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249 lines
9.1 KiB
249 lines
9.1 KiB
// kelondroHashtable.java
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// ------------------
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// part of the Kelondro Database
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// (C) by Michael Peter Christen; mc@yacy.net
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// first published on http://www.anomic.de
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// Frankfurt, Germany, 2005
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// last major change: 21.06.2005
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//
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// This program is free software; you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation; either version 2 of the License, or
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// (at your option) any later version.
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//
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// This program is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with this program; if not, write to the Free Software
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// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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/*
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we implement a hashtable based on folded binary trees
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each hight in these binary trees represents one step of rehasing
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the re-hashing is realised by extending the number of relevant bits in the given hash
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We construct the binary tree as follows
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- there exists no root node
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- at height-1 are 2 nodes, and can be accessed by using only the least significant bit of the hash
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- at height-2 are 4 nodes, addresses by (hash & 3) - mapping the 2 lsb of the hash
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- at height-3 are 8 nodes, addresses by (hash & 7)
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- .. and so on.
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The number of nodes N(k) that are needed for a tree of height-k is
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N(k) = 2**k + N(k-1) = 2**(k + 1) - 2 [where k > 0]
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We fold this tree by putting all heights of the tree in a sequence
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Computation of the position (the index) of a node:
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given:
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hash h, with k significant bits (representing a height-k): h|k
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then the position of a node node(h,k) is
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node(h,k) = N(k - 1) + h|k [where k > 0]
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We use these nodes to sequentially store a hash h at position node(h, 1), and
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if that fails on node(h, 2), node(h, 3) and so on.
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This is highly inefficient for the most heights k = 1, ..., (?)
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The 'inefficient-border' depends on the number of elements that we want to store.
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We therefore introduce an offset o which is the number of bits that are not used
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at the beginning of (re-)hashing. But even if these o re-hasing steps are not done,
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all bits of the hash are relevant.
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Now the number of nodes N(k) that are needed is computed by N(k,o):
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N(k,o) = N(k) - N(o) = 2**(k + 1) - 2**(o + 1) [where k > o, o >= 0]
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When o=0 then this is equivalent to N(k).
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The node-formula must be adopted as well
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node(h,k,o) = N(k - 1, o) + h|k [where k > o, o >= 0]
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So if you set an offset o, this leads to a minimum number of nodes
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at level k=o+1: node(0,o + 1,o) = N(o, o) = 0 (position of the first entry)
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Computatiion of the maxlen 'maxk', the maximum height of the tree for a given
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number of maximum entries 'maxsize' in the hashtable:
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maxk shall be computed in such a way, that N(k,o) <= maxsize, for any o or k
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This means paricualary, that
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node(h,k,o) < maxsize
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for h|k we must consider the worst case:
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h|k (by maxk) = 2**k - 1
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therefore
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node(h,maxk,o) < maxsize
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N(maxk - 1, o) + h|maxk < maxsize [where maxk > o, o >= 0]
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2**maxk - 2**(o + 1) + 2**maxk - 1 < maxsize [where maxk > o, o >= 0]
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2**maxk - 2**(o + 1) + 2**maxk < maxsize + 1 [where maxk > o, o >= 0]
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2**maxk + 2**maxk < maxsize + 2**(o + 1) + 1 [where maxk > o, o >= 0]
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2**(maxk+1) < maxsize + 2**(o + 1) + 1 [where maxk > o, o >= 0]
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maxk < log2(maxsize + 2**(o + 1) + 1) [where maxk > o, o >= 0]
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setting maxk to
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maxk = log2(maxsize)
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will make this relation true in any case, even if maxk = log2(maxsize) + 1
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would also be correct in some cases
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Now we can use the following formula to create the folded binary hash tree:
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node(h,k,o) = 2**k - 2**(o + 1) + h|k
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to compute the node index and
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maxk = log2(maxsize)
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to compute the upper limit of re-hashing
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*/
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package de.anomic.kelondro;
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import java.io.File;
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import java.io.IOException;
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public class kelondroHashtable {
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private final kelondroFixedWidthArray hashArray;
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protected int offset;
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protected int maxk;
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private int maxrehash;
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private kelondroRow.Entry dummyRow;
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private static final byte[] dummyKey = kelondroBase64Order.enhancedCoder.encodeLong(0, 5).getBytes();
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public kelondroHashtable(final File file, final kelondroRow rowdef, final int offset, final int maxsize, final int maxrehash) throws IOException {
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// this creates a new hashtable
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// the key element is not part of the columns array
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// this is unlike the kelondroTree, where the key is part of a row
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// the offset is a number of bits that is omitted in the folded tree hierarchy
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// a good number for offset is 8
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// the maxsize number is the maximum number of elements in the hashtable
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// this number is needed to omit grow of the table in case of re-hashing
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// the maxsize is re-computed to a virtual folding height and will result in a tablesize
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// less than the given maxsize. The actual maxsize can be retrieved by maxsize()
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final boolean fileExisted = file.exists();
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this.hashArray = new kelondroFixedWidthArray(file, extCol(rowdef), 6);
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if (fileExisted) {
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this.offset = hashArray.geti(0);
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this.maxk = hashArray.geti(1);
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this.maxrehash = hashArray.geti(2);
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} else {
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this.offset = offset;
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this.maxk = kelondroMSetTools.log2a(maxsize); // equal to |log2(maxsize)| + 1
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if (this.maxk >= kelondroMSetTools.log2a(maxsize + power2(offset + 1) + 1) - 1) this.maxk--;
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this.maxrehash = maxrehash;
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dummyRow = this.hashArray.row().newEntry();
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dummyRow.setCol(0, dummyKey);
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//for (int i = 0; i < hashArray.row().columns(); i++)
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hashArray.seti(0, this.offset);
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hashArray.seti(1, this.maxk);
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hashArray.seti(2, this.maxrehash);
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}
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}
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private kelondroRow extCol(final kelondroRow rowdef) {
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final kelondroColumn[] newCol = new kelondroColumn[rowdef.columns() + 1];
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newCol[0] = new kelondroColumn("Cardinal key-4 {b256}");
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for (int i = 0; i < rowdef.columns(); i++) newCol[i + 1] = rowdef.column(i);
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return new kelondroRow(newCol, rowdef.objectOrder, rowdef.primaryKeyIndex);
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}
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public static int power2(int x) {
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int p = 1;
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while (x > 0) {p = p << 1; x--;}
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return p;
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}
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public synchronized byte[][] get(final int key) throws IOException {
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final Object[] search = search(new Hash(key));
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if (search[1] == null) return null;
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final byte[][] row = (byte[][]) search[1];
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final byte[][] result = new byte[row.length - 1][];
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System.arraycopy(row, 1, result, 0, row.length - 1);
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return result;
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}
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public synchronized kelondroRow.Entry put(final int key, final kelondroRow.Entry rowentry) throws IOException {
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final Hash hash = new Hash(key);
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// find row
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final Object[] search = search(hash);
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kelondroRow.Entry oldhkrow;
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final int rowNumber = ((Integer) search[0]).intValue();
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if (search[1] == null) {
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oldhkrow = null;
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} else {
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oldhkrow = (kelondroRow.Entry) search[1];
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}
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// make space
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while (rowNumber >= hashArray.size()) hashArray.set(hashArray.size(), dummyRow);
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// write row
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final kelondroRow.Entry newhkrow = hashArray.row().newEntry();
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newhkrow.setCol(0, hash.key());
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newhkrow.setCol(1, rowentry.bytes());
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hashArray.set(rowNumber, newhkrow);
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return (oldhkrow == null ? null : hashArray.row().newEntry(oldhkrow.getColBytes(1)));
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}
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private Object[] search(final Hash hash) throws IOException {
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kelondroRow.Entry hkrow;
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int rowKey;
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int rowNumber;
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do {
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rowNumber = hash.node();
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if (rowNumber >= hashArray.size()) return new Object[]{new Integer(rowNumber), null};
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hkrow = hashArray.get(rowNumber);
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rowKey = (int) hkrow.getColLong(0);
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if (rowKey == 0) return new Object[]{new Integer(rowNumber), null};
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hash.rehash();
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} while (rowKey != hash.key());
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return new Object[]{new Integer(rowNumber), hkrow};
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}
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private class Hash {
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int key;
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int hash;
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int depth;
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public Hash(final int key) {
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this.key = key;
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this.hash = key;
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this.depth = offset + 1;
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}
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public int key() {
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return key;
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}
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private int hash() {
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return hash & (power2(depth) - 1); // apply mask
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}
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public int depth() {
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return depth;
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}
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public void rehash() {
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depth++;
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if (depth > maxk) {
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depth = offset + 1;
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hash = (int) ((5 * (long) hash - 7) / 3 + 13);
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}
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}
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public int node() {
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// node(h,k,o) = 2**k - 2**(o + 1) + h|k
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return power2(depth) - power2(offset + 1) + hash();
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}
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}
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}
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