Python导出Hbase数据的思路：

使用happybase连接Hbase使用table.scan()扫数据，将得到的数据整理为dataframe格式将从Hbase中得到的byte类型的数据转为str类型的数据

示例代码

import happybaseimport numpy as npimport pandas as pddef create_table(table_name):"""创建表"""connection = happybase.Connection()if table_name in connection.tables(): # 在所有的表中connection.delete_table(table_name, disable=True) # 删除表connection.create_table(table_name, # 表名{"col_1": dict(), # 定义列族"col_2": dict(), # 定义列族"col_3": dict(),})connection.close()def generate_data(table_name):"""添加数据，添加20000行数据"""connection = happybase.Connection()table = connection.table(table_name)with table.batch(batch_size=10) as batch_table:for i in range(20000):random_col = np.random.randint(0, 10)batch_table.put('row{}'.format(i), {'col_1:c{}'.format(random_col): "{}".format(random_col),'col_2:c{}'.format(random_col): "{}".format(random_col),'col_3:c{}'.format(random_col): "{}".format(random_col),})def convert_string(value):"""将byte类型的数据转为str"""if pd.isna(value):return valueelse:return value.decode("utf8")def change_data_to_dataframe(table_name, limit=2000):"""将数据转为dataframe"""connection = happybase.Connection()table = connection.table(table_name)table_index = []table_values = []for key, value in table.scan(limit=limit): # 选择前1000行table_index.append(key)table_values.append(value)table_index = [i.decode("utf8") for i in table_index]table_df = pd.DataFrame(table_values, index=table_index)table_df = table_df.applymap(convert_string) # 将bytes解码为utf-8table_df.columns = [convert_string(i) for i in table_df.columns]return table_dfdef main():table_name = "generate_table"create_table(table_name) # 创建数据tablegenerate_data(table_name) # 生成数据tabletable_df = change_data_to_dataframe(table_name)print(table_df.head())if __name__ == '__main__':main()