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lbrycrd/src/bloom.cpp
Robert McLaughlin cccf73db04 trivial: fix bloom filter init to isEmpty = true 
Fixes newly initialized bloom filters being
constructed with isEmpty(false), which still
works but loses the possible speedup when
checking for key membership in an empty filter.
2016-11-01 21:04:26 -04:00

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// Copyright (c) 2012-2015 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(true),
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)
{
double logFpRate = log(fpRate);
/* The optimal number of hash functions is log(fpRate) / log(0.5), but
* restrict it to the range 1-50. */
nHashFuncs = std::max(1, std::min((int)round(logFpRate / log(0.5)), 50));
/* In this rolling bloom filter, we'll store between 2 and 3 generations of nElements / 2 entries. */
nEntriesPerGeneration = (nElements + 1) / 2;
uint32_t nMaxElements = nEntriesPerGeneration * 3;
/* The maximum fpRate = pow(1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits), nHashFuncs)
* => pow(fpRate, 1.0 / nHashFuncs) = 1.0 - exp(-nHashFuncs * nMaxElements / nFilterBits)
* => 1.0 - pow(fpRate, 1.0 / nHashFuncs) = exp(-nHashFuncs * nMaxElements / nFilterBits)
* => log(1.0 - pow(fpRate, 1.0 / nHashFuncs)) = -nHashFuncs * nMaxElements / nFilterBits
* => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - pow(fpRate, 1.0 / nHashFuncs))
* => nFilterBits = -nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs))
*/
uint32_t nFilterBits = (uint32_t)ceil(-1.0 * nHashFuncs * nMaxElements / log(1.0 - exp(logFpRate / nHashFuncs)));
data.clear();
/* For each data element we need to store 2 bits. If both bits are 0, the
* bit is treated as unset. If the bits are (01), (10), or (11), the bit is
* treated as set in generation 1, 2, or 3 respectively.
* These bits are stored in separate integers: position P corresponds to bit
* (P & 63) of the integers data[(P >> 6) * 2] and data[(P >> 6) * 2 + 1]. */
data.resize(((nFilterBits + 63) / 64) << 1);
reset();
}
/* Similar to CBloomFilter::Hash */
static inline uint32_t RollingBloomHash(unsigned int nHashNum, uint32_t nTweak, const std::vector<unsigned char>& vDataToHash) {
return MurmurHash3(nHashNum * 0xFBA4C795 + nTweak, vDataToHash);
}
void CRollingBloomFilter::insert(const std::vector<unsigned char>& vKey)
{
if (nEntriesThisGeneration == nEntriesPerGeneration) {
nEntriesThisGeneration = 0;
nGeneration++;
if (nGeneration == 4) {
nGeneration = 1;
}
uint64_t nGenerationMask1 = -(uint64_t)(nGeneration & 1);
uint64_t nGenerationMask2 = -(uint64_t)(nGeneration >> 1);
/* Wipe old entries that used this generation number. */
for (uint32_t p = 0; p < data.size(); p += 2) {
uint64_t p1 = data[p], p2 = data[p + 1];
uint64_t mask = (p1 ^ nGenerationMask1) | (p2 ^ nGenerationMask2);
data[p] = p1 & mask;
data[p + 1] = p2 & mask;
}
}
nEntriesThisGeneration++;
for (int n = 0; n < nHashFuncs; n++) {
uint32_t h = RollingBloomHash(n, nTweak, vKey);
int bit = h & 0x3F;
uint32_t pos = (h >> 6) % data.size();
/* The lowest bit of pos is ignored, and set to zero for the first bit, and to one for the second. */
data[pos & ~1] = (data[pos & ~1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration & 1)) << bit;
data[pos | 1] = (data[pos | 1] & ~(((uint64_t)1) << bit)) | ((uint64_t)(nGeneration >> 1)) << bit;
}
}
void CRollingBloomFilter::insert(const uint256& hash)
{
vector<unsigned char> vData(hash.begin(), hash.end());
insert(vData);
}
bool CRollingBloomFilter::contains(const std::vector<unsigned char>& vKey) const
{
for (int n = 0; n < nHashFuncs; n++) {
uint32_t h = RollingBloomHash(n, nTweak, vKey);
int bit = h & 0x3F;
uint32_t pos = (h >> 6) % data.size();
/* If the relevant bit is not set in either data[pos & ~1] or data[pos | 1], the filter does not contain vKey */
if (!(((data[pos & ~1] | data[pos | 1]) >> bit) & 1)) {
return false;
}
}
return true;
}
bool CRollingBloomFilter::contains(const uint256& hash) const
{
vector<unsigned char> vData(hash.begin(), hash.end());
return contains(vData);
}
void CRollingBloomFilter::reset()
{
nTweak = GetRand(std::numeric_limits<unsigned int>::max());
nEntriesThisGeneration = 0;
nGeneration = 1;
for (std::vector<uint64_t>::iterator it = data.begin(); it != data.end(); it++) {
*it = 0;
}
}
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