Question

我正在尝试从AVRO文件创建一个包含表格结构的SQL表：

{
  "type" : "record",
  "name" : "warranty",
  "doc" : "Schema generated by Kite",
  "fields" : [ {
    "name" : "id",
    "type" : "long",
    "doc" : "Type inferred from '1'"
  }, {
    "name" : "train_id",
    "type" : "long",
    "doc" : "Type inferred from '21691'"
  }, {
    "name" : "siemens_nr",
    "type" : "string",
    "doc" : "Type inferred from 'Loco-001'"
  }, {
    "name" : "uic_nr",
    "type" : "long",
    "doc" : "Type inferred from '193901'"
  }, {
    "name" : "Configuration",
    "type" : "string",
    "doc" : "Type inferred from 'ZP28'"
  }, {
    "name" : "Warranty_Status",
    "type" : "string",
    "doc" : "Type inferred from 'Out_of_Warranty'"
  }, {
    "name" : "Warranty_Data_Type",
    "type" : "string",
    "doc" : "Type inferred from 'Real_based_on_preliminary_acceptance_date'"
  }, {
    "name" : "of_progression",
    "type" : "long",
    "doc" : "Type inferred from '100'"
  }, {
    "name" : "Delivery_Date",
    "type" : "string",
    "doc" : "Type inferred from '18/12/2009'"
  }, {
    "name" : "Warranty_on_Delivery_Date",
    "type" : "string",
    "doc" : "Type inferred from '18/12/2013'"
  }, {
    "name" : "Customer_Status",
    "type" : "string",
    "doc" : "Type inferred from 'homologation'"
  }, {
    "name" : "Commissioning_Date",
    "type" : "string",
    "doc" : "Type inferred from '6/10/2010'"
  }, {
    "name" : "Preliminary_acceptance_date",
    "type" : "string",
    "doc" : "Type inferred from '6/01/2011'"
  }, {
    "name" : "Warranty_Start_Date",
    "type" : "string",
    "doc" : "Type inferred from '6/01/2011'"
  }, {
    "name" : "Warranty_End_Date",
    "type" : "string",
    "doc" : "Type inferred from '6/01/2013'"
  }, {
    "name" : "Effective_End_Warranty_Date",
    "type" : [ "null", "string" ],
    "doc" : "Type inferred from 'null'",
    "default" : null
  }, {
    "name" : "Level_2_in_function",
    "type" : "string",
    "doc" : "Type inferred from '17/07/2015'"
  }, {
    "name" : "Baseline",
    "type" : "string",
    "doc" : "Type inferred from '2.10.23.4'"
  }, {
    "name" : "TC_report",
    "type" : "string",
    "doc" : "Type inferred from 'A480140'"
  }, {
    "name" : "Last_version_Date",
    "type" : "string",
    "doc" : "Type inferred from 'A-23/09/2015'"
  } ]
}

做这项工作，我正在使用（如果你有其他命题更简单就会很棒）

所以使用python我会得到这样的结果：

{'name':'id',type':'long','doc':'blablabla'}

我的问题是如何从这个结果中在python中创建一个SQL表？

感谢您的帮助

Answer 1

使用json模块，你可以从你的字符串中获取一个字典，然后你有一个字段定义数组。您遍历该数组以生成SQL语句。

注意：您需要一些机制来将avro字段类型映射到SQL字段类型，尤其是在类型为"type" : [ "null", "string" ]的情况下。

以下是基于字符串构建SQL CREATE TABLE语句的代码的工作示例：

import json

schema_str = """{
  "type" : "record",
  "name" : "warranty",
  "doc" : "Schema generated by Kite",
  "fields" : [ {
    "name" : "id",
    "type" : "long",
    "doc" : "Type inferred from '1'"
  }, {
    "name" : "train_id",
    "type" : "long",
    "doc" : "Type inferred from '21691'"
  }, {
    "name" : "siemens_nr",
    "type" : "string",
    "doc" : "Type inferred from 'Loco-001'"
  } ]
}"""

schema = json.loads(schema_str)
fields =  schema['fields']

sql_string = 'CREATE TABLE ' + schema['name'] + ' ( \n'
for field in fields : 
    sql_string = sql_string + field['name'] + ' ' + field['type'] + ', \n'

sql_string = sql_string[:-3] + '\n)'  # get rid of last comma and close the field list

print sql_string

使用python读取Avro文件以创建SQL表

1 个答案: