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BloomFilter: javadoc updates

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Mike Hearn 2014-03-26 20:04:32 +01:00
parent a22cc7f698
commit a31010b379
1 changed files with 19 additions and 23 deletions
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42
core/src/main/java/com/google/bitcoin/core/BloomFilter.java
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@ -70,25 +70,20 @@ public class BloomFilter extends Message {
} }
/** /**
* <p>Constructs a new Bloom Filter which will provide approximately the given false positive * <p>Constructs a new Bloom Filter which will provide approximately the given false positive rate when the given
* rate when the given number of elements have been inserted.</p> * number of elements have been inserted. If the filter would otherwise be larger than the maximum allowed size,
* it will be automatically downsized to the maximum size.</p>
* *
* <p>If the filter would otherwise be larger than the maximum allowed size, it will be * <p>To check the theoretical false positive rate of a given filter, use
* automatically downsized to the maximum size.</p> * {@link BloomFilter#getFalsePositiveRate(int)}.</p>
* *
* <p>To check the theoretical false positive rate of a given filter, use {@link BloomFilter#getFalsePositiveRate(int)}</p> * <p>The anonymity of which coins are yours to any peer which you send a BloomFilter to is controlled by the
* * false positive rate. For reference, as of block 187,000, the total number of addresses used in the chain was
* <p>The anonymity of which coins are yours to any peer which you send a BloomFilter to is * roughly 4.5 million. Thus, if you use a false positive rate of 0.001 (0.1%), there will be, on average, 4,500
* controlled by the false positive rate.</p> * distinct public keys/addresses which will be thought to be yours by nodes which have your bloom filter, but
* * which are not actually yours. Keep in mind that a remote node can do a pretty good job estimating the order of
* <p>For reference, as of block 187,000, the total number of addresses used in the chain was roughly 4.5 million.</p> * magnitude of the false positive rate of a given filter you provide it when considering the anonymity of a given
* * filter.</p>
* <p>Thus, if you use a false positive rate of 0.001 (0.1%), there will be, on average, 4,500 distinct public
* keys/addresses which will be thought to be yours by nodes which have your bloom filter, but which are not
* actually yours.</p>
*
* <p>Keep in mind that a remote node can do a pretty good job estimating the order of magnitude of the false positive
* rate of a given filter you provide it when considering the anonymity of a given filter.</p>
* *
* <p>In order for filtered block download to function efficiently, the number of matched transactions in any given * <p>In order for filtered block download to function efficiently, the number of matched transactions in any given
* block should be less than (with some headroom) the maximum size of the MemoryPool used by the Peer * block should be less than (with some headroom) the maximum size of the MemoryPool used by the Peer
@ -98,7 +93,10 @@ public class BloomFilter extends Message {
* <p>randomNonce is a tweak for the hash function used to prevent some theoretical DoS attacks. * <p>randomNonce is a tweak for the hash function used to prevent some theoretical DoS attacks.
* It should be a random value, however secureness of the random value is of no great consequence.</p> * It should be a random value, however secureness of the random value is of no great consequence.</p>
* *
* <p>updateFlag is used to control filter behavior</p> * <p>updateFlag is used to control filter behaviour on the server (remote node) side when it encounters a hit.
* See {@link com.google.bitcoin.core.BloomFilter.BloomUpdate} for a brief description of each mode. The purpose
* of this flag is to reduce network round-tripping and avoid over-dirtying the filter for the most common
* wallet configurations.</p>
*/ */
public BloomFilter(int elements, double falsePositiveRate, long randomNonce, BloomUpdate updateFlag) { public BloomFilter(int elements, double falsePositiveRate, long randomNonce, BloomUpdate updateFlag) {
// The following formulas were stolen from Wikipedia's page on Bloom Filters (with the addition of min(..., MAX_...)) // The following formulas were stolen from Wikipedia's page on Bloom Filters (with the addition of min(..., MAX_...))
@ -210,8 +208,8 @@ public class BloomFilter extends Message {
} }
/** /**
* Returns true if the given object matches the filter * Returns true if the given object matches the filter either because it was inserted, or because we have a
* (either because it was inserted, or because we have a false-positive) * false-positive.
*/ */
public boolean contains(byte[] object) { public boolean contains(byte[] object) {
for (int i = 0; i < hashFuncs; i++) { for (int i = 0; i < hashFuncs; i++) {
@ -221,9 +219,7 @@ public class BloomFilter extends Message {
return true; return true;
} }
/** /** Insert the given arbitrary data into the filter */
* Insert the given arbitrary data into the filter
*/
public void insert(byte[] object) { public void insert(byte[] object) {
for (int i = 0; i < hashFuncs; i++) for (int i = 0; i < hashFuncs; i++)
Utils.setBitLE(data, hash(i, object)); Utils.setBitLE(data, hash(i, object));