将部门层次结构打印到 table

print departments hierarchy to a table

我与部门的关系 table 如下:

+---------------+----------------+
|     Dept.     | superior Dept. |
+---------------+----------------+
| "00-01"       | "00"           |
| "00-02"       | "00"           |
| "00-01-01"    | "00-01"        |
| "00-01-02"    | "00-01"        |
| "00-01-03"    | "00-01"        |
| "00-02-01"    | "00-02"        |
| "00-02-03"    | "00-02"        |
| "00-02-03-01" | "00-02-03"     |
+---------------+----------------+

现在我想按等级列出它们,如下所示:

+-----------+--------------+--------------+--------------+
| Top Dept. | 2-tier Dept. | 3-tire Dept. | 4-tier Dept. |
+-----------+--------------+--------------+--------------+
|        00 |              |              |              |
|           | 00-01        |              |              |
|           |              | 00-01-01     |              |
|           |              | 00-01-02     |              |
|           | 00-02        |              |              |
|           |              | 00-02-01     |              |
|           |              | 00-02-03     |              |
|           |              |              | 00-02-03-01  |
+-----------+--------------+--------------+--------------+

我可以使用下面的代码构建关系树:
TreeNode.java

import java.util.LinkedList;
import java.util.List;

public class TreeNode {
  public String value;
  public List children = new LinkedList();

  public TreeNode(String rootValue) {
    value = rootValue;
  }

}

PairsToTree.java

import java.util.*;

public class PairsToTree {

  public static void main(String[] args) throws Exception {
    // Create the child to parent hash map
    Map <String, String> childParentMap = new HashMap<String, String>(8);
    childParentMap.put("00-01", "00");
    childParentMap.put("00-02", "00");
    childParentMap.put("00-01-01", "00-01");
    childParentMap.put("00-01-02", "00-01");
    childParentMap.put("00-01-03", "00-01");
    childParentMap.put("00-02-01", "00-02");
    childParentMap.put("00-02-03", "00-02");
    childParentMap.put("00-02-03-01", "00-02-03");

    // All children in the tree
    Collection<String> children = childParentMap.keySet();

    // All parents in the tree
    Collection<String> values = childParentMap.values();

    // Using extra space here as any changes made to values will
    // directly affect the map
    Collection<String> clonedValues = new HashSet();
    for (String value : values) {
      clonedValues.add(value);
    }

    // Find parent which is not a child to any node. It is the
    // root node
    clonedValues.removeAll(children);

    // Some error handling
    if (clonedValues.size() != 1) {
      throw new Exception("More than one root found or no roots found");
    }

    String rootValue = clonedValues.iterator().next();
    TreeNode root = new TreeNode(rootValue);

    HashMap<String, TreeNode> valueNodeMap = new HashMap();
    // Put the root node into value map as it will not be present
    // in the list of children
    valueNodeMap.put(root.value, root);

    // Populate all children into valueNode map
    for (String child : children) {
      TreeNode valueNode = new TreeNode(child);
      valueNodeMap.put(child, valueNode);
    }

    // Now the map contains all nodes in the tree. Iterate through
    // all the children and
    // associate them with their parents
    for (String child : children) {
      TreeNode childNode = valueNodeMap.get(child);
      String parent = childParentMap.get(child);
      TreeNode parentNode = valueNodeMap.get(parent);
      parentNode.children.add(childNode);
    }

    // Traverse tree in level order to see the output. Pretty
    // printing the tree would be very
    // long to fit here.
    Queue q1 = new ArrayDeque();
    Queue q2 = new ArrayDeque();
    q1.add(root);
    Queue<TreeNode> toEmpty = null;
    Queue toFill = null;
    while (true) {
      if (false == q1.isEmpty()) {
        toEmpty = q1;
        toFill = q2;
      } else if (false == q2.isEmpty()) {
        toEmpty = q2;
        toFill = q1;
      } else {
        break;
      }
      while (false == toEmpty.isEmpty()) {
        TreeNode node = toEmpty.poll();
        System.out.print(node.value + ", ");
        toFill.addAll(node.children);
      }
      System.out.println("");
    }
  }

}

但想不通 了解如何将输出格式化为类似于 table。或者是否有 sql statement/stored 程序(如 this question)来执行此操作?

编辑:部门名称只是为了方便起见,可以是任意字符串。

浏览计数 - 个字符的值。最大 - 字符数 +1 是 table 列数。值大小是行数。

您可以定义一个矩阵,例如String[][] 为 table.

对于每个值,您都可以找到列(计算字符串值中的 - 个字符)。 现在要查找行,您应该检查前一列以找到父字符串。

如果找到,则在找到的父行之后插入一个新行,向下移动所有其余行。

如果找不到父字符串,请先插入父字符串(基于 childParentMap)。

如果父级为空,则在末尾插入一个新行。

import java.util.LinkedList;
import java.util.List;

public class TreeNode {
  private String value;
  private int depth;
  private List children = new LinkedList<TreeNode>();

  public TreeNode(String rootValue, int depth) {
      value = rootValue;
      this.depth = depth;
  }


  public boolean add(String parent, String child) {
      if (this.value.equals(parent)) {
          this.children.add(new TreeNode(child, depth + 1));
          return true;
      } else {
          for (TreeNode node : children) {
              if (node.add(parent, child)) {
                  return true;
              }
          }
      }
      return false;
  }

  public String print() {
      StringBuilder sb = new StringBuilder();
      sb.append(format());
      for (TreeNode child : children) {
          sb.append(child.print())
      }
      return sb.toString();
  }

  public String format() {
      // Format this node according to depth;
  }

}

首先打印 Top Dept.,然后在 Top Dept 上调用 print()

这是一个基于您的数据的测试用例,它以表格方式打印部门,尝试运行它看看会发生什么

package test;

import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;

public class DeptHierachy {
    public Map<String,List<String>> deptMap= new HashMap<>();
    public static void main(String[] args) {
        TreeNode tn=new TreeNode("00");
        tn.addChildTo("00-01", "00");
        tn.addChildTo("00-02", "00");
        tn.addChildTo("00-01-01", "00-01");
        tn.addChildTo("00-01-02", "00-01");
        tn.addChildTo("00-01-03", "00-01");
        tn.addChildTo("00-02-01", "00-02");
        tn.addChildTo("00-02-03", "00-02");
        tn.addChildTo("00-02-03-01", "00-02-03");
        tn.print();
        //System.out.println("max height=" + tn.maxHeigth());
    }



    public static class TreeNode {
          public String value;
          public List<TreeNode> children = new LinkedList<>();

          public TreeNode(String rootValue) {
            value = rootValue;
          }

          public boolean addChildTo(String childName, String parentName) {
              if (parentName.equals(value)) {
                  for (TreeNode child:children) {
                      if (child.getValue().equals(childName)) {
                          throw new IllegalArgumentException(parentName + " already has a child named " + childName);
                      }
                  }
                  children.add(new TreeNode(childName));
                  return true;
              } else {
                  for (TreeNode child:children) {
                      if (child.addChildTo(childName, parentName)) {
                          return true;
                      }
                  }
              }
              return false;
          }

        public String getValue() {
            return value;
        }

        public void print() {
            int maxHeight=maxHeigth();
            System.out.printf("|%-20.20s",value);

            for (int i=0;i<maxHeight-1;i++) {
                System.out.printf("|%-20.20s","");
            }
            System.out.println("|");
            for (TreeNode child:children) {
                child.print(1,maxHeight);
            }
        }

        public void print(int level, int maxHeight) {
            for (int i=0;i<level;i++) {
                System.out.printf("|%-20.20s","");
            }
            System.out.printf("|%-20.20s",value);
            for (int i=level;i<maxHeight-1;i++) {
                System.out.printf("|%-20.20s","");
            }
            System.out.println("|");
            for (TreeNode child:children) {
                child.print(level+1,maxHeight);
            }
        }

        public int maxHeigth() {
            int localMaxHeight=0;
            for (TreeNode child:children) {
                int childHeight = child.maxHeigth();
                if (localMaxHeight < childHeight) {
                    localMaxHeight = childHeight;
                }
            }
            return localMaxHeight+1;
        }
    }   

}

您没有注意到您使用的是什么 RDBMS,但如果它恰好是 MS SQL 服务器或某些版本的 Oracle(请参阅下面的编辑),并且仅作为我们这些使用的人的服务T-SQL 并且对这个问题感兴趣,你可以在SQL 服务器中使用recursive CTE 来完成。

编辑:Oracle(我对它的经验非常非常少)似乎也支持递归,包括自 11g 第 2 版以来的递归 CTE。See this question for more information.

鉴于此设置:

CREATE TABLE hierarchy
    ([Dept] varchar(13), [superiorDept] varchar(12))
;

INSERT INTO hierarchy
    ([Dept], [superiorDept])
VALUES
    ('00',NULL),
    ('00-01', '00'),
    ('00-02', '00'),
    ('00-01-01', '00-01'),
    ('00-01-02', '00-01'),
    ('00-01-03', '00-01'),
    ('00-02-01', '00-02'),
    ('00-02-03', '00-02'),
    ('00-02-03-01', '00-02-03')
;

这个递归 CTE:

WITH cte AS (
SELECT 
  Dept,
  superiorDept,
  0 AS depth,
  CAST(Dept AS NVARCHAR(MAX)) AS sort
FROM hierarchy h
WHERE superiorDept IS NULL

UNION ALL

SELECT 
  h2.Dept,
  h2.superiorDept,
  cte.depth + 1 AS depth,
  CAST(cte.sort + h2.Dept AS NVARCHAR(MAX)) AS sort
FROM hierarchy h2
INNER JOIN cte ON h2.superiorDept = cte.Dept
)

SELECT 
  CASE WHEN depth = 0 THEN Dept END AS TopTier,
  CASE WHEN depth = 1 THEN Dept END AS Tier2,
  CASE WHEN depth = 2 THEN Dept END AS Tier3,
  CASE WHEN depth = 3 THEN Dept END AS Tier4
FROM cte
ORDER BY sort

将呈现所需的输出:

 TopTier    Tier2   Tier3     Tier4
 00 
            00-01   
                    00-01-01
                    00-01-02
                    00-01-03
            00-02
                    00-02-01
                    00-02-03
                              00-02-03-01

Here is a SQLFiddle to demonstrate

无论邻接表中涉及的两列的内容或类型如何,这都应该有效。只要父值与 id 值匹配,CTE 生成深度和排序信息应该没有问题。

在 SQL 中完全执行此操作的唯一警告是您必须手动定义一定数量的列,但在处理 SQL 时几乎总是如此。您可能希望生成 CTE,然后将已排序的结果传递给您的程序并使用深度信息使列操作变得微不足道。