一、小数据量情况下写入到Greenplum中

    from sqlalchemy import create_engine


    #指定表字段类型
    dtype = {
        'name' : types.VARCHAR(length=255),
        'age'  : types.INT,
    }    

    # 创建数据库信息
    engine = create_engine('postgresql://username:password@ip:host/postgres') 

    # data是一个dataframe对象
    data.to_sql('表名',con=engine,if_exists='append',index=False,dtype=dtype)

 二、大数据量情况下写入到Greenplum中（百万、千万、亿级别）

    import io
    from sqlalchemy import types,create_engine 


    #指定表字段类型
    dtype = {
        'name' : types.VARCHAR(length=255),
        'age'  : types.INT,
    }    

    # io流对象
    string_data_io = io.StringIO()
    # data是一个dataframe对象
    data.to_csv(string_data_io, sep='|', index=False)
    # 初始化数据库连接配置
    engine = create_engine('postgresql://username:password@ip:host/postgres') 
    pd_sql_engine = pd.io.sql.pandasSQL_builder(engine)
    table = pd.io.sql.SQLTable('表名', pd_sql_engine, frame=data, index=False, if_exists='replace',
                               schema=None, dtype=dtype)
    # 创建临时分数表
    table.create()
    string_data_io.seek(0)
    with engine.connect() as connection:
        with connection.connection.cursor() as cursor:
            copy_cmd = "COPY 表名 from STDIN HEADER DELIMITER '|' CSV"
            cursor.copy_expert(copy_cmd, string_data_io)
        connection.connection.commit()