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https://github.com/dashpay/dash.git
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302 lines
9.6 KiB
C++
302 lines
9.6 KiB
C++
// Copyright (c) 2012-2015 The Bitcoin Core developers
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// Distributed under the MIT software license, see the accompanying
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// file COPYING or http://www.opensource.org/licenses/mit-license.php.
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#include "bloom.h"
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#include "primitives/transaction.h"
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#include "hash.h"
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#include "script/script.h"
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#include "script/standard.h"
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#include "random.h"
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#include "streams.h"
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#include <math.h>
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#include <stdlib.h>
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#include <boost/foreach.hpp>
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#define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455
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#define LN2 0.6931471805599453094172321214581765680755001343602552
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using namespace std;
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CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn, unsigned char nFlagsIn) :
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/**
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* The ideal size for a bloom filter with a given number of elements and false positive rate is:
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* - nElements * log(fp rate) / ln(2)^2
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* We ignore filter parameters which will create a bloom filter larger than the protocol limits
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*/
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vData(min((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)), MAX_BLOOM_FILTER_SIZE * 8) / 8),
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/**
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* The ideal number of hash functions is filter size * ln(2) / number of elements
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* Again, we ignore filter parameters which will create a bloom filter with more hash functions than the protocol limits
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* See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these formulas
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*/
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isFull(false),
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isEmpty(true),
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nHashFuncs(min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)),
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nTweak(nTweakIn),
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nFlags(nFlagsIn)
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{
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}
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// Private constructor used by CRollingBloomFilter
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CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn) :
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vData((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)) / 8),
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isFull(false),
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isEmpty(true),
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nHashFuncs((unsigned int)(vData.size() * 8 / nElements * LN2)),
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nTweak(nTweakIn),
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nFlags(BLOOM_UPDATE_NONE)
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{
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}
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inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const
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{
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// 0xFBA4C795 chosen as it guarantees a reasonable bit difference between nHashNum values.
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return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (vData.size() * 8);
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}
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void CBloomFilter::insert(const vector<unsigned char>& vKey)
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{
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if (isFull)
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return;
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for (unsigned int i = 0; i < nHashFuncs; i++)
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{
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unsigned int nIndex = Hash(i, vKey);
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// Sets bit nIndex of vData
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vData[nIndex >> 3] |= (1 << (7 & nIndex));
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}
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isEmpty = false;
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}
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void CBloomFilter::insert(const COutPoint& outpoint)
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{
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CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
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stream << outpoint;
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vector<unsigned char> data(stream.begin(), stream.end());
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insert(data);
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}
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void CBloomFilter::insert(const uint256& hash)
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{
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vector<unsigned char> data(hash.begin(), hash.end());
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insert(data);
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}
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bool CBloomFilter::contains(const vector<unsigned char>& vKey) const
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{
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if (isFull)
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return true;
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if (isEmpty)
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return false;
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for (unsigned int i = 0; i < nHashFuncs; i++)
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{
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unsigned int nIndex = Hash(i, vKey);
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// Checks bit nIndex of vData
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if (!(vData[nIndex >> 3] & (1 << (7 & nIndex))))
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return false;
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}
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return true;
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}
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bool CBloomFilter::contains(const COutPoint& outpoint) const
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{
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CDataStream stream(SER_NETWORK, PROTOCOL_VERSION);
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stream << outpoint;
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vector<unsigned char> data(stream.begin(), stream.end());
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return contains(data);
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}
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bool CBloomFilter::contains(const uint256& hash) const
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{
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vector<unsigned char> data(hash.begin(), hash.end());
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return contains(data);
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}
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void CBloomFilter::clear()
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{
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vData.assign(vData.size(),0);
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isFull = false;
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isEmpty = true;
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}
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void CBloomFilter::reset(unsigned int nNewTweak)
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{
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clear();
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nTweak = nNewTweak;
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}
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bool CBloomFilter::IsWithinSizeConstraints() const
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{
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return vData.size() <= MAX_BLOOM_FILTER_SIZE && nHashFuncs <= MAX_HASH_FUNCS;
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}
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bool CBloomFilter::IsRelevantAndUpdate(const CTransaction& tx)
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{
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bool fFound = false;
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// Match if the filter contains the hash of tx
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// for finding tx when they appear in a block
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if (isFull)
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return true;
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if (isEmpty)
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return false;
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const uint256& hash = tx.GetHash();
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if (contains(hash))
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fFound = true;
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for (unsigned int i = 0; i < tx.vout.size(); i++)
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{
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const CTxOut& txout = tx.vout[i];
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// Match if the filter contains any arbitrary script data element in any scriptPubKey in tx
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// If this matches, also add the specific output that was matched.
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// This means clients don't have to update the filter themselves when a new relevant tx
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// is discovered in order to find spending transactions, which avoids round-tripping and race conditions.
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CScript::const_iterator pc = txout.scriptPubKey.begin();
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vector<unsigned char> data;
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while (pc < txout.scriptPubKey.end())
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{
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opcodetype opcode;
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if (!txout.scriptPubKey.GetOp(pc, opcode, data))
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break;
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if (data.size() != 0 && contains(data))
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{
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fFound = true;
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if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL)
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insert(COutPoint(hash, i));
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else if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_P2PUBKEY_ONLY)
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{
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txnouttype type;
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vector<vector<unsigned char> > vSolutions;
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if (Solver(txout.scriptPubKey, type, vSolutions) &&
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(type == TX_PUBKEY || type == TX_MULTISIG))
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insert(COutPoint(hash, i));
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}
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break;
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}
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}
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}
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if (fFound)
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return true;
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BOOST_FOREACH(const CTxIn& txin, tx.vin)
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{
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// Match if the filter contains an outpoint tx spends
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if (contains(txin.prevout))
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return true;
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// Match if the filter contains any arbitrary script data element in any scriptSig in tx
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CScript::const_iterator pc = txin.scriptSig.begin();
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vector<unsigned char> data;
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while (pc < txin.scriptSig.end())
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{
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opcodetype opcode;
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if (!txin.scriptSig.GetOp(pc, opcode, data))
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break;
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if (data.size() != 0 && contains(data))
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return true;
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}
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}
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return false;
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}
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void CBloomFilter::UpdateEmptyFull()
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{
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bool full = true;
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bool empty = true;
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for (unsigned int i = 0; i < vData.size(); i++)
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{
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full &= vData[i] == 0xff;
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empty &= vData[i] == 0;
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}
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isFull = full;
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isEmpty = empty;
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}
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CRollingBloomFilter::CRollingBloomFilter(unsigned int nElements, double fpRate)
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{
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double logFpRate = log(fpRate);
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/* The optimal number of hash functions is log(fpRate) / log(0.5), but
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* restrict it to the range 1-50. */
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nHashFuncs = std::max(1, std::min((int)round(logFpRate / log(0.5)), 50));
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/* In this rolling bloom filter, we'll store between 2 and 3 generations of nElements / 2 entries. */
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nEntriesPerGeneration = (nElements + 1) / 2;
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uint32_t nMaxElements = nEntriesPerGeneration * 3;
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/* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits), nHashFuncs)
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* => pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits)
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* => 1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs * nMaxElements / nFilterBits)
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* => log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs * nMaxElements / nFilterBits
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* => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - pow(fpRate, 1.0 / nHashFuncs))
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* => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs))
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*/
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uint32_t nFilterBits = (uint32_t)ceil(-1.0 * nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs)));
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data.clear();
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/* We store up to 16 'bits' per data element. */
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data.resize((nFilterBits + 15) / 16);
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reset();
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}
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/* Similar to CBloomFilter::Hash */
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inline unsigned int CRollingBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const {
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return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (data.size() * 16);
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}
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void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey)
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{
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if (nEntriesThisGeneration == nEntriesPerGeneration) {
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nEntriesThisGeneration = 0;
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nGeneration++;
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if (nGeneration == 4) {
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nGeneration = 1;
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}
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/* Wipe old entries that used this generation number. */
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for (uint32_t p = 0; p < data.size() * 16; p++) {
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if (get(p) == nGeneration) {
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put(p, 0);
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}
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}
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}
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nEntriesThisGeneration++;
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for (int n = 0; n < nHashFuncs; n++) {
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uint32_t h = Hash(n, vKey);
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put(h, nGeneration);
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}
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}
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void CRollingBloomFilter::insert(const uint256& hash)
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{
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vector<unsigned char> data(hash.begin(), hash.end());
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insert(data);
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}
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bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const
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{
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for (int n = 0; n < nHashFuncs; n++) {
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uint32_t h = Hash(n, vKey);
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if (get(h) == 0) {
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return false;
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}
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}
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return true;
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}
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bool CRollingBloomFilter::contains(const uint256& hash) const
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{
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vector<unsigned char> data(hash.begin(), hash.end());
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return contains(data);
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}
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void CRollingBloomFilter::reset()
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{
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nTweak = GetRand(std::numeric_limits<unsigned int>::max());
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nEntriesThisGeneration = 0;
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nGeneration = 1;
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for (std::vector<uint32_t>::iterator it = data.begin(); it != data.end(); it++) {
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*it = 0;
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}
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}
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