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CQRS在java世界中(CQRS in the java world)

我现在很长时间都在关于cqrs的讨论。

我遇到的一点是,所选择的编程语言大部分都是在dot.Net世界中解决的。

是否有这种情况的原因? 为什么cqrs的概念不能在java世界中嵌套呢? 是否有另一种概念/架构风格,可能在java strathosphere中命名的不同我还不知道?


I follow the discussion about cqrs a long time now.

Something that occured to me, is that the programming language of choice is mostly settled in the dot.Net world.

Is there any reasons why this is the case? Why dind't the concepts of cqrs nest themself in the java world yet? Is there a another concept/architecture style, maybe different named in the java strathosphere i don't know yet?


原文:https://stackoverflow.com/questions/4350943
更新时间:2023-08-16 10:08

最满意答案

您需要使用np.in1d来测试您的criteriaList成员资格:

In [1]: myArray["ZoneName"] in criteriaList
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-ff2173ff4348> in <module>()
----> 1 myArray["ZoneName"] in criteriaList

ValueError: The truth value of an array with more than one element is ambiguous.
Use a.any() or a.all()

In [2]: np.in1d(myArray["ZoneName"], criteriaList)
Out[2]: array([False,  True,  True,  True,  True], dtype=bool)

In [3]: myArray[(myArray["Flag1"] == 1) &
   ....:        (myArray["Flag2"] == 1) &
   ....:        np.in1d(myArray["ZoneName"], criteriaList)]["Value"].sum()
Out[3]: 31.344999999999999

You need to use np.in1d to test for membership of your criteriaList:

In [1]: myArray["ZoneName"] in criteriaList
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-ff2173ff4348> in <module>()
----> 1 myArray["ZoneName"] in criteriaList

ValueError: The truth value of an array with more than one element is ambiguous.
Use a.any() or a.all()

In [2]: np.in1d(myArray["ZoneName"], criteriaList)
Out[2]: array([False,  True,  True,  True,  True], dtype=bool)

In [3]: myArray[(myArray["Flag1"] == 1) &
   ....:        (myArray["Flag2"] == 1) &
   ....:        np.in1d(myArray["ZoneName"], criteriaList)]["Value"].sum()
Out[3]: 31.344999999999999

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