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// Copyright (c) 2009-2010 Satoshi Nakamoto
// Copyright (c) 2009-2013 The Bitcoin developers
// Distributed under the MIT/X11 software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#include "core.h"
#include "txmempool.h"
#include "util.h"
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
#include <boost/circular_buffer.hpp>
using namespace std;
CTxMemPoolEntry::CTxMemPoolEntry():
nFee(0), nTxSize(0), nTime(0), dPriority(0.0)
{
nHeight = MEMPOOL_HEIGHT;
}
CTxMemPoolEntry::CTxMemPoolEntry(const CTransaction& _tx, int64_t _nFee,
int64_t _nTime, double _dPriority,
unsigned int _nHeight):
tx(_tx), nFee(_nFee), nTime(_nTime), dPriority(_dPriority), nHeight(_nHeight)
{
nTxSize = ::GetSerializeSize(tx, SER_NETWORK, PROTOCOL_VERSION);
nModSize = tx.CalculateModifiedSize(nTxSize);
}
CTxMemPoolEntry::CTxMemPoolEntry(const CTxMemPoolEntry& other)
{
*this = other;
}
double
CTxMemPoolEntry::GetPriority(unsigned int currentHeight) const
{
int64_t nValueIn = tx.GetValueOut()+nFee;
double deltaPriority = ((double)(currentHeight-nHeight)*nValueIn)/nModSize;
double dResult = dPriority + deltaPriority;
return dResult;
}
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
//
// Keep track of fee/priority for transactions confirmed within N blocks
//
class CBlockAverage
{
private:
boost::circular_buffer<CFeeRate> feeSamples;
boost::circular_buffer<double> prioritySamples;
template<typename T> std::vector<T> buf2vec(boost::circular_buffer<T> buf) const
{
std::vector<T> vec(buf.begin(), buf.end());
return vec;
}
public:
CBlockAverage() : feeSamples(100), prioritySamples(100) { }
void RecordFee(const CFeeRate& feeRate) {
feeSamples.push_back(feeRate);
}
void RecordPriority(double priority) {
prioritySamples.push_back(priority);
}
size_t FeeSamples() const { return feeSamples.size(); }
size_t GetFeeSamples(std::vector<CFeeRate>& insertInto) const
{
BOOST_FOREACH(const CFeeRate& f, feeSamples)
insertInto.push_back(f);
return feeSamples.size();
}
size_t PrioritySamples() const { return prioritySamples.size(); }
size_t GetPrioritySamples(std::vector<double>& insertInto) const
{
BOOST_FOREACH(double d, prioritySamples)
insertInto.push_back(d);
return prioritySamples.size();
}
// Used as belt-and-suspenders check when reading to detect
// file corruption
bool AreSane(const std::vector<CFeeRate>& vecFee, const CFeeRate& minRelayFee)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
{
BOOST_FOREACH(CFeeRate fee, vecFee)
{
if (fee < CFeeRate(0))
return false;
if (fee.GetFeePerK() > minRelayFee.GetFeePerK() * 10000)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
return false;
}
return true;
}
bool AreSane(const std::vector<double> vecPriority)
{
BOOST_FOREACH(double priority, vecPriority)
{
if (priority < 0)
return false;
}
return true;
}
void Write(CAutoFile& fileout) const
{
std::vector<CFeeRate> vecFee = buf2vec(feeSamples);
fileout << vecFee;
std::vector<double> vecPriority = buf2vec(prioritySamples);
fileout << vecPriority;
}
void Read(CAutoFile& filein, const CFeeRate& minRelayFee) {
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
std::vector<CFeeRate> vecFee;
filein >> vecFee;
if (AreSane(vecFee, minRelayFee))
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
feeSamples.insert(feeSamples.end(), vecFee.begin(), vecFee.end());
else
throw runtime_error("Corrupt fee value in estimates file.");
std::vector<double> vecPriority;
filein >> vecPriority;
if (AreSane(vecPriority))
prioritySamples.insert(prioritySamples.end(), vecPriority.begin(), vecPriority.end());
else
throw runtime_error("Corrupt priority value in estimates file.");
if (feeSamples.size() + prioritySamples.size() > 0)
LogPrint("estimatefee", "Read %d fee samples and %d priority samples\n",
feeSamples.size(), prioritySamples.size());
}
};
class CMinerPolicyEstimator
{
private:
// Records observed averages transactions that confirmed within one block, two blocks,
// three blocks etc.
std::vector<CBlockAverage> history;
std::vector<CFeeRate> sortedFeeSamples;
std::vector<double> sortedPrioritySamples;
int nBestSeenHeight;
// nBlocksAgo is 0 based, i.e. transactions that confirmed in the highest seen block are
// nBlocksAgo == 0, transactions in the block before that are nBlocksAgo == 1 etc.
void seenTxConfirm(const CFeeRate& feeRate, const CFeeRate& minRelayFee, double dPriority, int nBlocksAgo)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
{
// Last entry records "everything else".
int nBlocksTruncated = min(nBlocksAgo, (int) history.size() - 1);
assert(nBlocksTruncated >= 0);
// We need to guess why the transaction was included in a block-- either
// because it is high-priority or because it has sufficient fees.
bool sufficientFee = (feeRate > minRelayFee);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
bool sufficientPriority = AllowFree(dPriority);
const char* assignedTo = "unassigned";
if (sufficientFee && !sufficientPriority)
{
history[nBlocksTruncated].RecordFee(feeRate);
assignedTo = "fee";
}
else if (sufficientPriority && !sufficientFee)
{
history[nBlocksTruncated].RecordPriority(dPriority);
assignedTo = "priority";
}
else
{
// Neither or both fee and priority sufficient to get confirmed:
// don't know why they got confirmed.
}
LogPrint("estimatefee", "Seen TX confirm: %s : %s fee/%g priority, took %d blocks\n",
assignedTo, feeRate.ToString(), dPriority, nBlocksAgo);
}
public:
CMinerPolicyEstimator(int nEntries) : nBestSeenHeight(0)
{
history.resize(nEntries);
}
void seenBlock(const std::vector<CTxMemPoolEntry>& entries, int nBlockHeight, const CFeeRate minRelayFee)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
{
if (nBlockHeight <= nBestSeenHeight)
{
// Ignore side chains and re-orgs; assuming they are random
// they don't affect the estimate.
// And if an attacker can re-org the chain at will, then
// you've got much bigger problems than "attacker can influence
// transaction fees."
return;
}
nBestSeenHeight = nBlockHeight;
// Fill up the history buckets based on how long transactions took
// to confirm.
std::vector<std::vector<const CTxMemPoolEntry*> > entriesByConfirmations;
entriesByConfirmations.resize(history.size());
BOOST_FOREACH(const CTxMemPoolEntry& entry, entries)
{
// How many blocks did it take for miners to include this transaction?
int delta = nBlockHeight - entry.GetHeight();
if (delta <= 0)
{
// Re-org made us lose height, this should only happen if we happen
// to re-org on a difficulty transition point: very rare!
continue;
}
if ((delta-1) >= (int)history.size())
delta = history.size(); // Last bucket is catch-all
entriesByConfirmations.at(delta-1).push_back(&entry);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
for (size_t i = 0; i < entriesByConfirmations.size(); i++)
{
std::vector<const CTxMemPoolEntry*> &e = entriesByConfirmations.at(i);
// Insert at most 10 random entries per bucket, otherwise a single block
// can dominate an estimate:
if (e.size() > 10) {
std::random_shuffle(e.begin(), e.end());
e.resize(10);
}
BOOST_FOREACH(const CTxMemPoolEntry* entry, e)
{
// Fees are stored and reported as BTC-per-kb:
CFeeRate feeRate(entry->GetFee(), entry->GetTxSize());
double dPriority = entry->GetPriority(entry->GetHeight()); // Want priority when it went IN
seenTxConfirm(feeRate, minRelayFee, dPriority, i);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
}
//After new samples are added, we have to clear the sorted lists,
//so they'll be resorted the next time someone asks for an estimate
sortedFeeSamples.clear();
sortedPrioritySamples.clear();
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
for (size_t i = 0; i < history.size(); i++) {
if (history[i].FeeSamples() + history[i].PrioritySamples() > 0)
LogPrint("estimatefee", "estimates: for confirming within %d blocks based on %d/%d samples, fee=%s, prio=%g\n",
i,
history[i].FeeSamples(), history[i].PrioritySamples(),
estimateFee(i+1).ToString(), estimatePriority(i+1));
}
}
// Can return CFeeRate(0) if we don't have any data for that many blocks back. nBlocksToConfirm is 1 based.
CFeeRate estimateFee(int nBlocksToConfirm)
{
nBlocksToConfirm--;
if (nBlocksToConfirm < 0 || nBlocksToConfirm >= (int)history.size())
return CFeeRate(0);
if (sortedFeeSamples.size() == 0)
{
for (size_t i = 0; i < history.size(); i++)
history.at(i).GetFeeSamples(sortedFeeSamples);
std::sort(sortedFeeSamples.begin(), sortedFeeSamples.end(),
std::greater<CFeeRate>());
}
if (sortedFeeSamples.size() < 11)
{
// Eleven is Gavin's Favorite Number
// ... but we also take a maximum of 10 samples per block so eleven means
// we're getting samples from at least two different blocks
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
return CFeeRate(0);
}
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
int nBucketSize = history.at(nBlocksToConfirm).FeeSamples();
// Estimates should not increase as number of confirmations goes up,
// but the estimates are noisy because confirmations happen discretely
// in blocks. To smooth out the estimates, use all samples in the history
// and use the nth highest where n is (number of samples in previous bucket +
// half the samples in nBlocksToConfirm bucket):
size_t nPrevSize = 0;
for (int i = 0; i < nBlocksToConfirm; i++)
nPrevSize += history.at(i).FeeSamples();
size_t index = min(nPrevSize + nBucketSize/2, sortedFeeSamples.size()-1);
return sortedFeeSamples[index];
}
double estimatePriority(int nBlocksToConfirm)
{
nBlocksToConfirm--;
if (nBlocksToConfirm < 0 || nBlocksToConfirm >= (int)history.size())
return -1;
if (sortedPrioritySamples.size() == 0)
{
for (size_t i = 0; i < history.size(); i++)
history.at(i).GetPrioritySamples(sortedPrioritySamples);
std::sort(sortedPrioritySamples.begin(), sortedPrioritySamples.end(),
std::greater<double>());
}
if (sortedPrioritySamples.size() < 11)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
return -1.0;
int nBucketSize = history.at(nBlocksToConfirm).PrioritySamples();
// Estimates should not increase as number of confirmations needed goes up,
// but the estimates are noisy because confirmations happen discretely
// in blocks. To smooth out the estimates, use all samples in the history
// and use the nth highest where n is (number of samples in previous buckets +
// half the samples in nBlocksToConfirm bucket).
size_t nPrevSize = 0;
for (int i = 0; i < nBlocksToConfirm; i++)
nPrevSize += history.at(i).PrioritySamples();
size_t index = min(nPrevSize + nBucketSize/2, sortedPrioritySamples.size()-1);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
return sortedPrioritySamples[index];
}
void Write(CAutoFile& fileout) const
{
fileout << nBestSeenHeight;
fileout << history.size();
BOOST_FOREACH(const CBlockAverage& entry, history)
{
entry.Write(fileout);
}
}
void Read(CAutoFile& filein, const CFeeRate& minRelayFee)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
{
int nFileBestSeenHeight;
filein >> nFileBestSeenHeight;
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
size_t numEntries;
filein >> numEntries;
if (numEntries <= 0 || numEntries > 10000)
throw runtime_error("Corrupt estimates file. Must have between 1 and 10k entires.");
std::vector<CBlockAverage> fileHistory;
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
for (size_t i = 0; i < numEntries; i++)
{
CBlockAverage entry;
entry.Read(filein, minRelayFee);
fileHistory.push_back(entry);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
//Now that we've processed the entire fee estimate data file and not
//thrown any errors, we can copy it to our history
nBestSeenHeight = nFileBestSeenHeight;
history = fileHistory;
assert(history.size() > 0);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
};
CTxMemPool::CTxMemPool(const CFeeRate& _minRelayFee) :
nTransactionsUpdated(0),
minRelayFee(_minRelayFee)
{
// Sanity checks off by default for performance, because otherwise
// accepting transactions becomes O(N^2) where N is the number
// of transactions in the pool
fSanityCheck = false;
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
// 25 blocks is a compromise between using a lot of disk/memory and
// trying to give accurate estimates to people who might be willing
// to wait a day or two to save a fraction of a penny in fees.
// Confirmation times for very-low-fee transactions that take more
// than an hour or three to confirm are highly variable.
minerPolicyEstimator = new CMinerPolicyEstimator(25);
}
CTxMemPool::~CTxMemPool()
{
delete minerPolicyEstimator;
}
void CTxMemPool::pruneSpent(const uint256 &hashTx, CCoins &coins)
{
LOCK(cs);
std::map<COutPoint, CInPoint>::iterator it = mapNextTx.lower_bound(COutPoint(hashTx, 0));
// iterate over all COutPoints in mapNextTx whose hash equals the provided hashTx
while (it != mapNextTx.end() && it->first.hash == hashTx) {
coins.Spend(it->first.n); // and remove those outputs from coins
it++;
}
}
unsigned int CTxMemPool::GetTransactionsUpdated() const
{
LOCK(cs);
return nTransactionsUpdated;
}
void CTxMemPool::AddTransactionsUpdated(unsigned int n)
{
LOCK(cs);
nTransactionsUpdated += n;
}
bool CTxMemPool::addUnchecked(const uint256& hash, const CTxMemPoolEntry &entry)
{
// Add to memory pool without checking anything.
// Used by main.cpp AcceptToMemoryPool(), which DOES do
// all the appropriate checks.
LOCK(cs);
{
mapTx[hash] = entry;
const CTransaction& tx = mapTx[hash].GetTx();
for (unsigned int i = 0; i < tx.vin.size(); i++)
mapNextTx[tx.vin[i].prevout] = CInPoint(&tx, i);
nTransactionsUpdated++;
totalTxSize += entry.GetTxSize();
}
return true;
}
void CTxMemPool::remove(const CTransaction &tx, std::list<CTransaction>& removed, bool fRecursive)
{
// Remove transaction from memory pool
{
LOCK(cs);
uint256 hash = tx.GetHash();
if (fRecursive) {
for (unsigned int i = 0; i < tx.vout.size(); i++) {
std::map<COutPoint, CInPoint>::iterator it = mapNextTx.find(COutPoint(hash, i));
if (it == mapNextTx.end())
continue;
remove(*it->second.ptx, removed, true);
}
}
if (mapTx.count(hash))
{
removed.push_front(tx);
BOOST_FOREACH(const CTxIn& txin, tx.vin)
mapNextTx.erase(txin.prevout);
totalTxSize -= mapTx[hash].GetTxSize();
mapTx.erase(hash);
nTransactionsUpdated++;
}
}
}
void CTxMemPool::removeConflicts(const CTransaction &tx, std::list<CTransaction>& removed)
{
// Remove transactions which depend on inputs of tx, recursively
list<CTransaction> result;
LOCK(cs);
BOOST_FOREACH(const CTxIn &txin, tx.vin) {
std::map<COutPoint, CInPoint>::iterator it = mapNextTx.find(txin.prevout);
if (it != mapNextTx.end()) {
const CTransaction &txConflict = *it->second.ptx;
if (txConflict != tx)
{
remove(txConflict, removed, true);
}
}
}
}
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
// Called when a block is connected. Removes from mempool and updates the miner fee estimator.
void CTxMemPool::removeForBlock(const std::vector<CTransaction>& vtx, unsigned int nBlockHeight,
std::list<CTransaction>& conflicts)
{
LOCK(cs);
std::vector<CTxMemPoolEntry> entries;
BOOST_FOREACH(const CTransaction& tx, vtx)
{
uint256 hash = tx.GetHash();
if (mapTx.count(hash))
entries.push_back(mapTx[hash]);
}
minerPolicyEstimator->seenBlock(entries, nBlockHeight, minRelayFee);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
BOOST_FOREACH(const CTransaction& tx, vtx)
{
std::list<CTransaction> dummy;
remove(tx, dummy, false);
removeConflicts(tx, conflicts);
ClearPrioritisation(tx.GetHash());
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
}
void CTxMemPool::clear()
{
LOCK(cs);
mapTx.clear();
mapNextTx.clear();
totalTxSize = 0;
++nTransactionsUpdated;
}
void CTxMemPool::check(const CCoinsViewCache *pcoins) const
{
if (!fSanityCheck)
return;
LogPrint("mempool", "Checking mempool with %u transactions and %u inputs\n", (unsigned int)mapTx.size(), (unsigned int)mapNextTx.size());
uint64_t checkTotal = 0;
LOCK(cs);
for (std::map<uint256, CTxMemPoolEntry>::const_iterator it = mapTx.begin(); it != mapTx.end(); it++) {
unsigned int i = 0;
checkTotal += it->second.GetTxSize();
const CTransaction& tx = it->second.GetTx();
BOOST_FOREACH(const CTxIn &txin, tx.vin) {
// Check that every mempool transaction's inputs refer to available coins, or other mempool tx's.
std::map<uint256, CTxMemPoolEntry>::const_iterator it2 = mapTx.find(txin.prevout.hash);
if (it2 != mapTx.end()) {
const CTransaction& tx2 = it2->second.GetTx();
assert(tx2.vout.size() > txin.prevout.n && !tx2.vout[txin.prevout.n].IsNull());
} else {
const CCoins &coins = pcoins->GetCoins(txin.prevout.hash);
assert(coins.IsAvailable(txin.prevout.n));
}
// Check whether its inputs are marked in mapNextTx.
std::map<COutPoint, CInPoint>::const_iterator it3 = mapNextTx.find(txin.prevout);
assert(it3 != mapNextTx.end());
assert(it3->second.ptx == &tx);
assert(it3->second.n == i);
i++;
}
}
for (std::map<COutPoint, CInPoint>::const_iterator it = mapNextTx.begin(); it != mapNextTx.end(); it++) {
uint256 hash = it->second.ptx->GetHash();
map<uint256, CTxMemPoolEntry>::const_iterator it2 = mapTx.find(hash);
const CTransaction& tx = it2->second.GetTx();
assert(it2 != mapTx.end());
assert(&tx == it->second.ptx);
assert(tx.vin.size() > it->second.n);
assert(it->first == it->second.ptx->vin[it->second.n].prevout);
}
assert(totalTxSize == checkTotal);
}
void CTxMemPool::queryHashes(vector<uint256>& vtxid)
{
vtxid.clear();
LOCK(cs);
vtxid.reserve(mapTx.size());
for (map<uint256, CTxMemPoolEntry>::iterator mi = mapTx.begin(); mi != mapTx.end(); ++mi)
vtxid.push_back((*mi).first);
}
bool CTxMemPool::lookup(uint256 hash, CTransaction& result) const
{
LOCK(cs);
map<uint256, CTxMemPoolEntry>::const_iterator i = mapTx.find(hash);
if (i == mapTx.end()) return false;
result = i->second.GetTx();
return true;
}
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
CFeeRate CTxMemPool::estimateFee(int nBlocks) const
{
LOCK(cs);
return minerPolicyEstimator->estimateFee(nBlocks);
}
double CTxMemPool::estimatePriority(int nBlocks) const
{
LOCK(cs);
return minerPolicyEstimator->estimatePriority(nBlocks);
}
bool
CTxMemPool::WriteFeeEstimates(CAutoFile& fileout) const
{
try {
LOCK(cs);
fileout << 99900; // version required to read: 0.9.99 or later
fileout << CLIENT_VERSION; // version that wrote the file
minerPolicyEstimator->Write(fileout);
}
catch (std::exception &e) {
LogPrintf("CTxMemPool::WriteFeeEstimates() : unable to write policy estimator data (non-fatal)");
return false;
}
return true;
}
bool
CTxMemPool::ReadFeeEstimates(CAutoFile& filein)
{
try {
int nVersionRequired, nVersionThatWrote;
filein >> nVersionRequired >> nVersionThatWrote;
if (nVersionRequired > CLIENT_VERSION)
return error("CTxMemPool::ReadFeeEstimates() : up-version (%d) fee estimate file", nVersionRequired);
LOCK(cs);
minerPolicyEstimator->Read(filein, minRelayFee);
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
}
catch (std::exception &e) {
LogPrintf("CTxMemPool::ReadFeeEstimates() : unable to read policy estimator data (non-fatal)");
return false;
}
return true;
}
void CTxMemPool::PrioritiseTransaction(const uint256 hash, const string strHash, double dPriorityDelta, int64_t nFeeDelta)
{
{
LOCK(cs);
std::pair<double, int64_t> &deltas = mapDeltas[hash];
deltas.first += dPriorityDelta;
deltas.second += nFeeDelta;
}
LogPrintf("PrioritiseTransaction: %s priority += %f, fee += %d\n", strHash.c_str(), dPriorityDelta, nFeeDelta);
}
void CTxMemPool::ApplyDeltas(const uint256 hash, double &dPriorityDelta, int64_t &nFeeDelta)
{
LOCK(cs);
std::map<uint256, std::pair<double, int64_t> >::iterator pos = mapDeltas.find(hash);
if (pos == mapDeltas.end())
return;
const std::pair<double, int64_t> &deltas = pos->second;
dPriorityDelta += deltas.first;
nFeeDelta += deltas.second;
}
void CTxMemPool::ClearPrioritisation(const uint256 hash)
{
LOCK(cs);
mapDeltas.erase(hash);
}
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
9 years ago
CCoinsViewMemPool::CCoinsViewMemPool(CCoinsView &baseIn, CTxMemPool &mempoolIn) : CCoinsViewBacked(baseIn), mempool(mempoolIn) { }
bool CCoinsViewMemPool::GetCoins(const uint256 &txid, CCoins &coins) const {
// If an entry in the mempool exists, always return that one, as it's guaranteed to never
// conflict with the underlying cache, and it cannot have pruned entries (as it contains full)
// transactions. First checking the underlying cache risks returning a pruned entry instead.
CTransaction tx;
if (mempool.lookup(txid, tx)) {
coins = CCoins(tx, MEMPOOL_HEIGHT);
return true;
}
return (base->GetCoins(txid, coins) && !coins.IsPruned());
}
bool CCoinsViewMemPool::HaveCoins(const uint256 &txid) const {
return mempool.exists(txid) || base->HaveCoins(txid);
}