| /* |
| * Licensed to the Apache Software Foundation (ASF) under one |
| * or more contributor license agreements. See the NOTICE file |
| * distributed with this work for additional information |
| * regarding copyten ownership. The ASF licenses this file |
| * to you under the Apache License, Version 2.0 (the |
| * "License"); you may not use this file except in compliance |
| * with the License. You may obtain a copy of the License at |
| * |
| * http://www.apache.org/licenses/LICENSE-2.0 |
| * |
| * Unless required by applicable law or agreed to in writing, |
| * software distributed under the License is distributed on an |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| * KIND, either express or implied. See the License for the |
| * specific language governing permissions and limitations |
| * under the License. |
| */ |
| package org.apache.cassandra.utils; |
| |
| import java.math.BigInteger; |
| import java.util.*; |
| |
| import com.google.common.collect.Lists; |
| |
| import org.junit.Before; |
| import org.junit.Test; |
| import org.apache.cassandra.config.DatabaseDescriptor; |
| import org.apache.cassandra.dht.IPartitioner; |
| import org.apache.cassandra.dht.RandomPartitioner; |
| import org.apache.cassandra.dht.RandomPartitioner.BigIntegerToken; |
| import org.apache.cassandra.dht.Range; |
| import org.apache.cassandra.dht.Token; |
| import org.apache.cassandra.io.util.DataInputBuffer; |
| import org.apache.cassandra.io.util.DataInputPlus; |
| import org.apache.cassandra.io.util.DataOutputBuffer; |
| import org.apache.cassandra.net.MessagingService; |
| import org.apache.cassandra.utils.MerkleTree.Hashable; |
| import org.apache.cassandra.utils.MerkleTree.RowHash; |
| import org.apache.cassandra.utils.MerkleTree.TreeRange; |
| import org.apache.cassandra.utils.MerkleTree.TreeRangeIterator; |
| |
| import static org.apache.cassandra.utils.MerkleTree.RECOMMENDED_DEPTH; |
| import static org.junit.Assert.*; |
| |
| public class MerkleTreeTest |
| { |
| public static byte[] DUMMY = "blah".getBytes(); |
| |
| /** |
| * If a test assumes that the tree is 8 units wide, then it should set this value |
| * to 8. |
| */ |
| public static BigInteger TOKEN_SCALE = new BigInteger("8"); |
| |
| protected IPartitioner partitioner; |
| protected MerkleTree mt; |
| |
| private Range<Token> fullRange() |
| { |
| return new Range<>(partitioner.getMinimumToken(), partitioner.getMinimumToken()); |
| } |
| |
| @Before |
| public void clear() |
| { |
| TOKEN_SCALE = new BigInteger("8"); |
| partitioner = RandomPartitioner.instance; |
| // TODO need to trickle TokenSerializer |
| DatabaseDescriptor.setPartitionerUnsafe(partitioner); |
| mt = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, Integer.MAX_VALUE); |
| } |
| |
| public static void assertHashEquals(final byte[] left, final byte[] right) |
| { |
| assertHashEquals("", left, right); |
| } |
| |
| public static void assertHashEquals(String message, final byte[] left, final byte[] right) |
| { |
| String lstring = left == null ? "null" : Hex.bytesToHex(left); |
| String rstring = right == null ? "null" : Hex.bytesToHex(right); |
| assertEquals(message, lstring, rstring); |
| } |
| |
| /** |
| * The value returned by this method is affected by TOKEN_SCALE: setting TOKEN_SCALE |
| * to 8 means that passing -1 through 8 for this method will return values mapped |
| * between -1 and Token.MAX_VALUE. |
| */ |
| public static Token tok(int i) |
| { |
| if (i == -1) |
| return new BigIntegerToken(new BigInteger("-1")); |
| BigInteger bint = RandomPartitioner.MAXIMUM.divide(TOKEN_SCALE).multiply(new BigInteger(""+i)); |
| return new BigIntegerToken(bint); |
| } |
| |
| @Test |
| public void testSplit() |
| { |
| // split the range (zero, zero] into: |
| // (zero,four], (four,six], (six,seven] and (seven, zero] |
| mt.split(tok(4)); |
| mt.split(tok(6)); |
| mt.split(tok(7)); |
| |
| assertEquals(4, mt.size()); |
| assertEquals(new Range<>(tok(7), tok(-1)), mt.get(tok(-1))); |
| assertEquals(new Range<>(tok(-1), tok(4)), mt.get(tok(3))); |
| assertEquals(new Range<>(tok(-1), tok(4)), mt.get(tok(4))); |
| assertEquals(new Range<>(tok(4), tok(6)), mt.get(tok(6))); |
| assertEquals(new Range<>(tok(6), tok(7)), mt.get(tok(7))); |
| |
| // check depths |
| assertEquals((byte)1, mt.get(tok(4)).depth); |
| assertEquals((byte)2, mt.get(tok(6)).depth); |
| assertEquals((byte)3, mt.get(tok(7)).depth); |
| assertEquals((byte)3, mt.get(tok(-1)).depth); |
| |
| try |
| { |
| mt.split(tok(-1)); |
| fail("Shouldn't be able to split outside the initial range."); |
| } |
| catch (AssertionError e) |
| { |
| // pass |
| } |
| } |
| |
| @Test |
| public void testSplitLimitDepth() |
| { |
| mt = new MerkleTree(partitioner, fullRange(), (byte)2, Integer.MAX_VALUE); |
| |
| assertTrue(mt.split(tok(4))); |
| assertTrue(mt.split(tok(2))); |
| assertEquals(3, mt.size()); |
| |
| // should fail to split below hashdepth |
| assertFalse(mt.split(tok(1))); |
| assertEquals(3, mt.size()); |
| assertEquals(new Range<>(tok(4), tok(-1)), mt.get(tok(-1))); |
| assertEquals(new Range<>(tok(-1), tok(2)), mt.get(tok(2))); |
| assertEquals(new Range<>(tok(2), tok(4)), mt.get(tok(4))); |
| } |
| |
| @Test |
| public void testSplitLimitSize() |
| { |
| mt = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, 2); |
| |
| assertTrue(mt.split(tok(4))); |
| assertEquals(2, mt.size()); |
| |
| // should fail to split above maxsize |
| assertFalse(mt.split(tok(2))); |
| assertEquals(2, mt.size()); |
| assertEquals(new Range<>(tok(4), tok(-1)), mt.get(tok(-1))); |
| assertEquals(new Range<>(tok(-1), tok(4)), mt.get(tok(4))); |
| } |
| |
| @Test |
| public void testInvalids() |
| { |
| Iterator<TreeRange> ranges; |
| |
| // (zero, zero] |
| ranges = mt.invalids(); |
| assertEquals(new Range<>(tok(-1), tok(-1)), ranges.next()); |
| assertFalse(ranges.hasNext()); |
| |
| // all invalid |
| mt.split(tok(4)); |
| mt.split(tok(2)); |
| mt.split(tok(6)); |
| mt.split(tok(3)); |
| mt.split(tok(5)); |
| ranges = mt.invalids(); |
| assertEquals(new Range<>(tok(6), tok(-1)), ranges.next()); |
| assertEquals(new Range<>(tok(-1), tok(2)), ranges.next()); |
| assertEquals(new Range<>(tok(2), tok(3)), ranges.next()); |
| assertEquals(new Range<>(tok(3), tok(4)), ranges.next()); |
| assertEquals(new Range<>(tok(4), tok(5)), ranges.next()); |
| assertEquals(new Range<>(tok(5), tok(6)), ranges.next()); |
| assertEquals(new Range<>(tok(6), tok(-1)), ranges.next()); |
| assertFalse(ranges.hasNext()); |
| } |
| |
| |
| @Test |
| public void testHashFull() |
| { |
| byte[] val = DUMMY; |
| Range<Token> range = new Range<>(tok(-1), tok(-1)); |
| |
| // (zero, zero] |
| assertNull(mt.hash(range)); |
| |
| // validate the range |
| mt.get(tok(-1)).hash(val); |
| |
| assertHashEquals(val, mt.hash(range)); |
| } |
| |
| @Test |
| public void testHashPartial() |
| { |
| byte[] val = DUMMY; |
| byte[] leftval = hashed(val, 1, 1); |
| byte[] partialval = hashed(val, 1); |
| Range<Token> left = new Range<>(tok(-1), tok(4)); |
| Range<Token> partial = new Range<>(tok(2), tok(4)); |
| Range<Token> right = new Range<>(tok(4), tok(-1)); |
| Range<Token> linvalid = new Range<>(tok(1), tok(4)); |
| Range<Token> rinvalid = new Range<>(tok(4), tok(6)); |
| |
| // (zero,two] (two,four] (four, zero] |
| mt.split(tok(4)); |
| mt.split(tok(2)); |
| assertNull(mt.hash(left)); |
| assertNull(mt.hash(partial)); |
| assertNull(mt.hash(right)); |
| assertNull(mt.hash(linvalid)); |
| assertNull(mt.hash(rinvalid)); |
| |
| // validate the range |
| mt.get(tok(2)).hash(val); |
| mt.get(tok(4)).hash(val); |
| mt.get(tok(-1)).hash(val); |
| |
| assertHashEquals(leftval, mt.hash(left)); |
| assertHashEquals(partialval, mt.hash(partial)); |
| assertHashEquals(val, mt.hash(right)); |
| assertNull(mt.hash(linvalid)); |
| assertNull(mt.hash(rinvalid)); |
| } |
| |
| @Test |
| public void testHashInner() |
| { |
| byte[] val = DUMMY; |
| byte[] lchildval = hashed(val, 3, 3, 2); |
| byte[] rchildval = hashed(val, 2, 2); |
| byte[] fullval = hashed(val, 3, 3, 2, 2, 2); |
| Range<Token> full = new Range<>(tok(-1), tok(-1)); |
| Range<Token> lchild = new Range<>(tok(-1), tok(4)); |
| Range<Token> rchild = new Range<>(tok(4), tok(-1)); |
| Range<Token> invalid = new Range<>(tok(1), tok(-1)); |
| |
| // (zero,one] (one, two] (two,four] (four, six] (six, zero] |
| mt.split(tok(4)); |
| mt.split(tok(2)); |
| mt.split(tok(6)); |
| mt.split(tok(1)); |
| assertNull(mt.hash(full)); |
| assertNull(mt.hash(lchild)); |
| assertNull(mt.hash(rchild)); |
| assertNull(mt.hash(invalid)); |
| |
| // validate the range |
| mt.get(tok(1)).hash(val); |
| mt.get(tok(2)).hash(val); |
| mt.get(tok(4)).hash(val); |
| mt.get(tok(6)).hash(val); |
| mt.get(tok(-1)).hash(val); |
| |
| assertHashEquals(fullval, mt.hash(full)); |
| assertHashEquals(lchildval, mt.hash(lchild)); |
| assertHashEquals(rchildval, mt.hash(rchild)); |
| assertNull(mt.hash(invalid)); |
| } |
| |
| @Test |
| public void testHashDegenerate() |
| { |
| TOKEN_SCALE = new BigInteger("32"); |
| |
| byte[] val = DUMMY; |
| byte[] childfullval = hashed(val, 5, 5, 4); |
| byte[] fullval = hashed(val, 5, 5, 4, 3, 2, 1); |
| Range<Token> childfull = new Range<>(tok(-1), tok(4)); |
| Range<Token> full = new Range<>(tok(-1), tok(-1)); |
| Range<Token> invalid = new Range<>(tok(4), tok(-1)); |
| |
| mt = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, Integer.MAX_VALUE); |
| mt.split(tok(16)); |
| mt.split(tok(8)); |
| mt.split(tok(4)); |
| mt.split(tok(2)); |
| mt.split(tok(1)); |
| assertNull(mt.hash(full)); |
| assertNull(mt.hash(childfull)); |
| assertNull(mt.hash(invalid)); |
| |
| // validate the range |
| mt.get(tok(1)).hash(val); |
| mt.get(tok(2)).hash(val); |
| mt.get(tok(4)).hash(val); |
| mt.get(tok(8)).hash(val); |
| mt.get(tok(16)).hash(val); |
| mt.get(tok(-1)).hash(val); |
| |
| assertHashEquals(fullval, mt.hash(full)); |
| assertHashEquals(childfullval, mt.hash(childfull)); |
| assertNull(mt.hash(invalid)); |
| } |
| |
| @Test |
| public void testHashRandom() |
| { |
| int max = 1000000; |
| TOKEN_SCALE = new BigInteger("" + max); |
| |
| mt = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, 32); |
| Random random = new Random(); |
| while (true) |
| { |
| if (!mt.split(tok(random.nextInt(max)))) |
| break; |
| } |
| |
| // validate the tree |
| TreeRangeIterator ranges = mt.invalids(); |
| for (TreeRange range : ranges) |
| range.addHash(new RowHash(range.right, new byte[0], 0)); |
| |
| assert mt.hash(new Range<>(tok(-1), tok(-1))) != null : |
| "Could not hash tree " + mt; |
| } |
| |
| /** |
| * Generate two trees with different splits, but containing the same keys, and |
| * check that they compare equally. |
| * |
| * The set of keys used in this test is: #{2,4,6,8,12,14,0} |
| */ |
| @Test |
| public void testValidateTree() |
| { |
| TOKEN_SCALE = new BigInteger("16"); // this test needs slightly more resolution |
| |
| Range<Token> full = new Range<>(tok(-1), tok(-1)); |
| Iterator<TreeRange> ranges; |
| MerkleTree mt2 = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, Integer.MAX_VALUE); |
| |
| mt.split(tok(8)); |
| mt.split(tok(4)); |
| mt.split(tok(12)); |
| mt.split(tok(6)); |
| mt.split(tok(10)); |
| |
| ranges = mt.invalids(); |
| ranges.next().addAll(new HIterator(2, 4)); // (-1,4]: depth 2 |
| ranges.next().addAll(new HIterator(6)); // (4,6] |
| ranges.next().addAll(new HIterator(8)); // (6,8] |
| ranges.next().addAll(new HIterator(/*empty*/ new int[0])); // (8,10] |
| ranges.next().addAll(new HIterator(12)); // (10,12] |
| ranges.next().addAll(new HIterator(14, -1)); // (12,-1]: depth 2 |
| |
| |
| mt2.split(tok(8)); |
| mt2.split(tok(4)); |
| mt2.split(tok(12)); |
| mt2.split(tok(2)); |
| mt2.split(tok(10)); |
| mt2.split(tok(9)); |
| mt2.split(tok(11)); |
| |
| ranges = mt2.invalids(); |
| ranges.next().addAll(new HIterator(2)); // (-1,2] |
| ranges.next().addAll(new HIterator(4)); // (2,4] |
| ranges.next().addAll(new HIterator(6, 8)); // (4,8]: depth 2 |
| ranges.next().addAll(new HIterator(/*empty*/ new int[0])); // (8,9] |
| ranges.next().addAll(new HIterator(/*empty*/ new int[0])); // (9,10] |
| ranges.next().addAll(new HIterator(/*empty*/ new int[0])); // (10,11]: depth 4 |
| ranges.next().addAll(new HIterator(12)); // (11,12]: depth 4 |
| ranges.next().addAll(new HIterator(14, -1)); // (12,-1]: depth 2 |
| |
| byte[] mthash = mt.hash(full); |
| byte[] mt2hash = mt2.hash(full); |
| assertHashEquals("Tree hashes did not match: " + mt + " && " + mt2, mthash, mt2hash); |
| } |
| |
| @Test |
| public void testSerialization() throws Exception |
| { |
| Range<Token> full = new Range<>(tok(-1), tok(-1)); |
| |
| // populate and validate the tree |
| mt.maxsize(256); |
| mt.init(); |
| for (TreeRange range : mt.invalids()) |
| range.addAll(new HIterator(range.right)); |
| |
| byte[] initialhash = mt.hash(full); |
| |
| DataOutputBuffer out = new DataOutputBuffer(); |
| MerkleTree.serializer.serialize(mt, out, MessagingService.current_version); |
| byte[] serialized = out.toByteArray(); |
| |
| DataInputPlus in = new DataInputBuffer(serialized); |
| MerkleTree restored = MerkleTree.serializer.deserialize(in, MessagingService.current_version); |
| |
| assertHashEquals(initialhash, restored.hash(full)); |
| } |
| |
| @Test |
| public void testDifference() |
| { |
| int maxsize = 16; |
| mt.maxsize(maxsize); |
| MerkleTree mt2 = new MerkleTree(partitioner, fullRange(), RECOMMENDED_DEPTH, maxsize); |
| mt.init(); |
| mt2.init(); |
| |
| // add dummy hashes to both trees |
| for (TreeRange range : mt.invalids()) |
| range.addAll(new HIterator(range.right)); |
| for (TreeRange range : mt2.invalids()) |
| range.addAll(new HIterator(range.right)); |
| |
| TreeRange leftmost = null; |
| TreeRange middle = null; |
| |
| mt.maxsize(maxsize + 2); // give some room for splitting |
| |
| // split the leftmost |
| Iterator<TreeRange> ranges = mt.invalids(); |
| leftmost = ranges.next(); |
| mt.split(leftmost.right); |
| |
| // set the hashes for the leaf of the created split |
| middle = mt.get(leftmost.right); |
| middle.hash("arbitrary!".getBytes()); |
| mt.get(partitioner.midpoint(leftmost.left, leftmost.right)).hash("even more arbitrary!".getBytes()); |
| |
| // trees should disagree for (leftmost.left, middle.right] |
| List<TreeRange> diffs = MerkleTree.difference(mt, mt2); |
| assertEquals(diffs + " contains wrong number of differences:", 1, diffs.size()); |
| assertTrue(diffs.contains(new Range<>(leftmost.left, middle.right))); |
| } |
| |
| /** |
| * difference should behave as expected, even with extremely small ranges |
| */ |
| @Test |
| public void differenceSmallRange() |
| { |
| Token start = new BigIntegerToken("9"); |
| Token end = new BigIntegerToken("10"); |
| Range<Token> range = new Range<>(start, end); |
| |
| MerkleTree ltree = new MerkleTree(partitioner, range, RECOMMENDED_DEPTH, 16); |
| ltree.init(); |
| MerkleTree rtree = new MerkleTree(partitioner, range, RECOMMENDED_DEPTH, 16); |
| rtree.init(); |
| |
| byte[] h1 = "asdf".getBytes(); |
| byte[] h2 = "hjkl".getBytes(); |
| |
| // add dummy hashes to both trees |
| for (TreeRange tree : ltree.invalids()) |
| { |
| tree.addHash(new RowHash(range.right, h1, h1.length)); |
| } |
| for (TreeRange tree : rtree.invalids()) |
| { |
| tree.addHash(new RowHash(range.right, h2, h2.length)); |
| } |
| |
| List<TreeRange> diffs = MerkleTree.difference(ltree, rtree); |
| assertEquals(Lists.newArrayList(range), diffs); |
| assertEquals(MerkleTree.FULLY_INCONSISTENT, MerkleTree.differenceHelper(ltree, rtree, new ArrayList<>(), new MerkleTree.TreeDifference(ltree.fullRange.left, ltree.fullRange.right, (byte)0))); |
| } |
| |
| /** |
| * matching should behave as expected, even with extremely small ranges |
| */ |
| @Test |
| public void matchingSmallRange() |
| { |
| Token start = new BigIntegerToken("9"); |
| Token end = new BigIntegerToken("10"); |
| Range<Token> range = new Range<>(start, end); |
| |
| MerkleTree ltree = new MerkleTree(partitioner, range, RECOMMENDED_DEPTH, 16); |
| ltree.init(); |
| MerkleTree rtree = new MerkleTree(partitioner, range, RECOMMENDED_DEPTH, 16); |
| rtree.init(); |
| |
| byte[] h1 = "asdf".getBytes(); |
| byte[] h2 = "asdf".getBytes(); |
| |
| |
| // add dummy hashes to both trees |
| for (TreeRange tree : ltree.invalids()) |
| { |
| tree.addHash(new RowHash(range.right, h1, h1.length)); |
| } |
| for (TreeRange tree : rtree.invalids()) |
| { |
| tree.addHash(new RowHash(range.right, h2, h2.length)); |
| } |
| |
| // top level difference() should show no differences |
| assertEquals(MerkleTree.difference(ltree, rtree), Lists.newArrayList()); |
| } |
| |
| /** |
| * Return the root hash of a binary tree with leaves at the given depths |
| * and with the given hash val in each leaf. |
| */ |
| byte[] hashed(byte[] val, Integer... depths) |
| { |
| ArrayDeque<Integer> dstack = new ArrayDeque<Integer>(); |
| ArrayDeque<byte[]> hstack = new ArrayDeque<byte[]>(); |
| Iterator<Integer> depthiter = Arrays.asList(depths).iterator(); |
| if (depthiter.hasNext()) |
| { |
| dstack.push(depthiter.next()); |
| hstack.push(val); |
| } |
| while (depthiter.hasNext()) |
| { |
| Integer depth = depthiter.next(); |
| byte[] hash = val; |
| while (depth.equals(dstack.peek())) |
| { |
| // consume the stack |
| hash = Hashable.binaryHash(hstack.pop(), hash); |
| depth = dstack.pop()-1; |
| } |
| dstack.push(depth); |
| hstack.push(hash); |
| } |
| assert hstack.size() == 1; |
| return hstack.pop(); |
| } |
| |
| static class HIterator extends AbstractIterator<RowHash> |
| { |
| private Iterator<Token> tokens; |
| |
| public HIterator(int... tokens) |
| { |
| List<Token> tlist = new LinkedList<Token>(); |
| for (int token : tokens) |
| tlist.add(tok(token)); |
| this.tokens = tlist.iterator(); |
| } |
| |
| public HIterator(Token... tokens) |
| { |
| this.tokens = Arrays.asList(tokens).iterator(); |
| } |
| |
| public RowHash computeNext() |
| { |
| if (tokens.hasNext()) |
| return new RowHash(tokens.next(), DUMMY, DUMMY.length); |
| return endOfData(); |
| } |
| } |
| } |