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