java树形结构 算法

最近看到一个有意思的树形结构,为每个节点添加了lftrgt两个属性。这样查找该节点的子节点、查找该节点所有父节点,就不用去递归查询,只需要用betweenand语句就可以实现。下面以创建一个栏目树为例,以下是我的理解。

  一般来讲,我们创建栏目树的时候,大多只需要一个外键parentid来区分该节点属于哪个父节点。数据库的设计如下图:
这样一来,

1.查找该节点的所有子节点,则需要采用sql的递归语句:

 

select * from tableName connect by prior id=sj_parent_id start with  id=1

 

 (oracle 写法,mysql目前不支持,如果mysql想查找树形,可以利用存储过程).

2.查找该节点的父节点的sql递归语句:

 

select * from tableName connect by prior sj_parent_id =id start with  id=1

 

 如果数据量过大或者层次太多,那么这样操作是会影响性能的。

 

  “任何树形结构都可以用二叉树来表示”。其实我们创建的栏目树就是一个简型的二叉树。根据数据结构里面二叉树的遍历,再稍微修改下,将数据库设计如下图所示:

 


这样我们查找该节点的所有子节点,则只需要查找idlftrgt之间的所有节点即可。

1.查找该节点的所有子节点的Sql语句为:

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select * from tb_subject s,tb_subject t where s.lft between t.lft and t.rgt and t.id=1

 

2.查找该节点的所有父节点的sql语句为:

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select s.* from tb_subject s,tb_subject t where s.lft<t.lft and (s.rgt-s.lft)>1 and s.rgt>t.rgt and t.id=1

 

 下面来详细讲解下,怎么用java来实现这种算法。

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 1. 新增节点

 新增节点比较简单,基本步骤为

 A. 查找当前插入节点的父节点的lft

 B. 将树形中所有lftrgt节点大于父节点左值的节点都+2

 C. 将父节点左值+1,左值+2分别作为当前节点的lftrgt

 因为项目中采用的是struts2+hibernate3.2+spring2.5的框架,代码如下:

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public boolean onSave(Object entity, Serializable id, Object[] state,
			String[] propertyNames, Type[] types) {
		if (entity instanceof HibernateTree) {
			HibernateTree tree = (HibernateTree) entity;
			Long parentId = tree.getParentId();
			String beanName = tree.getClass().getName();
			Session session = getSession();
			FlushMode model = session.getFlushMode();
			session.setFlushMode(FlushMode.MANUAL);
			Integer myPosition = new Integer(0);
			//查找父节点的左值
			if (parentId != null) {
				String hql = "select b.lft from " + beanName
						+ " b where b.id=:pid";
				myPosition = (Integer) session.createQuery(hql).setLong("pid",
						parentId).uniqueResult();
			}
			//将树形结构中所有大于父节点左值的右节点+2
			String hql1 = "update " + beanName
					+ " b set b.rgt = b.rgt + 2 WHERE b.rgt > :myPosition";
			//将树形结构中所有大于父节点左值的左节点+2
			String hql2 = "update " + beanName
					+ " b set b.lft = b.lft + 2 WHERE b.lft > :myPosition";
			if (!StringUtils.isBlank(tree.getTreeCondition())) {
				hql1 += " and (" + tree.getTreeCondition() + ")";
				hql2 += " and (" + tree.getTreeCondition() + ")";
			}
			session.createQuery(hql1).setInteger("myPosition", myPosition)
					.executeUpdate();
			session.createQuery(hql2).setInteger("myPosition", myPosition)
					.executeUpdate();
			session.setFlushMode(model);
			//定位自己的左值(父节点左值+1)和右值(父节点左值+2)
			for (int i = 0; i < propertyNames.length; i++) {
				if (propertyNames[i].equals(HibernateTree.LFT)) {
					state[i] = myPosition + 1;
				}
				if (propertyNames[i].equals(HibernateTree.RGT)) {
					state[i] = myPosition + 2;
				}

			}
			return true;
		}
		return false;
	}

 

 2. 修改节点

  修改的时候比较麻烦,具体步骤为:

  在修改lftrgt之前,当前节点的父节点id已经改变

a. 查出当前节点的左右节点(nodelftnodergt),并nodergt-nodelft+1 = span,获取父节点的左节点parentlft

b. 将所有大于parentlftlft(左节点)rgt(右节点)的值+span

c. 查找当前节点的左右节点(nodelftnodergt),并parentlft-nodelft+1 = offset

d. 将所有lft(左节点) between nodelft and nodergt的值+offset

e. 将所有大于nodergtlft(左节点)rgt(右节点)的值-span

 Java代码如下:

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public void updateParent(HibernateTree tree, HibernateTree preParent,
			HibernateTree curParent) {
		if (preParent != null && preParent != null
				&& !preParent.equals(curParent)) {
			String beanName = tree.getClass().getName();
			// 获得节点位置
			String hql = "select b.lft,b.rgt from " + beanName
					+ " b where b.id=:id";
			Object[] position = (Object[]) super.createQuery(hql).setLong(
					"id", tree.getId()).uniqueResult();
			System.out.println(hql+"| id = "+tree.getId()); 
			int nodeLft = ((Number) position[0]).intValue();
			int nodeRgt = ((Number) position[1]).intValue();
			int span = nodeRgt - nodeLft + 1;
			// 获得当前父节点左位置
			hql = "select b.lft from " + beanName + " b where b.id=:id";
			int parentLft = ((Number) super.createQuery(hql).setLong("id",
					curParent.getId()).uniqueResult()).intValue();

			System.out.println(hql+"| id = "+curParent.getId());
			// 先空出位置
			String hql1 = "update " + beanName + " b set b.rgt = b.rgt + "
					+ span + " WHERE b.rgt > :parentLft";
			String hql2 = "update " + beanName + " b set b.lft = b.lft + "
					+ span + " WHERE b.lft > :parentLft";
			if (!StringUtils.isBlank(tree.getTreeCondition())) {
				hql1 += " and (" + tree.getTreeCondition() + ")";
				hql2 += " and (" + tree.getTreeCondition() + ")";
			}
			super.createQuery(hql1).setInteger("parentLft", parentLft)
					.executeUpdate();
			super.createQuery(hql2).setInteger("parentLft", parentLft)
					.executeUpdate();

			System.out.println(hql1+"| parentLft = "+parentLft);
			System.out.println(hql2+"| parentLft = "+parentLft);
			
			// 再调整自己
			hql = "select b.lft,b.rgt from " + beanName + " b where b.id=:id";
			position = (Object[]) super.createQuery(hql).setLong("id",
					tree.getId()).uniqueResult();
			System.out.println(hql+"| id = "+tree.getId());
			nodeLft = ((Number) position[0]).intValue();
			nodeRgt = ((Number) position[1]).intValue();
			int offset = parentLft - nodeLft + 1;
			hql = "update "
					+ beanName
					+ " b set b.lft=b.lft+:offset, b.rgt=b.rgt+:offset WHERE b.lft between :nodeLft and :nodeRgt";
			if (!StringUtils.isBlank(tree.getTreeCondition())) {
				hql += " and (" + tree.getTreeCondition() + ")";
			}
			super.createQuery(hql).setParameter("offset", offset)
					.setParameter("nodeLft", nodeLft).setParameter("nodeRgt",
							nodeRgt).executeUpdate();
			System.out.println(hql+"| offset = "+offset+" | nodelft = "+nodeLft+" | nodergt = "+ nodeRgt);
			// 最后删除(清空位置)
			hql1 = "update " + beanName + " b set b.rgt = b.rgt - " + span
					+ " WHERE b.rgt > :nodeRgt";
			hql2 = "update " + beanName + " b set b.lft = b.lft - " + span
					+ " WHERE b.lft > :nodeRgt";
			if (tree.getTreeCondition() != null) {
				hql1 += " and (" + tree.getTreeCondition() + ")";
				hql2 += " and (" + tree.getTreeCondition() + ")";
			}
			super.createQuery(hql1).setParameter("nodeRgt", nodeRgt)
					.executeUpdate();
			super.createQuery(hql2).setParameter("nodeRgt", nodeRgt)
					.executeUpdate();
			System.out.println(hql1+"| nodeRgt = "+nodeRgt);
			System.out.println(hql2+"| nodeRgt = "+nodeRgt);
			
		}
	}

 

 3. 删除节点

 删除节点也比较简单,具体步骤为:

 A. 查找要删除节点的lft

 B. 将所有lftrgt大于删除节点lft值的都-2

 Java代码如下:

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public void onDelete(Object entity, Serializable id, Object[] state,
			String[] propertyNames, Type[] types) {
		if (entity instanceof HibernateTree) {
			HibernateTree tree = (HibernateTree) entity;
			String beanName = tree.getClass().getName();
			Session session = getSession();
			FlushMode model = session.getFlushMode();
			session.setFlushMode(FlushMode.MANUAL);
		//查找要删除的节点的左值
			String hql = "select b.lft from " + beanName + " b where b.id=:id";
			Integer myPosition = (Integer) session.createQuery(hql).setLong(
					"id", tree.getId()).uniqueResult();
//将所有大于删除节点左值的rgt都-2
			String hql1 = "update " + beanName
					+ " b set b.rgt = b.rgt - 2 WHERE b.rgt > :myPosition";
//将所有大于删除节点左值的lft都-2
			String hql2 = "update " + beanName
					+ " b set b.lft = b.lft - 2 WHERE b.lft > :myPosition";
			if (tree.getTreeCondition() != null) {
				hql1 += " and (" + tree.getTreeCondition() + ")";
				hql2 += " and (" + tree.getTreeCondition() + ")";
			}
			session.createQuery(hql1).setInteger("myPosition", myPosition)
					.executeUpdate();
			session.createQuery(hql2).setInteger("myPosition", myPosition)
					.executeUpdate();
			session.setFlushMode(model);
		}
	}

 
 

 

 

 

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