如何将多层嵌套的json转换为sql表
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【中文标题】如何将多层嵌套的json转换为sql表【英文标题】:how to convert multiple layers of nested json to sql table 【发布时间】:2017-03-20 06:42:20 【问题描述】:在 *** 的帮助下,我能够做到这一点。需要更多帮助将 JSON 转换为 SQL 表。非常感谢任何帮助。
"Volumes": [
"AvailabilityZone": "us-east-1a",
"Attachments": [
"AttachTime": "2013-12-18T22:35:00.000Z",
"InstanceId": "i-1234567890abcdef0",
"VolumeId": "vol-049df61146c4d7901",
"State": "attached",
"DeleteOnTermination": true,
"Device": "/dev/sda1",
"Tags": [
"Value": "DBJanitor-Private",
"Key": "Name"
,
"Value": "DBJanitor",
"Key": "Owner"
,
"Value": "Database",
"Key": "Product"
,
"Value": "DB Janitor",
"Key": "Portfolio"
,
"Value": "DB Service",
"Key": "Service"
]
],
"Ebs":
"Status": "attached",
"DeleteOnTermination": true,
"VolumeId": "vol-049df61146c4d7901",
"AttachTime": "2016-09-14T19:49:11.000Z"
,
"VolumeType": "standard",
"VolumeId": "vol-049df61146c4d7901"
]
在 *** 的帮助下,我能够解决直到标签。不知道如何解决 Ebs 问题。我对编码很陌生,非常感谢任何帮助。
In [1]: fn = r'D:\temp\.data\40454898.json'
In [2]: with open(fn) as f:
...: data = json.load(f)
...:
In [14]: t = pd.io.json.json_normalize(data['Volumes'],
...: ['Attachments','Tags'],
...: [['Attachments', 'VolumeId'],
...: ['Attachments', 'InstanceId']])
...:
In [15]: t
Out[15]:
Key Value Attachments.InstanceId Attachments.VolumeId
0 Name DBJanitor-Private i-1234567890abcdef0 vol-049df61146c4d7901
1 Owner DBJanitor i-1234567890abcdef0 vol-049df61146c4d7901
2 Product Database i-1234567890abcdef0 vol-049df61146c4d7901
3 Portfolio DB Janitor i-1234567890abcdef0 vol-049df61146c4d7901
4 Service DB Service i-1234567890abcdef0 vol-049df61146c4d7901
谢谢
【问题讨论】:
【参考方案1】:json_normalize
需要一个 list 字典,如果是 Ebs
- 它只是一个字典,所以我们应该预处理 JSON 数据:
In [88]: with open(fn) as f:
...: data = json.load(f)
...:
In [89]: for r in data['Volumes']:
...: if 'Ebs' not in r: # add 'Ebs' dict if it's not in the record...
...: r['Ebs'] = []
...: if not isinstance(r['Ebs'], list): # wrap 'Ebs' in a list if it's not a list
...: r['Ebs'] = [r['Ebs']]
...:
In [90]: data
Out[90]:
'Volumes': ['Attachments': ['AttachTime': '2013-12-18T22:35:00.000Z',
'DeleteOnTermination': True,
'Device': '/dev/sda1',
'InstanceId': 'i-1234567890abcdef0',
'State': 'attached',
'Tags': ['Key': 'Name', 'Value': 'DBJanitor-Private',
'Key': 'Owner', 'Value': 'DBJanitor',
'Key': 'Product', 'Value': 'Database',
'Key': 'Portfolio', 'Value': 'DB Janitor',
'Key': 'Service', 'Value': 'DB Service'],
'VolumeId': 'vol-049df61146c4d7901'],
'AvailabilityZone': 'us-east-1a',
'Ebs': ['AttachTime': '2016-09-14T19:49:11.000Z',
'DeleteOnTermination': True,
'Status': 'attached',
'VolumeId': 'vol-049df61146c4d7901'],
'VolumeId': 'vol-049df61146c4d7901',
'VolumeType': 'standard']
注意:'Ebs': ..
已替换为 'Ebs': [..]
In [91]: e = pd.io.json.json_normalize(data['Volumes'],
...: ['Ebs'],
...: ['VolumeId'],
...: meta_prefix='parent_')
...:
In [92]: e
Out[92]:
AttachTime DeleteOnTermination Status VolumeId parent_VolumeId
0 2016-09-14T19:49:11.000Z True attached vol-049df61146c4d7901 vol-049df61146c4d7901
【讨论】:
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