使用apache元模型读取数据源元数据

时间:2015-07-03 07:28:01

标签: java apache-metamodel

我想阅读数据源的元数据。无论是数据库还是文件。要求是显示每个表的可用表和列的集合。我也想知道外键等的细节。我知道这应该可以使用JDBC API。但我想知道Apache Metamodel是否以抽象的方式支持它,可以用于所有类型的数据源。

很好,如果你可以分享任何例子。

...... 拉姆

1 个答案:

答案 0 :(得分:1)

可以在Apache Metamodel中探索模式,表和列。 DataContext有一个名为“information_schema”的模式,您可以看到有关数据上下文的元数据。查找此代码段以获取示例:

    // Prepare a data context based on plain old Java objects
    List<TableDataProvider<?>> tableDataProviders = new ArrayList<TableDataProvider<?>>();
    SimpleTableDef tableDef1 = new SimpleTableDef("snippetTableName1", new String[] {"id", "name"});
    tableDataProviders.add(new ArrayTableDataProvider(tableDef1,
            new ArrayList<Object[]>()));
    PojoDataContext dataContext = new PojoDataContext("snippetSchemaName", tableDataProviders);

    // Prints a schema tree
    for (Schema schema : dataContext.getSchemas()) {
        System.out.println("Schema: " + schema.getName());
        for (Table table : schema.getTables()) {
            System.out.println("\t Table: " + table.getName());
            for (Column column : table.getColumns()) {
                System.out.println("\t\t Column: " + column.getName() + " of type: " + column.getType());
            }
        }
    }

这应该打印:

Schema: information_schema
 Table: tables
     Column: name of type: VARCHAR
     Column: type of type: VARCHAR
     Column: num_columns of type: INTEGER
     Column: remarks of type: VARCHAR
 Table: columns
     Column: name of type: VARCHAR
     Column: type of type: VARCHAR
     Column: native_type of type: VARCHAR
     Column: size of type: INTEGER
     Column: nullable of type: BOOLEAN
     Column: indexed of type: BOOLEAN
     Column: table of type: VARCHAR
     Column: remarks of type: VARCHAR
 Table: relationships
     Column: primary_table of type: VARCHAR
     Column: primary_column of type: VARCHAR
     Column: foreign_table of type: VARCHAR
     Column: foreign_column of type: VARCHAR
Schema: snippetSchemaName
     Table: snippetTableName1
         Column: id of type: VARCHAR
         Column: name of type: VARCHAR