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📄 priorityqueue.java

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package org.apache.lucene.util;/** * 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 "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. *//** A PriorityQueue maintains a partial ordering of its elements such that the  least element can always be found in constant time.  Put()'s and pop()'s  require log(size) time. */public abstract class PriorityQueue {  private Object[] heap;  private int size;  private int maxSize;  /** Determines the ordering of objects in this priority queue.  Subclasses    must define this one method. */  protected abstract boolean lessThan(Object a, Object b);  /** Subclass constructors must call this. */  protected final void initialize(int maxSize) {    size = 0;    int heapSize = maxSize + 1;    heap = new Object[heapSize];    this.maxSize = maxSize;  }  /**   * Adds an Object to a PriorityQueue in log(size) time.   * If one tries to add more objects than maxSize from initialize   * a RuntimeException (ArrayIndexOutOfBound) is thrown.   */  public final void put(Object element) {    size++;    heap[size] = element;    upHeap();  }  /**   * Adds element to the PriorityQueue in log(size) time if either   * the PriorityQueue is not full, or not lessThan(element, top()).   * @param element   * @return true if element is added, false otherwise.   */  public boolean insert(Object element){    if(size < maxSize){      put(element);      return true;    }    else if(size > 0 && !lessThan(element, top())){      heap[1] = element;      adjustTop();      return true;    }    else      return false;   }  /** Returns the least element of the PriorityQueue in constant time. */  public final Object top() {    if (size > 0)      return heap[1];    else      return null;  }  /** Removes and returns the least element of the PriorityQueue in log(size)    time. */  public final Object pop() {    if (size > 0) {      Object result = heap[1];			  // save first value      heap[1] = heap[size];			  // move last to first      heap[size] = null;			  // permit GC of objects      size--;      downHeap();				  // adjust heap      return result;    } else      return null;  }  /** Should be called when the Object at top changes values.  Still log(n)   * worst case, but it's at least twice as fast to <pre>   *  { pq.top().change(); pq.adjustTop(); }   * </pre> instead of <pre>   *  { o = pq.pop(); o.change(); pq.push(o); }   * </pre>   */  public final void adjustTop() {    downHeap();  }  /** Returns the number of elements currently stored in the PriorityQueue. */  public final int size() {    return size;  }  /** Removes all entries from the PriorityQueue. */  public final void clear() {    for (int i = 0; i <= size; i++)      heap[i] = null;    size = 0;  }  private final void upHeap() {    int i = size;    Object node = heap[i];			  // save bottom node    int j = i >>> 1;    while (j > 0 && lessThan(node, heap[j])) {      heap[i] = heap[j];			  // shift parents down      i = j;      j = j >>> 1;    }    heap[i] = node;				  // install saved node  }  private final void downHeap() {    int i = 1;    Object node = heap[i];			  // save top node    int j = i << 1;				  // find smaller child    int k = j + 1;    if (k <= size && lessThan(heap[k], heap[j])) {      j = k;    }    while (j <= size && lessThan(heap[j], node)) {      heap[i] = heap[j];			  // shift up child      i = j;      j = i << 1;      k = j + 1;      if (k <= size && lessThan(heap[k], heap[j])) {	j = k;      }    }    heap[i] = node;				  // install saved node  }}

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