1374 lines
45 KiB
C++
Executable File
1374 lines
45 KiB
C++
Executable File
/*
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* TDMetric.actor.h
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*
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* This source file is part of the FoundationDB open source project
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*
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* Copyright 2013-2018 Apple Inc. and the FoundationDB project authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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// When actually compiled (NO_INTELLISENSE), include the generated version of this file. In intellisense use the source version.
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#if defined(NO_INTELLISENSE) && !defined(FLOW_TDMETRIC_ACTOR_G_H)
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#define FLOW_TDMETRIC_ACTOR_G_H
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#include "TDMetric.actor.g.h"
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#elif !defined(FLOW_TDMETRIC_ACTOR_H)
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#define FLOW_TDMETRIC_ACTOR_H
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#include "actorcompiler.h"
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#include "flow.h"
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#include "IndexedSet.h"
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#include "network.h"
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#include "Knobs.h"
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#include "genericactors.actor.h"
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#include "CompressedInt.h"
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#include <algorithm>
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#include <functional>
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struct MetricNameRef {
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MetricNameRef() {}
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MetricNameRef(const StringRef& type, const StringRef& name, const StringRef &id)
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: type(type), name(name), id(id) {
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}
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MetricNameRef(Arena& a, const MetricNameRef& copyFrom)
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: type(a, copyFrom.type), name(a, copyFrom.name), id(a, copyFrom.id) {
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}
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StringRef type, name, id;
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std::string toString() const {
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return format("(%s,%s,%s,%s)", type.toString().c_str(), name.toString().c_str(), id.toString().c_str());
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}
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int expectedSize() const {
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return type.expectedSize() + name.expectedSize();
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}
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};
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extern std::string reduceFilename(std::string const &filename);
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inline bool operator < (const MetricNameRef& l, const MetricNameRef& r ) {
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int cmp = l.type.compare(r.type);
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if(cmp == 0) {
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cmp = l.name.compare(r.name);
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if(cmp == 0)
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cmp = l.id.compare(r.id);
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}
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return cmp < 0;
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}
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inline bool operator == (const MetricNameRef& l, const MetricNameRef& r ) {
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return l.type == r.type && l.name == r.name && l.id == r.id;
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}
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inline bool operator != (const MetricNameRef& l, const MetricNameRef& r ) {
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return !(l == r);
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}
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struct KeyWithWriter {
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Standalone<StringRef> key;
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BinaryWriter writer;
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int writerOffset;
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KeyWithWriter( Standalone<StringRef> const& key, BinaryWriter& writer, int writerOffset = 0) : key(key), writer(std::move(writer)), writerOffset(writerOffset) {}
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KeyWithWriter( KeyWithWriter&& r ) : key(std::move(r.key)), writer(std::move(r.writer)), writerOffset(r.writerOffset) {}
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void operator=( KeyWithWriter&& r ) { key = std::move(r.key); writer = std::move(r.writer); writerOffset = r.writerOffset; }
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StringRef value() {
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return StringRef(writer.toStringRef().substr(writerOffset));
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}
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};
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// This is a very minimal interface for getting metric data from the DB which is needed
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// to support continuing existing metric data series.
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// It's lack of generality is intentional.
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class IMetricDB {
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public:
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virtual ~IMetricDB() {}
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// key should be the result of calling metricKey or metricFieldKey with time = 0
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virtual Future<Optional<Standalone<StringRef>>> getLastBlock(Standalone<StringRef> key) = 0;
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};
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// Key generator for metric keys for various things.
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struct MetricKeyRef {
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MetricKeyRef() : level(-1) {}
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MetricKeyRef(Arena& a, const MetricKeyRef& copyFrom)
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: prefix(a, copyFrom.prefix), name(a, copyFrom.name), address(a, copyFrom.address),
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fieldName(a, copyFrom.fieldName), fieldType(a, copyFrom.fieldType), level(copyFrom.level) {
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}
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StringRef prefix;
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MetricNameRef name;
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StringRef address;
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StringRef fieldName;
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StringRef fieldType;
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uint64_t level;
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int expectedSize() const {
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return prefix.expectedSize() + name.expectedSize() + address.expectedSize() + fieldName.expectedSize() + fieldType.expectedSize();
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}
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template <typename T> inline MetricKeyRef withField(const T &field) const {
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MetricKeyRef mk(*this);
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mk.fieldName = field.name();
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mk.fieldType = field.typeName();
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return mk;
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}
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const Standalone<StringRef> packLatestKey() const;
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const Standalone<StringRef> packDataKey(int64_t time = -1) const;
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const Standalone<StringRef> packFieldRegKey() const;
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bool isField() const { return fieldName.size() > 0 && fieldType.size() > 0; }
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void writeField(BinaryWriter &wr) const;
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void writeMetricName(BinaryWriter &wr) const;
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};
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struct MetricUpdateBatch {
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std::vector<KeyWithWriter> inserts;
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std::vector<KeyWithWriter> appends;
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std::vector<std::pair<Standalone<StringRef>,Standalone<StringRef>>> updates;
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std::vector<std::function<Future<Void>(IMetricDB *, MetricUpdateBatch *)>> callbacks;
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void clear() {
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inserts.clear();
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appends.clear();
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updates.clear();
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callbacks.clear();
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}
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};
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template<typename T>
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inline const StringRef metricTypeName() {
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// If this function does not compile then T is not a supported metric type
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return T::metric_field_type();
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}
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#define MAKE_TYPENAME(T, S) template<> inline const StringRef metricTypeName<T>() { return LiteralStringRef(S); }
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MAKE_TYPENAME(bool, "Bool")
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MAKE_TYPENAME(int64_t, "Int64")
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MAKE_TYPENAME(double, "Double")
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MAKE_TYPENAME(Standalone<StringRef>, "String")
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#undef MAKE_TYPENAME
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struct BaseMetric;
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// The collection of metrics that exist for a single process, at a single address.
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class TDMetricCollection {
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public:
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TDMetricCollection() : currentTimeBytes(0) {}
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// Metric Name to reference to its instance
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Map<Standalone<MetricNameRef>, Reference<BaseMetric>, MapPair<Standalone<MetricNameRef>, Reference<BaseMetric>>, int> metricMap;
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AsyncTrigger metricAdded;
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AsyncTrigger metricEnabled;
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AsyncTrigger metricRegistrationChanged;
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// Initialize the collection. Once this returns true, metric data can be written to a database. Note that metric data can be logged
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// before that time, just not written to a database.
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bool init() {
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// Get and store the local address in the metric collection, but only if it is not 0.0.0.0:0
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if( address.size() == 0 ) {
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NetworkAddress addr = g_network->getLocalAddress();
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if(addr.ip != 0 && addr.port != 0)
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address = StringRef(addr.toString());
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}
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return address.size() != 0;
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}
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// Returns the TDMetrics that the calling process should use
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static TDMetricCollection* getTDMetrics() {
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if(g_network == nullptr)
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return nullptr;
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return static_cast<TDMetricCollection*>((void*) g_network->global(INetwork::enTDMetrics));
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}
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Deque<uint64_t> rollTimes;
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int64_t currentTimeBytes;
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Standalone<StringRef> address;
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void checkRoll(uint64_t t, int64_t usedBytes);
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bool canLog(int level);
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};
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struct MetricData {
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uint64_t start;
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uint64_t rollTime;
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uint64_t appendStart;
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BinaryWriter writer;
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explicit MetricData(uint64_t appendStart = 0) :
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writer(AssumeVersion(currentProtocolVersion)),
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start(0),
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rollTime(std::numeric_limits<uint64_t>::max()),
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appendStart(appendStart) {
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}
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MetricData( MetricData&& r ) noexcept(true) :
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start(r.start),
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rollTime(r.rollTime),
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appendStart(r.appendStart),
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writer(std::move(r.writer)) {
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}
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void operator=( MetricData&& r ) noexcept(true) {
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start = r.start; rollTime = r.rollTime; appendStart = r.appendStart; writer = std::move(r.writer);
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}
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std::string toString();
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};
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// Some common methods to reduce code redundancy across different metric definitions
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template<typename T, typename _ValueType = Void>
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struct MetricUtil {
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typedef _ValueType ValueType;
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typedef T MetricType;
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// Looks up a metric by name and id and returns a reference to it if it exists.
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// Empty names will not be looked up.
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// If create is true then a metric will be created with the given initial value if one could not be found to return.
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// If a metric is created and name is not empty then the metric will be placed in the collection.
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static Reference<T> getOrCreateInstance(StringRef const& name, StringRef const &id = StringRef(), bool create = false, ValueType initial = ValueType()) {
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Reference<T> m;
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TDMetricCollection *collection = TDMetricCollection::getTDMetrics();
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// If there is a metric collect and this metric has a name then look it up in the collection
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bool useMap = collection != nullptr && name.size() > 0;
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MetricNameRef mname;
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if(useMap) {
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mname = MetricNameRef(T::metricType, name, id);
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auto mi = collection->metricMap.find(mname);
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if(mi != collection->metricMap.end()) {
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m = mi->value.castTo<T>();
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}
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}
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// 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
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if(!m && create) {
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// Metric not found in collection but create is set then create it in the map
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m = Reference<T>(new T(mname, initial));
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if(useMap) {
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collection->metricMap[mname] = m.template castTo<BaseMetric>();
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collection->metricAdded.trigger();
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}
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}
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return m;
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}
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// Lookup the T metric by name and return its value (or nullptr if it doesn't exist)
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static T * lookupMetric(MetricNameRef const &name) {
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auto it = T::metricMap().find(name);
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if(it != T::metricMap().end())
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return it->value;
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return nullptr;
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}
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};
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// index_sequence implementation since VS2013 doesn't have it yet
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template <size_t... Ints> class index_sequence {
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public:
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static size_t size() { return sizeof...(Ints); }
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};
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template <size_t Start, typename Indices, size_t End>
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struct make_index_sequence_impl;
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template <size_t Start, size_t... Indices, size_t End>
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struct make_index_sequence_impl<Start, index_sequence<Indices...>, End> {
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typedef typename make_index_sequence_impl<
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Start + 1, index_sequence<Indices..., Start>, End>::type type;
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};
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template <size_t End, size_t... Indices>
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struct make_index_sequence_impl<End, index_sequence<Indices...>, End> {
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typedef index_sequence<Indices...> type;
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};
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// The code that actually implements tuple_map
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template <size_t I, typename F, typename... Tuples>
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auto tuple_zip_invoke(F f, const Tuples &... ts) -> decltype( f(std::get<I>(ts)...) ) {
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return f(std::get<I>(ts)...);
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}
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template <typename F, size_t... Is, typename... Tuples>
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auto tuple_map_impl(F f, index_sequence<Is...>, const Tuples &... ts) -> decltype( std::make_tuple(tuple_zip_invoke<Is>(f, ts...)...) ) {
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return std::make_tuple(tuple_zip_invoke<Is>(f, ts...)...);
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}
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// tuple_map( f(a,b), (a1,a2,a3), (b1,b2,b3) ) = (f(a1,b1), f(a2,b2), f(a3,b3))
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template <typename F, typename Tuple, typename... Tuples>
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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...) ) {
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return tuple_map_impl(f, typename make_index_sequence_impl<0, index_sequence<>, std::tuple_size<Tuple>::value>::type(), t, ts...);
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}
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template <class T>
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struct Descriptor {};
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// FieldHeader is a serializable (FIXED SIZE!) and updatable Header type for Metric field levels.
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// Update is via += with either a T or another FieldHeader
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// Default implementation is sufficient for ints and doubles
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template<typename T>
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struct FieldHeader {
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FieldHeader() : version(1), count(0), sum(0) {}
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uint8_t version;
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int64_t count;
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// sum is a T if T is arithmetic, otherwise it's an int64_t
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typename std::conditional<std::is_floating_point<T>::value, double, int64_t>::type sum;
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void update(FieldHeader const &h) {
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count += h.count;
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sum += h.sum;
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}
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void update(T const &v) {
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++count;
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sum += v;
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}
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template<class Ar> void serialize(Ar &ar) {
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ar & version;
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ASSERT(version == 1);
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ar & count & sum;
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}
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};
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template <> inline void FieldHeader<Standalone<StringRef>>::update(Standalone<StringRef> const &v) {
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++count;
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sum += v.size();
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}
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// FieldValueBlockEncoding is a class for reading and writing encoded field values to and from field
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// value data blocks. Note that an implementation can be stateful.
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// Proper usage requires that a single Encoding instance is used to either write all field values to a metric
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// data block or to read all field values from a metric value block. This usage pattern enables enables
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// encoding and decoding values as deltas from previous values.
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//
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// The default implementation works for ints and writes delta from the previous value.
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template <typename T>
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struct FieldValueBlockEncoding {
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FieldValueBlockEncoding() : prev(0) {}
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inline void write(BinaryWriter &w, T v) {
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w << CompressedInt<T>(v - prev);
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prev = v;
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}
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T read(BinaryReader &r) {
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CompressedInt<T> v;
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r >> v;
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prev += v.value;
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return prev;
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}
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T prev;
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};
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template <>
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struct FieldValueBlockEncoding<double> {
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inline void write(BinaryWriter &w, double v) {
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w << v;
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}
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double read(BinaryReader &r) {
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double v;
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r >> v;
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return v;
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}
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};
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template <>
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struct FieldValueBlockEncoding<bool> {
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inline void write(BinaryWriter &w, bool v) {
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w.serializeBytes( v ? LiteralStringRef("\x01") : LiteralStringRef("\x00") );
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}
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bool read(BinaryReader &r) {
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uint8_t *v = (uint8_t *)r.readBytes(sizeof(uint8_t));
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return *v != 0;
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}
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};
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// Encoder for strings, writes deltas
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template <>
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struct FieldValueBlockEncoding<Standalone<StringRef>> {
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inline void write(BinaryWriter &w, Standalone<StringRef> const &v) {
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int reuse = 0;
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int stop = std::min(v.size(), prev.size());
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while(reuse < stop && v[reuse] == prev[reuse])
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++reuse;
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w << CompressedInt<int>(reuse) << CompressedInt<int>(v.size() - reuse);
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if(v.size() > reuse)
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w.serializeBytes(v.substr(reuse));
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prev = v;
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}
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Standalone<StringRef> read(BinaryReader &r) {
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CompressedInt<int> reuse;
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CompressedInt<int> extra;
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r >> reuse >> extra;
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ASSERT(reuse.value >= 0 && extra.value >= 0 && reuse.value <= prev.size());
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Standalone<StringRef> v = makeString(reuse.value + extra.value);
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memcpy(mutateString(v), prev.begin(), reuse.value);
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memcpy(mutateString(v) + reuse.value, r.readBytes(extra.value), extra.value);
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prev = v;
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return v;
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}
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// Using a Standalone<StringRef> for prev is efficient for writing but not great for reading.
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Standalone<StringRef> prev;
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};
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// Field level for value type of T using header type of Header. Default header type is the default FieldHeader implementation for type T.
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template <class T, class Header = FieldHeader<T>, class Encoder = FieldValueBlockEncoding<T>>
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struct FieldLevel {
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Deque<MetricData> metrics;
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int64_t appendUsed;
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Header header;
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// The previous header and the last timestamp at which an out going MetricData block requires header patching
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Optional<Header> previousHeader;
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uint64_t lastTimeRequiringHeaderPatch;
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Encoder enc;
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explicit FieldLevel() : appendUsed(0) {
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metrics.emplace_back(MetricData());
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metrics.back().writer << header;
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}
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FieldLevel(FieldLevel &&f)
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: metrics(std::move(f.metrics)), appendUsed(f.appendUsed), enc(f.enc), header(f.header),
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previousHeader(f.previousHeader), lastTimeRequiringHeaderPatch(f.lastTimeRequiringHeaderPatch) {
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}
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// update Header, use Encoder to write T v
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void log( T v, uint64_t t, bool& overflow, int64_t& bytes ) {
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int lastLength = metrics.back().writer.getLength();
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if( metrics.back().start == 0 )
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metrics.back().start = t;
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header.update(v);
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enc.write(metrics.back().writer, v);
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bytes += metrics.back().writer.getLength() - lastLength;
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if(lastLength + appendUsed > FLOW_KNOBS->MAX_METRIC_SIZE)
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overflow = true;
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}
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void nextKey( uint64_t t ) {
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// If nothing has actually been written to the current block, don't add a new block,
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// just modify this one if needed so that the next log call will set the ts for this block.
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auto &m = metrics.back();
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if(m.start == 0 && m.appendStart == 0)
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return;
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// This block would have appended but had no data so just reset it to a non-append block instead of adding a new one
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if(m.appendStart != 0 && m.writer.getLength() == 0) {
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m.appendStart = 0;
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m.writer << header;
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enc = Encoder();
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return;
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}
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metrics.back().rollTime = t;
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metrics.emplace_back(MetricData());
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metrics.back().writer << header;
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enc = Encoder();
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|
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) {
|
|
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) {
|
|
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())...
|
|
};
|
|
}
|
|
|
|
template <size_t... Is>
|
|
void initFields(index_sequence<Is...>) {
|
|
auto _ = {
|
|
(std::get<Is>(values).init(), Void())...
|
|
};
|
|
}
|
|
|
|
template <size_t... Is>
|
|
void nextKeys(index_sequence<Is...>, uint64_t t, int64_t l ) {
|
|
auto _ = {
|
|
(std::get<Is>(values).nextKey(t, l),Void())...
|
|
};
|
|
}
|
|
|
|
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 ) {
|
|
auto _ = {
|
|
(std::get<Is>(values).flushField( mk, rollTime, batch ),Void())...
|
|
};
|
|
}
|
|
|
|
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 ) {
|
|
auto _ = {
|
|
(std::get<Is>(values).rollMetric( t ),Void())...
|
|
};
|
|
}
|
|
|
|
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 ) {
|
|
auto _ = {
|
|
(std::get<Is>(values).registerField( mk, fieldKeys ),Void())...
|
|
};
|
|
}
|
|
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) {
|
|
ar & version;
|
|
ASSERT(version == 1);
|
|
ar & count & area;
|
|
}
|
|
};
|
|
|
|
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;
|
|
};
|
|
|
|
// ValueBlock encoder/decoder specialization for continuous bool metrics because they are encoded
|
|
// 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>>;
|
|
|
|
#endif
|