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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.

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/*
 * 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 copyright 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
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package org.apache.cassandra.utils.btree;

import java.util.Comparator;

import io.netty.util.Recycler;

import static org.apache.cassandra.utils.btree.BTree.EMPTY_LEAF;
import static org.apache.cassandra.utils.btree.BTree.FAN_SHIFT;
import static org.apache.cassandra.utils.btree.BTree.POSITIVE_INFINITY;

/**
 * A class for constructing a new BTree, either from an existing one and some set of modifications
 * or a new tree from a sorted collection of items.
 * 

* This is a fairly heavy-weight object, so a Recycled instance is created for making modifications to a tree */ final class TreeBuilder { private final static Recycler builderRecycler = new Recycler() { protected TreeBuilder newObject(Handle handle) { return new TreeBuilder(handle); } }; public static TreeBuilder newInstance() { return builderRecycler.get(); } private final Recycler.Handle recycleHandle; private final NodeBuilder rootBuilder = new NodeBuilder(); private TreeBuilder(Recycler.Handle handle) { this.recycleHandle = handle; } /** * At the highest level, we adhere to the classic b-tree insertion algorithm: * * 1. Add to the appropriate leaf * 2. Split the leaf if necessary, add the median to the parent * 3. Split the parent if necessary, etc. * * There is one important difference: we don't actually modify the original tree, but copy each node that we * modify. Note that every node on the path to the key being inserted or updated will be modified; this * implies that at a minimum, the root node will be modified for every update, so every root is a "snapshot" * of a tree that can be iterated or sliced without fear of concurrent modifications. * * The NodeBuilder class handles the details of buffering the copied contents of the original tree and * adding in our changes. Since NodeBuilder maintains parent/child references, it also handles parent-splitting * (easy enough, since any node affected by the split will already be copied into a NodeBuilder). * * One other difference from the simple algorithm is that we perform modifications in bulk; * we assume @param source has been sorted, e.g. by BTree.update, so the update of each key resumes where * the previous left off. */ public Object[] update(Object[] btree, Comparator comparator, Iterable source, UpdateFunction updateF) { assert updateF != null; NodeBuilder current = rootBuilder; current.reset(btree, POSITIVE_INFINITY, updateF, comparator); for (K key : source) { while (true) { if (updateF.abortEarly()) { rootBuilder.clear(); return null; } NodeBuilder next = current.update(key); if (next == null) break; // we were in a subtree from a previous key that didn't contain this new key; // retry against the correct subtree current = next; } } // finish copying any remaining keys from the original btree while (true) { NodeBuilder next = current.finish(); if (next == null) break; current = next; } // updating with POSITIVE_INFINITY means that current should be back to the root assert current.isRoot(); Object[] r = current.toNode(); current.clear(); builderRecycler.recycle(this, recycleHandle); return r; } public Object[] build(Iterable source, UpdateFunction updateF, int size) { assert updateF != null; NodeBuilder current = rootBuilder; // we descend only to avoid wasting memory; in update() we will often descend into existing trees // so here we want to descend also, so we don't have lg max(N) depth in both directions while ((size >>= FAN_SHIFT) > 0) current = current.ensureChild(); current.reset(EMPTY_LEAF, POSITIVE_INFINITY, updateF, null); for (K key : source) current.addNewKey(key); current = current.ascendToRoot(); Object[] r = current.toNode(); current.clear(); builderRecycler.recycle(this, recycleHandle); return r; } public Object[] build(K [] source, UpdateFunction updateF, int size) { assert updateF != null; int origSize = size; NodeBuilder current = rootBuilder; // we descend only to avoid wasting memory; in update() we will often descend into existing trees // so here we want to descend also, so we don't have lg max(N) depth in both directions while ((size >>= FAN_SHIFT) > 0) current = current.ensureChild(); current.reset(EMPTY_LEAF, POSITIVE_INFINITY, updateF, null); for (int i = 0; i < origSize; i++) current.addNewKey(source[i]); current = current.ascendToRoot(); Object[] r = current.toNode(); current.clear(); builderRecycler.recycle(this, recycleHandle); return r; } }





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