StringRef>>& fieldKeys ) {
fieldKeys.push_back(mk.withField(*this).packFieldRegKey());
}
};
struct MakeEventField {
template <class Descriptor>
EventField<typename Descriptor::type, Descriptor> operator() (Descriptor) { return EventField<typename Descriptor::type, Descriptor>(); }
};
struct TimeDescriptor {
static StringRef name() { return LiteralStringRef("Time"); }
};
struct BaseMetric {
BaseMetric(MetricNameRef const &name) : metricName(name), pCollection(nullptr), registered(false), enabled(false) {
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setConfig(false);
}
virtual ~BaseMetric() {
}
virtual void addref() = 0;
virtual void delref() = 0;
virtual void rollMetric(uint64_t t) = 0;
virtual void flushData(const MetricKeyRef &mk, uint64_t rollTime, MetricUpdateBatch &batch) = 0;
virtual void registerFields(const MetricKeyRef &mk, std::vector<Standalone<StringRef>>& fieldKeys) {};
// Set the metric's config. An assert will fail if the metric is enabled before the metrics collection is available.
void setConfig(bool enable, int minLogLevel = 0) {
bool wasEnabled = enabled;
enabled = enable;
minLevel = minLogLevel;
if(enable && pCollection == nullptr) {
pCollection = TDMetricCollection::getTDMetrics();
ASSERT(pCollection != nullptr);
}
if(wasEnabled != enable) {
if(enabled) {
onEnable();
pCollection->metricEnabled.trigger();
}
else
onDisable();
}
}
// Callbacks for when metric is Enabled or Disabled.
// Metrics should verify their underlying storage on Enable because they could have been initially created
// at a time when the knobs were not initialized.
virtual void onEnable() = 0;
virtual void onDisable() {};
// Combines checking this metric's configured minimum level and any collection-wide throttling
// This should only be called after it is determined that a metric is enabled.
bool canLog(int level) {
return level >= minLevel && pCollection->canLog(level);
}
Standalone<MetricNameRef> metricName;
bool enabled; // The metric is currently logging data
int minLevel; // The minimum level that will be logged.
// All metrics need a pointer to their collection for performance reasons - every time a data point is logged
// canLog must be called which uses the collection's canLog to decide based on the metric write queue.
TDMetricCollection *pCollection;
// The metric has been registered in its current form (some metrics can change and require re-reg)
bool registered;
};
struct BaseEventMetric : BaseMetric {
BaseEventMetric(MetricNameRef const &name) : BaseMetric(name) {
}
// Needed for MetricUtil
static const StringRef metricType;
Void getValue() const {
return Void();
}
virtual ~BaseEventMetric() {}
// Every metric should have a set method for its underlying type in order for MetricUtil::getOrCreateInstance
// to initialize it. In the case of event metrics there is no underlying type so the underlying type
// is Void and set does nothing.
void set(Void const &val) {}
virtual StringRef getTypeName() = 0;
};
template <class E>
struct EventMetric : E, ReferenceCounted<EventMetric<E>>, MetricUtil<EventMetric<E>>, BaseEventMetric {
EventField<int64_t, TimeDescriptor> time;
bool latestRecorded;
decltype( tuple_map( MakeEventField(), typename Descriptor<E>::fields() ) ) values;
virtual void addref() { ReferenceCounted<EventMetric<E>>::addref(); }
virtual void delref() { ReferenceCounted<EventMetric<E>>::delref(); }
EventMetric( MetricNameRef const &name, Void) : BaseEventMetric(name), latestRecorded(false) {
}
virtual ~EventMetric() {
}
virtual StringRef getTypeName() { return Descriptor<E>::typeName(); }
void onEnable() {
// Must initialize fields, previously knobs may not have been set.
time.init();
initFields( typename Descriptor<E>::field_indexes());
}
// Log the event.
// Returns the time that was logged for the event so that it can be passed to other events that need to be time-sync'd.
// NOTE: Do NOT use the same time for two consecutive loggings of the SAME event. This *could* cause there to be metric data
// blocks such that the last timestamp of one block is equal to the first timestamp of the next, which means if a search is done
// for the exact timestamp then the first event will not be found.
uint64_t log(uint64_t explicitTime = 0) {
if(!enabled)
return 0;
uint64_t t = explicitTime ? explicitTime : timer_int();
double x = g_random->random01();
int64_t l = 0;
if (x == 0.0)
l = FLOW_KNOBS->MAX_METRIC_LEVEL-1;
else
l = std::min(FLOW_KNOBS->MAX_METRIC_LEVEL-1, (int64_t)(::log(1.0/x) / FLOW_KNOBS->METRIC_LEVEL_DIVISOR));
if(!canLog(l))
return 0;
bool overflow = false;
int64_t bytes = 0;
time.log(t, t, l, overflow, bytes);
logFields( typename Descriptor<E>::field_indexes(), t, l, overflow, bytes );
if(overflow) {
time.nextKey(t, l);
nextKeys(typename Descriptor<E>::field_indexes(), t, l);
}
latestRecorded = false;
return t;
}
template <size_t... Is>
void logFields(index_sequence<Is...>, uint64_t t, int64_t l, bool& overflow, int64_t& bytes) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).log( std::tuple_element<Is, typename Descriptor<E>::fields>::type::get( static_cast<E&>(*this) ), t, l, overflow, bytes ), Void())...
};
#endif
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}
template <size_t... Is>
void initFields(index_sequence<Is...>) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).init(), Void())...
};
#endif
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}
template <size_t... Is>
void nextKeys(index_sequence<Is...>, uint64_t t, int64_t l ) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).nextKey(t, l),Void())...
};
#endif
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}
virtual void flushData(MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
time.flushField( mk, rollTime, batch );
flushFields( typename Descriptor<E>::field_indexes(), mk, rollTime, batch );
if(!latestRecorded) {
batch.updates.push_back(std::make_pair(mk.packLatestKey(), StringRef()));
latestRecorded = true;
}
}
template <size_t... Is>
void flushFields(index_sequence<Is...>, MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch ) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).flushField( mk, rollTime, batch ),Void())...
};
#endif
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}
virtual void rollMetric( uint64_t t ) {
time.rollMetric(t);
rollFields( typename Descriptor<E>::field_indexes(), t );
}
template <size_t... Is>
void rollFields(index_sequence<Is...>, uint64_t t ) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).rollMetric( t ),Void())...
};
#endif
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}
virtual void registerFields( MetricKeyRef const &mk, std::vector<Standalone<StringRef>>& fieldKeys ) {
time.registerField( mk, fieldKeys );
registerFields( typename Descriptor<E>::field_indexes(), mk, fieldKeys );
}
template <size_t... Is>
void registerFields(index_sequence<Is...>, const MetricKeyRef &mk, std::vector<Standalone<StringRef>>& fieldKeys ) {
#ifdef NO_INTELLISENSE
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auto _ = {
(std::get<Is>(values).registerField( mk, fieldKeys ),Void())...
};
#endif
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}
protected:
bool it;
};
// A field Descriptor compatible with EventField but with name set at runtime
struct DynamicDescriptor {
DynamicDescriptor(const char *name)
: _name(StringRef((uint8_t *)name, strlen(name))) {}
StringRef name() const { return _name; }
private:
const Standalone<StringRef> _name;
};
template<typename T>
struct DynamicField;
struct DynamicFieldBase {
virtual ~DynamicFieldBase() {}
virtual StringRef fieldName() = 0;
virtual const StringRef getDerivedTypeName() = 0;
virtual void init() = 0;
virtual void clear() = 0;
virtual void log(uint64_t t, int64_t l, bool& overflow, int64_t& bytes ) = 0;
virtual void nextKey( uint64_t t, int level ) = 0;
virtual void nextKeyAllLevels( uint64_t t) = 0;
virtual void rollMetric( uint64_t t ) = 0;
virtual void flushField( MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch) = 0;
virtual void registerField( MetricKeyRef const &mk, std::vector<Standalone<StringRef>>& fieldKeys ) = 0;
// Set the current value of this field from the value of another
virtual void setValueFrom(DynamicFieldBase *src, StringRef eventType) = 0;
// Create a new field of the same type and with the same current value as this one and with the given name
virtual DynamicFieldBase * createNewWithValue(const char *name) = 0;
// This does a fairly cheap and "safe" downcast without using dynamic_cast / RTTI by checking that the pointer value
// of the const char * type string is the same as getDerivedTypeName for this object.
template<typename T> DynamicField<T> * safe_downcast(StringRef eventType) {
if(getDerivedTypeName() == metricTypeName<T>())
return (DynamicField<T> *)this;
TraceEvent(SevWarnAlways, "ScopeEventFieldTypeMismatch")
.detail("EventType", eventType.toString())
.detail("FieldName", fieldName().toString())
.detail("OldType", getDerivedTypeName().toString())
.detail("NewType", metricTypeName<T>().toString());
return NULL;
}
};
template<typename T>
struct DynamicField : public DynamicFieldBase, EventField<T, DynamicDescriptor> {
typedef EventField<T, DynamicDescriptor> EventFieldType;
DynamicField(const char *name) : DynamicFieldBase(), EventFieldType(DynamicDescriptor(name)), value(T()) {}
virtual ~DynamicField() {}
StringRef fieldName() { return EventFieldType::name(); }
// Get the field's datatype, this is used as a form of RTTI by DynamicFieldBase::safe_downcast()
const StringRef getDerivedTypeName() { return metricTypeName<T>(); }
// Pure virtual implementations
void clear() { value = T(); }
void log(uint64_t t, int64_t l, bool& overflow, int64_t& bytes) {
return EventFieldType::log(value, t, l, overflow, bytes);
}
// Redirects to EventFieldType methods
void nextKey( uint64_t t, int level ) {
return EventFieldType::nextKey(t, level);
}
void nextKeyAllLevels( uint64_t t) {
return EventFieldType::nextKeyAllLevels(t);
}
void rollMetric( uint64_t t ) {
return EventFieldType::rollMetric(t);
}
void flushField(MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
return EventFieldType::flushField(mk, rollTime, batch);
}
void registerField(MetricKeyRef const &mk, std::vector<Standalone<StringRef>>& fieldKeys) {
return EventFieldType::registerField(mk, fieldKeys);
}
void init() {
return EventFieldType::init();
}
// Set this field's value to the value of another field of exactly the same type.
void setValueFrom(DynamicFieldBase *src, StringRef eventType) {
DynamicField<T> *s = src->safe_downcast<T>(eventType);
if(s != NULL)
set(s->value);
else
clear(); // Not really necessary with proper use but just in case it is better to clear than use an old value.
}
DynamicFieldBase * createNewWithValue(const char *name) {
DynamicField<T> *n = new DynamicField<T>(name);
n->set(value);
return n;
}
// Non virtuals
void set(T val) { value = val; }
private:
T value;
};
// A DynamicEventMetric is an EventMetric whose field set can be modified at runtime.
struct DynamicEventMetric : ReferenceCounted<DynamicEventMetric>, MetricUtil<DynamicEventMetric>, BaseEventMetric {
private:
EventField<int64_t, TimeDescriptor> time;
bool latestRecorded;
// TODO: A Standalone key type isn't ideal because on lookups a ref will be made Standalone just for the search
// All fields that are set with setField will be in fields.
std::map<Standalone<StringRef>, DynamicFieldBase *> fields;
// Set of fields not yet registered
std::set<Standalone<StringRef> > fieldsToRegister;
// Whether or not new fields have been added since the last logging. fieldsToRegister can't
// be used for this because registration is independent of actually logging data.
bool newFields;
void newFieldAdded(Standalone<StringRef> const &fname) {
fieldsToRegister.insert(fname); // So that this field will be registered when asked by the metrics logger actor later
newFields = true; // So that log() will know that there is a new field
// Registration has now changed so set registered to false and trigger a reg change event if possible
registered = false;
if(pCollection != nullptr)
pCollection->metricRegistrationChanged.trigger();
}
public:
DynamicEventMetric(MetricNameRef const &name, Void = Void());
~DynamicEventMetric();
virtual void addref() { ReferenceCounted<DynamicEventMetric>::addref(); }
virtual void delref() { ReferenceCounted<DynamicEventMetric>::delref(); }
void onEnable() {
// Must initialize fields, previously knobs may not have been set.
// Note that future fields will be okay because the field constructor will init and the knobs will be set.
time.init();
for(auto f : fields)
f.second->init();
}
// Set (or create) a new field in the event
template<typename ValueType>
void setField(const char *fieldName, const ValueType &value) {
StringRef fname((uint8_t *)fieldName, strlen(fieldName));
DynamicFieldBase *&p = fields[fname];
if (p != NULL) {
// FIXME: This will break for DynamicEventMetric instances that are reused, such as use cases outside
// of TraceEvents. Currently there are none in the code, and there may never any be but if you're here
// because you reused a DynamicEventMetric and got the error below then this issue must be fixed. One
// possible solution is to have a flag in DynamicEventMetric which enables this check so that
// TraceEvent can preserve this behavior.
TraceEvent(SevError, "DuplicateTraceProperty").detail("Property", fieldName).backtrace();
if (g_network->isSimulated()) ASSERT(false);
}
p = new DynamicField<ValueType>(fieldName);
if(pCollection != nullptr)
p->init();
newFieldAdded(fname);
// This will return NULL if the datatype is wrong.
DynamicField<ValueType> *f = p->safe_downcast<ValueType>(getTypeName());
// Only set the field value if the type is correct.
// Another option here is to redefine the field to the new type and flush (roll) the existing field but that would create many keys
// with small values in the db if two frequent events keep tug-of-war'ing the types back and forth.
if(f != NULL)
f->set(value);
else
p->clear(); // Not really necessary with proper use but just in case it is better to clear than use an old value.
}
// This provides a way to first set fields in a temporary DynamicEventMetric and then push all of those field values
// into another DynamicEventMetric (which is actually logging somewhere) and log the event.
uint64_t setFieldsAndLogFrom(DynamicEventMetric *source, uint64_t explicitTime = 0) {
for(auto f : source->fields)
{
DynamicFieldBase *&p = fields[f.first];
if(p == NULL) {
p = f.second->createNewWithValue(f.first.toString().c_str());
if(pCollection != nullptr)
p->init();
newFieldAdded(f.first);
}
else
p->setValueFrom(f.second, getTypeName());
}
return log(explicitTime);
}
StringRef getTypeName() { return metricName.name; }
// Set all of the fields to their default values.
void clearFields() {
for(auto f : fields)
f.second->clear();
}
uint64_t log(uint64_t explicitTime = 0);
// Virtual function implementations
void flushData(MetricKeyRef const &mk, uint64_t rollTime, MetricUpdateBatch &batch);
void rollMetric( uint64_t t );
void registerFields(MetricKeyRef const &mk, std::vector<Standalone<StringRef>>& fieldKeys);
};
// Continuous metrics are a single-field metric using an EventField<TimeAndValue<T>>
template <typename T>
struct TimeAndValue {
TimeAndValue() : time(0), value() {}
int64_t time;
T value;
// The metric field type for TimeAndValue is just the Value type.
static inline const StringRef metric_field_type() { return metricTypeName<T>(); }
};
// FieldHeader for continuous metrics, works for T = int, double, bool
template <typename T>
struct FieldHeader<TimeAndValue<T>> {
FieldHeader() : version(1), count(0), area(0), previous_time(0) {}
uint8_t version;
int64_t count;
// If T is a floating point type then area is a double, otherwise it's an int64_t
typename std::conditional<std::is_floating_point<T>::value, double, int64_t>::type area;
int64_t previous_time;
void update(FieldHeader const &h) {
count += h.count;
area += h.area;
}
void update(TimeAndValue<T> const &v) {
++count;
if(previous_time > 0)
area += v.value * (v.time - previous_time);
previous_time = v.time;
}
template<class Ar> void serialize(Ar &ar) {
serializer(ar, version);
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ASSERT(version == 1);
serializer(ar, count, area);
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}
};
template <> inline void FieldHeader<TimeAndValue<Standalone<StringRef>>>::update(TimeAndValue<Standalone<StringRef>> const &v) {
++count;
area += v.value.size();
}
// ValueBlock encoder/decoder for continuous metrics which have a type of TimeAndValue<T>
// Uses encodings for int64_t and T and encodes (time, value, [time, value]...)
template <typename T>
struct FieldValueBlockEncoding<TimeAndValue<T>> {
FieldValueBlockEncoding() : time_encoding(), value_encoding() {}
inline void write(BinaryWriter &w, TimeAndValue<T> const &v) {
time_encoding.write(w, v.time);
value_encoding.write(w, v.value);
}
TimeAndValue<T> read(BinaryReader &r) {
TimeAndValue<T> result;
result.time = time_encoding.read(r);
result.value = value_encoding.read(r);
return result;
}
FieldValueBlockEncoding<int64_t> time_encoding;
FieldValueBlockEncoding<T> value_encoding;
};
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// ValueBlock encoder/decoder specialization for continuous bool metrics because they are encoded
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// more efficiently than encoding the time and bool types separately.
// Instead, time and value are combined to a single value (time delta << 1) + (value ? 1 : 0) and then
// that value is encoded as a delta.
template <>
struct FieldValueBlockEncoding<TimeAndValue<bool>> {
FieldValueBlockEncoding() : prev(), prev_combined(0) {}
inline void write(BinaryWriter &w, TimeAndValue<bool> const &v) {
int64_t combined = (v.time << 1) | (v.value ? 1 : 0);
w << CompressedInt<int64_t>(combined - prev_combined);
prev = v;
prev_combined = combined;
}
TimeAndValue<bool> read(BinaryReader &r) {
CompressedInt<int64_t> d;
r >> d;
prev_combined += d.value;
prev.value = prev_combined & 1;
prev.time = prev_combined << 1;
return prev;
}
TimeAndValue<bool> prev;
int64_t prev_combined;
};
template <typename T>
struct ContinuousMetric: NonCopyable, ReferenceCounted<ContinuousMetric<T>>, MetricUtil<ContinuousMetric<T>, T>, BaseMetric {
// Needed for MetricUtil
static const StringRef metricType;
private:
EventField<TimeAndValue<T>> field;
TimeAndValue<T> tv;
bool recorded;
public:
ContinuousMetric(MetricNameRef const &name, T const &initial)
: BaseMetric(name), recorded(false) {
tv.value = initial;
}
virtual void addref() { ReferenceCounted<ContinuousMetric<T>>::addref(); }
virtual void delref() { ReferenceCounted<ContinuousMetric<T>>::delref(); }
T getValue() const {
return tv.value;
}
void flushData(const MetricKeyRef &mk, uint64_t rollTime, MetricUpdateBatch &batch) {
if( !recorded ) {
batch.updates.push_back(std::make_pair(mk.packLatestKey(), getLatestAsValue()));
recorded = true;
}
field.flushField(mk, rollTime, batch);
}
void rollMetric(uint64_t t) {
field.rollMetric(t);
}
Standalone<StringRef> getLatestAsValue() {
FieldValueBlockEncoding< TimeAndValue< T > > enc;
BinaryWriter wr(AssumeVersion(currentProtocolVersion));
// Write a header so the client can treat this value like a normal data value block.
// TOOD: If it is useful, this could be the current header value of the most recently logged level.
wr << FieldHeader<TimeAndValue<T>>();
enc.write(wr, tv);
return wr.toStringRef();
}
void onEnable() {
field.init();
change();
}
void onDisable() {
change();
}
void set(const T &v) {
if(v != tv.value) {
if(enabled)
change();
tv.value = v;
}
}
// requires += on T
void add(const T &delta) {
if(delta != T()) {
if(enabled)
change();
tv.value += delta;
}
}
// requires ! on T
void toggle() {
if(enabled)
change();
tv.value = !tv.value;
}
void change() {
uint64_t toggleTime = timer_int();
int64_t bytes = 0;
if(tv.time != 0) {
double x = g_random->random01();
int64_t l = 0;
if (x == 0.0)
l = FLOW_KNOBS->MAX_METRIC_LEVEL-1;
else if (toggleTime != tv.time)
l = std::min(
FLOW_KNOBS->MAX_METRIC_LEVEL-1,
(int64_t)(
log((toggleTime - tv.time) / x) /
FLOW_KNOBS->METRIC_LEVEL_DIVISOR
)
);
if(!canLog(l))
return;
bool overflow = false;
field.log(tv, tv.time, l, overflow, bytes);
if(overflow)
field.nextKey(toggleTime, l);
}
tv.time = toggleTime;
recorded = false;
TDMetricCollection::getTDMetrics()->checkRoll(tv.time, bytes);
}
};
typedef ContinuousMetric<int64_t> Int64Metric;
typedef Int64Metric VersionMetric;
typedef ContinuousMetric<bool> BoolMetric;
typedef ContinuousMetric<Standalone<StringRef>> StringMetric;
// MetricHandle / EventMetricHandle are wrappers for a Reference<MetricType> which provides
// the following interface conveniences
//
// * The underlying metric reference is always initialized to a valid object. That valid object
// may not actually be in a metric collection and therefore may not actually be able to write
// data to a database, but it will work in other ways (i.e. int metrics will act like integers).
//
// * Operator =, ++, --, +=, and -= can be used as though the handle is an object of the MetricType::ValueType of
// the metric type for which it is a handle.
//
// * Operator -> is defined such that the MetricHandle acts like a pointer to the underlying MetricType
//
// * Cast operator to MetricType::ValueType is defined so that the handle will act like a MetricType::ValueType
//
// * The last three features allow, for example, a MetricHandle<Int64Metric> to be a drop-in replacement for an int64_t.
//
template <typename T>
struct MetricHandle {
template<typename ValueType = typename T::ValueType>
MetricHandle(StringRef const &name = StringRef(), StringRef const &id = StringRef(), ValueType const &initial = ValueType())
: ref(T::getOrCreateInstance(name, id, true, initial)) {
}
// Initialize this handle to point to a new or existing metric with (name, id). If a new metric is created then the handle's
// current metric's current value will be the new metric's initial value. This allows Metric handle users to treate their
// Metric variables as normal variables and then bind them to actual logging metrics later while continuing with the current value.
void init(StringRef const &name, StringRef const &id = StringRef()) {
ref = T::getOrCreateInstance(name, id, true, ref->getValue());
}
void init(StringRef const &name, StringRef const &id, typename T::ValueType const &initial) {
ref = T::getOrCreateInstance(name, id, true, initial);
}
void operator=(typename T::ValueType const &v) {
ref->set(v);
}
void operator++() {
ref->add(1);
}
void operator++(int) {
ref->add(1);
}
void operator--() {
ref->add(-1);
}
void operator--(int) {
ref->add(-1);
}
void operator+=(typename T::ValueType const &v) {
ref->add(v);
}
void operator-=(typename T::ValueType const &v) {
ref->add(-v);
}
T * operator-> () { return ref.getPtr(); }
operator typename T::ValueType () const { return ref->getValue(); }
typename T::ValueType getValue() const { return ref->getValue(); }
Reference<T> ref;
};
typedef MetricHandle<Int64Metric> Int64MetricHandle;
typedef MetricHandle<VersionMetric> VersionMetricHandle;
typedef MetricHandle<BoolMetric> BoolMetricHandle;
typedef MetricHandle<StringMetric> StringMetricHandle;
template <typename E>
using EventMetricHandle = MetricHandle<EventMetric<E>>;
#include "flow/unactorcompiler.h"
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#endif