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Diffstat (limited to 'src/bloom.cpp')
| -rw-r--r-- | src/bloom.cpp | 272 |
1 files changed, 272 insertions, 0 deletions
diff --git a/src/bloom.cpp b/src/bloom.cpp new file mode 100644 index 000000000..de8720659 --- /dev/null +++ b/src/bloom.cpp @@ -0,0 +1,272 @@ +// Copyright (c) 2012-2014 The Bitcoin Core developers +// Distributed under the MIT software license, see the accompanying +// file COPYING or http://www.opensource.org/licenses/mit-license.php. + +#include "bloom.h" + +#include "primitives/transaction.h" +#include "hash.h" +#include "script/script.h" +#include "script/standard.h" +#include "random.h" +#include "streams.h" + +#include <math.h> +#include <stdlib.h> + +#include <boost/foreach.hpp> + +#define LN2SQUARED 0.4804530139182014246671025263266649717305529515945455 +#define LN2 0.6931471805599453094172321214581765680755001343602552 + +using namespace std; + +CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn, unsigned char nFlagsIn) : + /** + * The ideal size for a bloom filter with a given number of elements and false positive rate is: + * - nElements * log(fp rate) / ln(2)^2 + * We ignore filter parameters which will create a bloom filter larger than the protocol limits + */ + vData(min((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)), MAX_BLOOM_FILTER_SIZE * 8) / 8), + /** + * The ideal number of hash functions is filter size * ln(2) / number of elements + * Again, we ignore filter parameters which will create a bloom filter with more hash functions than the protocol limits + * See https://en.wikipedia.org/wiki/Bloom_filter for an explanation of these formulas + */ + isFull(false), + isEmpty(false), + nHashFuncs(min((unsigned int)(vData.size() * 8 / nElements * LN2), MAX_HASH_FUNCS)), + nTweak(nTweakIn), + nFlags(nFlagsIn) +{ +} + +// Private constructor used by CRollingBloomFilter +CBloomFilter::CBloomFilter(unsigned int nElements, double nFPRate, unsigned int nTweakIn) : + vData((unsigned int)(-1 / LN2SQUARED * nElements * log(nFPRate)) / 8), + isFull(false), + isEmpty(true), + nHashFuncs((unsigned int)(vData.size() * 8 / nElements * LN2)), + nTweak(nTweakIn), + nFlags(BLOOM_UPDATE_NONE) +{ +} + +inline unsigned int CBloomFilter::Hash(unsigned int nHashNum, const std::vector<unsigned char>& vDataToHash) const +{ + // 0xFBA4C795 chosen as it guarantees a reasonable bit difference between nHashNum values. + return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash) % (vData.size() * 8); +} + +void CBloomFilter::insert(const vector<unsigned char>& vKey) +{ + if (isFull) + return; + for (unsigned int i = 0; i < nHashFuncs; i++) + { + unsigned int nIndex = Hash(i, vKey); + // Sets bit nIndex of vData + vData[nIndex >> 3] |= (1 << (7 & nIndex)); + } + isEmpty = false; +} + +void CBloomFilter::insert(const COutPoint& outpoint) +{ + CDataStream stream(SER_NETWORK, PROTOCOL_VERSION); + stream << outpoint; + vector<unsigned char> data(stream.begin(), stream.end()); + insert(data); +} + +void CBloomFilter::insert(const uint256& hash) +{ + vector<unsigned char> data(hash.begin(), hash.end()); + insert(data); +} + +bool CBloomFilter::contains(const vector<unsigned char>& vKey) const +{ + if (isFull) + return true; + if (isEmpty) + return false; + for (unsigned int i = 0; i < nHashFuncs; i++) + { + unsigned int nIndex = Hash(i, vKey); + // Checks bit nIndex of vData + if (!(vData[nIndex >> 3] & (1 << (7 & nIndex)))) + return false; + } + return true; +} + +bool CBloomFilter::contains(const COutPoint& outpoint) const +{ + CDataStream stream(SER_NETWORK, PROTOCOL_VERSION); + stream << outpoint; + vector<unsigned char> data(stream.begin(), stream.end()); + return contains(data); +} + +bool CBloomFilter::contains(const uint256& hash) const +{ + vector<unsigned char> data(hash.begin(), hash.end()); + return contains(data); +} + +void CBloomFilter::clear() +{ + vData.assign(vData.size(),0); + isFull = false; + isEmpty = true; +} + +void CBloomFilter::reset(unsigned int nNewTweak) +{ + clear(); + nTweak = nNewTweak; +} + +bool CBloomFilter::IsWithinSizeConstraints() const +{ + return vData.size() <= MAX_BLOOM_FILTER_SIZE && nHashFuncs <= MAX_HASH_FUNCS; +} + +bool CBloomFilter::IsRelevantAndUpdate(const CTransaction& tx) +{ + bool fFound = false; + // Match if the filter contains the hash of tx + // for finding tx when they appear in a block + if (isFull) + return true; + if (isEmpty) + return false; + const uint256& hash = tx.GetHash(); + if (contains(hash)) + fFound = true; + + for (unsigned int i = 0; i < tx.vout.size(); i++) + { + const CTxOut& txout = tx.vout[i]; + // Match if the filter contains any arbitrary script data element in any scriptPubKey in tx + // If this matches, also add the specific output that was matched. + // This means clients don't have to update the filter themselves when a new relevant tx + // is discovered in order to find spending transactions, which avoids round-tripping and race conditions. + CScript::const_iterator pc = txout.scriptPubKey.begin(); + vector<unsigned char> data; + while (pc < txout.scriptPubKey.end()) + { + opcodetype opcode; + if (!txout.scriptPubKey.GetOp(pc, opcode, data)) + break; + if (data.size() != 0 && contains(data)) + { + fFound = true; + if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_ALL) + insert(COutPoint(hash, i)); + else if ((nFlags & BLOOM_UPDATE_MASK) == BLOOM_UPDATE_P2PUBKEY_ONLY) + { + txnouttype type; + vector<vector<unsigned char> > vSolutions; + if (Solver(txout.scriptPubKey, type, vSolutions) && + (type == TX_PUBKEY || type == TX_MULTISIG)) + insert(COutPoint(hash, i)); + } + break; + } + } + } + + if (fFound) + return true; + + BOOST_FOREACH(const CTxIn& txin, tx.vin) + { + // Match if the filter contains an outpoint tx spends + if (contains(txin.prevout)) + return true; + + // Match if the filter contains any arbitrary script data element in any scriptSig in tx + CScript::const_iterator pc = txin.scriptSig.begin(); + vector<unsigned char> data; + while (pc < txin.scriptSig.end()) + { + opcodetype opcode; + if (!txin.scriptSig.GetOp(pc, opcode, data)) + break; + if (data.size() != 0 && contains(data)) + return true; + } + } + + return false; +} + +void CBloomFilter::UpdateEmptyFull() +{ + bool full = true; + bool empty = true; + for (unsigned int i = 0; i < vData.size(); i++) + { + full &= vData[i] == 0xff; + empty &= vData[i] == 0; + } + isFull = full; + isEmpty = empty; +} + +CRollingBloomFilter::CRollingBloomFilter(unsigned int nElements, double fpRate) : + b1(nElements * 2, fpRate, 0), b2(nElements * 2, fpRate, 0) +{ + // Implemented using two bloom filters of 2 * nElements each. + // We fill them up, and clear them, staggered, every nElements + // inserted, so at least one always contains the last nElements + // inserted. + nInsertions = 0; + nBloomSize = nElements * 2; + + reset(); +} + +void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey) +{ + if (nInsertions == 0) { + b1.clear(); + } else if (nInsertions == nBloomSize / 2) { + b2.clear(); + } + b1.insert(vKey); + b2.insert(vKey); + if (++nInsertions == nBloomSize) { + nInsertions = 0; + } +} + +void CRollingBloomFilter::insert(const uint256& hash) +{ + vector<unsigned char> data(hash.begin(), hash.end()); + insert(data); +} + +bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const +{ + if (nInsertions < nBloomSize / 2) { + return b2.contains(vKey); + } + return b1.contains(vKey); +} + +bool CRollingBloomFilter::contains(const uint256& hash) const +{ + vector<unsigned char> data(hash.begin(), hash.end()); + return contains(data); +} + +void CRollingBloomFilter::reset() +{ + unsigned int nNewTweak = GetRand(std::numeric_limits<unsigned int>::max()); + b1.reset(nNewTweak); + b2.reset(nNewTweak); + nInsertions = 0; +} |