neo4j实现表字段级血缘关系

标签：String List 表字 currentVertex ColumnVertex table neo4j 段级 name

需求背景

需要在前端页面展示当前表字段的所有上下游血缘关系，以进一步做数据诊断治理。大致效果图如下：

首先这里解释什么是表字段血缘关系，SQL 示例：

CREATE TABLE IF NOT EXISTS table_b
AS SELECT order_id, order_status FROM table_a;

如上 DDL 语句中，创建的 table_b 的 order_id 和 order_status 字段来源于 table_a，代表table_a 就是 table_b 的来源表，也叫上游表，table_b 就是 table_a 下游表，另外 table_a.order_id 就是 table_b.order_id 的上游字段，它们之间就存在血缘关系。

INSERT INTO table_c
SELECT a.order_id, b.order_status
FROM table_a a JOIN table_b b ON a.order_id = b.order_id;

如上 DML 语句中，table_c 的 order_id 字段来源于 table_a，而 order_status 来源于 table_b，表示 table_c 和 table_a、table_b 之间也存在血缘关系。

由上也可看出想要存储血缘关系，还需要先解析 sql，这块儿主要使用了开源项目 calcite 的解析器，这篇文章不再展开，本篇主要讲如何存储和如何展示

环境配置

参考另一篇：springboot 配置内嵌式 neo4j

Node 数据结构定义

因为要展示表的字段之间的血缘关系，所以直接将表字段作为图节点存储，表字段之间的血缘关系就用图节点之间的关系表示，具体 node 定义如下：

public class ColumnVertex {
  // 唯一键
  private String name;

  public ColumnVertex(String catalogName, String databaseName, String tableName, String columnName) {
    this.name = catalogName + "." + databaseName + "." + tableName + "." + columnName;
  }

  public String getCatalogName() {
    return Long.parseLong(name.split("\\.")[0]);
  }

  public String getDatabaseName() {
    return name.split("\\.")[1];
  }

  public String getTableName() {
    return name.split("\\.")[2];
  }

  public String getColumnName() {
    return name.split("\\.")[3];
  }
}

通用 Service 定义

public interface EmbeddedGraphService {
    // 添加图节点以及与上游节点之间的关系
    void addColumnVertex(ColumnVertex currentVertex, ColumnVertex upstreamVertex);
    // 寻找上游节点
    List<ColumnVertex> findUpstreamColumnVertex(ColumnVertex currentVertex);
    // 寻找下游节点
    List<ColumnVertex> findDownstreamColumnVertex(ColumnVertex currentVertex);
}

Service 实现

import javax.annotation.Resource;
import org.neo4j.graphdb.GraphDatabaseService;
import org.neo4j.graphdb.Result;
import org.neo4j.graphdb.Transaction;
import org.springframework.stereotype.Service;

@Service
public class EmbeddedGraphServiceImpl implements EmbeddedGraphService {

  @Resource private GraphDatabaseService graphDb;

  @Override
  public void addColumnVertex(ColumnVertex currentVertex, ColumnVertex upstreamVertex) {
    try (Transaction tx = graphDb.beginTx()) {
      tx.execute(
          "MERGE (c:ColumnVertex {name: $currentName}) MERGE (u:ColumnVertex {name: $upstreamName})"
              + " MERGE (u)-[:UPSTREAM]->(c)",
          Map.of("currentName", currentVertex.getName(), "upstreamName", upstreamVertex.getName()));
      tx.commit();
    }
  }

  @Override
  public List<ColumnVertex> findUpstreamColumnVertex(ColumnVertex currentVertex) {
    List<ColumnVertex> result = new ArrayList<>();
    try (Transaction tx = graphDb.beginTx()) {
      Result queryResult =
          tx.execute(
              "MATCH (u:ColumnVertex)-[:UPSTREAM]->(c:ColumnVertex) WHERE c.name = $name RETURN"
                  + " u.name AS name",
              Map.of("name", currentVertex.getName()));
      while (queryResult.hasNext()) {
        Map<String, Object> row = queryResult.next();
        result.add(new ColumnVertex().setName((String) row.get("name")));
      }
      tx.commit();
    }
    return result;
  }

  @Override
  public List<ColumnVertex> findDownstreamColumnVertex(ColumnVertex currentVertex) {
    List<ColumnVertex> result = new ArrayList<>();
    try (Transaction tx = graphDb.beginTx()) {
      Result queryResult =
          tx.execute(
              "MATCH (c:ColumnVertex)-[:UPSTREAM]->(d:ColumnVertex) WHERE c.name = $name RETURN"
                  + " d.name AS name",
              Map.of("name", currentVertex.getName()));
      while (queryResult.hasNext()) {
        Map<String, Object> row = queryResult.next();
        result.add(new ColumnVertex().setName((String) row.get("name")));
      }
      tx.commit();
    }
    return result;
  }
}

遍历图节点

实现逻辑：

restful 接口入参：当前表（catalogName, databaseName, tableName）
定义返回给前端的数据结构，采用 nodes 和 edges 方式返回，然后前端再根据节点与边关系渲染出完整的血缘关系图

public class ColumnLineageVO {
  List<ColumnLineageNode> nodes;
  List<ColumnLineageEdge> edges;
}

public class ColumnLineageNode {
  private String databaseName;
  private String tableName;
  private List<String> columnNames;
}

public class ColumnLineageEdge {
  private ColumnLineageEdgePoint source;
  private ColumnLineageEdgePoint target;
}

public class ColumnLineageEdgePoint {
  private String databaseName;
  private String tableName;
  private String columnName;
}

查询表字段
采用递归的方式，利用当前表字段遍历与当前表字段关联的所有上下游图节点
将所有节点封装成 List ColumnLineageVO 返回给前端

public ColumnLineageVO getColumnLineage(Table table) {
    ColumnLineageVO columnLineageVO = new ColumnLineageVO();
    List<ColumnLineageNode> nodes = new ArrayList<>();
    List<ColumnLineageEdge> edges = new ArrayList<>();
    // Deduplication
    Set<String> visitedNodes = new HashSet<>();
    Set<String> visitedEdges = new HashSet<>();
    Map<String, List<ColumnVertex>> upstreamCache = new HashMap<>();
    Map<String, List<ColumnVertex>> downstreamCache = new HashMap<>();

    ColumnLineageNode currentNode =
        ColumnLineageNode.builder()
            .databaseName(table.getDatabaseName())
            .tableName(table.getTableName())
            .type(TableType.EXTERNAL_TABLE.getDesc())
            .build();
    nodes.add(currentNode);
    visitedNodes.add(currentNode.getDatabaseName() + "." + currentNode.getTableName());

    for (String columnName : table.getColumnNames()) {
      ColumnVertex currentVertex =
          new ColumnVertex(
              table.getScriptId(), table.getDatabaseName(), table.getTableName(), columnName);
      traverseUpstreamColumnVertex(
          currentVertex, nodes, edges, visitedNodes, visitedEdges, upstreamCache);
      traverseDownstreamColumnVertex(
          currentVertex, nodes, edges, visitedNodes, visitedEdges, downstreamCache);
    }

    columnLineageVO.setNodes(nodes);
    columnLineageVO.setEdges(edges);
    return columnLineageVO;
  }

private void traverseUpstreamColumnVertex(
      ColumnVertex currentVertex,
      List<ColumnLineageNode> nodes,
      List<ColumnLineageEdge> edges,
      Set<String> visitedNodes,
      Set<String> visitedEdges,
      Map<String, List<ColumnVertex>> cache) {
    List<ColumnVertex> upstreamVertices;
    if (cache.containsKey(currentVertex.getName())) {
      upstreamVertices = cache.get(currentVertex.getName());
    } else {
      upstreamVertices = embeddedGraphService.findUpstreamColumnVertex(currentVertex);
      cache.put(currentVertex.getName(), upstreamVertices);
    }
    for (ColumnVertex upstreamVertex : upstreamVertices) {
      String nodeKey = upstreamVertex.getDatabaseName() + "." + upstreamVertex.getTableName();
      if (!visitedNodes.contains(nodeKey)) {
        ColumnLineageNode upstreamNode =
            ColumnLineageNode.builder()
                .databaseName(upstreamVertex.getDatabaseName())
                .tableName(upstreamVertex.getTableName())
                .type(TableType.EXTERNAL_TABLE.getDesc())
                .build();
        nodes.add(upstreamNode);
        visitedNodes.add(nodeKey);
      }
      String edgeKey =
          upstreamVertex.getDatabaseName()
              + upstreamVertex.getTableName()
              + upstreamVertex.getColumnName()
              + currentVertex.getDatabaseName()
              + currentVertex.getTableName()
              + currentVertex.getColumnName();
      if (!visitedEdges.contains(edgeKey)) {
        ColumnLineageEdge edge = createEdge(upstreamVertex, currentVertex);
        edges.add(edge);
        visitedEdges.add(edgeKey);
      }
      traverseUpstreamColumnVertex(upstreamVertex, nodes, edges, visitedNodes, visitedEdges, cache);
    }
  }
  
private void traverseDownstreamColumnVertex(
      ColumnVertex currentVertex,
      List<ColumnLineageNode> nodes,
      List<ColumnLineageEdge> edges,
      Set<String> visitedNodes,
      Set<String> visitedEdges,
      Map<String, List<ColumnVertex>> cache) {
    List<ColumnVertex> downstreamVertices;
    if (cache.containsKey(currentVertex.getName())) {
      downstreamVertices = cache.get(currentVertex.getName());
    } else {
      downstreamVertices = embeddedGraphService.findDownstreamColumnVertex(currentVertex);
      cache.put(currentVertex.getName(), downstreamVertices);
    }
    for (ColumnVertex downstreamVertex : downstreamVertices) {
      String nodeKey = downstreamVertex.getDatabaseName() + "." + downstreamVertex.getTableName();
      if (!visitedNodes.contains(nodeKey)) {
        ColumnLineageNode downstreamNode =
            ColumnLineageNode.builder()
                .databaseName(downstreamVertex.getDatabaseName())
                .tableName(downstreamVertex.getTableName())
                .type(TableType.EXTERNAL_TABLE.getDesc())
                .build();
        nodes.add(downstreamNode);
        visitedNodes.add(nodeKey);
      }
      String edgeKey =
          currentVertex.getDatabaseName()
              + currentVertex.getTableName()
              + currentVertex.getColumnName()
              + downstreamVertex.getDatabaseName()
              + downstreamVertex.getTableName()
              + downstreamVertex.getColumnName();
      if (!visitedEdges.contains(edgeKey)) {
        ColumnLineageEdge edge = createEdge(currentVertex, downstreamVertex);
        edges.add(edge);
        visitedEdges.add(edgeKey);
      }
      traverseDownstreamColumnVertex(
          downstreamVertex, nodes, edges, visitedNodes, visitedEdges, cache);
    }
  }

标签：String,List,表字,currentVertex,ColumnVertex,table,neo4j,段级,name
From： https://www.cnblogs.com/pandacode/p/17648359.html