如何在DynamoDB（Python）中的嵌套属性上使用FilterExpression？

Question

这是我的json模型：

item=item={"Company":"ABCD",
               "Industry":"Invest.Services",
               "Sector":"Financial",
               "Financial_Results":
                             [{"Date":"2007-03-31","Frequency":"Annual","REV1":"20","REV3":"33"},
                              {"Date":"2008-03-31","Frequency":"Annual","REV1":"20","REV3":"34.43"},
                              {"Date":"2012-03-31","Frequency":"Annual","REV1":"30","REV3":Decimal("230")},
                              {"Date":"2013-03-31","Frequency":"Quarterly","REV1":Decimal("30"),"REV3":"3.32"},
                              {"Date":"2013-06-31","Frequency":"Quarterly","REV1":Decimal("20"),"REV3":"-0.343"},
                              {"Date":"2013-09-31","Frequency":"Quarterly","REV1":"20.50","REV3":"-0.543"}]
             }
    table.put_item(Item=item)

item=item={"Company":"EFGH",
               "Industry":"Mining",
               "Sector":"Metals",
               "Financial_Results":
                             [{"Date":"2007-03-31","Frequency":"Annual","REV1":"20","REV3":"33"},
                              {"Date":"2008-03-31","Frequency":"Annual","REV1":"20","REV3":"34.43"},
                              {"Date":"2012-03-31","Frequency":"Annual","REV1":"30","REV3":Decimal("230")},
                              {"Date":"2013-03-31","Frequency":"Quarterly","REV1":Decimal("30"),"REV3":"3.32"},
                              {"Date":"2013-06-31","Frequency":"Quarterly","REV1":Decimal("20"),"REV3":"-0.343"},
                              {"Date":"2014-03-31","Frequency":"Annual","REV1":"20.50","REV3":"-0.543"}]
             }
    table.put_item(Item=item)

公司-分区键（哈希键）。

没有范围键（排序键）。

我的要求是：

• 我该如何过滤'Date'属性等于或大于'2013-03-31'和'REV1'属性且仅包含少于零个项目。

注意：我已经引用了以下链接http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Expressions.Attributes.html#DocumentPaths

我仍然没有任何结论。请帮助我。 提前致谢

Answer 1

经过一整天的研发，我终于找到了答案。 根据AWS DynamoDB文档和其他重要研究，我得出结论，目前不支持我的json模型准备（在顶部） 。根据我的要求，我需要整理数据而不是文档基础。尽管如此，感谢每个贡献者。