任何Python OLAP / MDX ORM引擎？ [英] Any Python OLAP/MDX ORM engines?

问题描述

我是MDX / OLAP的新手，我想知道是否有类似于支持OLAP的Python的Django ORM类似的ORM。

I'm new to the MDX/OLAP and I'm wondering if there is any ORM similar like Django ORM for Python that would support OLAP.

一个Python / Django开发人员，如果会有一些与Django有一定程度的集成，我将会更加了解更多关于它的信息。

I'm a Python/Django developer and if there would be something that would have some level of integration with Django I would be much interested in learning more about it.

推荐答案

Django有一些即将发布的OLAP功能。

Django has some OLAP features that are nearing release.

阅读 http://www.eflorenzano.com/blog/post/secrets-django-orm/

http://doughellmann.com /2007/12/30/using-raw-sql-in-django.html ，也

如果您在第一个地方，则一维结果可以具有以下形式。

If you have a proper star schema design in the first place, then one-dimensional results can have the following form.

from myapp.models import SomeFact
from collections import defaultdict

facts = SomeFact.objects.filter( dimension1__attribute=this, dimension2__attribute=that )
myAggregates = defaultdict( int )
for row in facts:
    myAggregates[row.dimension3__attribute] += row.someMeasure

如果要创建二维总结，你必须做如下的事情。

If you want to create a two-dimensional summary, you have to do something like the following.

facts = SomeFact.objects.filter( dimension1__attribute=this, dimension2__attribute=that )
myAggregates = defaultdict( int )
for row in facts:
    key = ( row.dimension3__attribute, row.dimension4__attribute )
    myAggregates[key] += row.someMeasure

要计算多个SUM和COUNT，而不需要执行此操作。

To compute multiple SUM's and COUNT's and what-not, you have to do something like this.

class MyAgg( object ):
    def __init__( self ):
        self.count = 0
        self.thisSum= 0
        self.thatSum= 0

myAggregates= defaultdict( MyAgg )
for row in facts:
    myAggregates[row.dimension3__attr].count += 1
    myAggregates[row.dimension3__attr].thisSum += row.this
    myAggregates[row.dimension3__attr].thatSum += row.that

这 - 首先是脸红 - - 似乎效率低下你正在拖动事实表，返回大量的行，然后您在应用程序中进行聚合。

This -- at first blush -- seems inefficient. You're trolling through the fact table returning lots of rows which you are then aggregating in your application.

在某些情况下，这可能会更快 RDBMS的本机sum / group_by。为什么？您正在使用简单的映射，而不是RDBMS经常为此使用更复杂的基于排序的分组操作。是的，你得到很多行但是你做得更少了。

In some cases, this may be faster than the RDBMS's native sum/group_by. Why? You're using a simple mapping, not the more complex sort-based grouping operation that the RDBMS often has to use for this. Yes, you're getting a lot of rows; but you're doing less to get them.

这个缺点是它不像我们想要的那么声明。它的优点是纯粹的Django ORM。

This has the disadvantage that it's not so declarative as we'd like. It has the advantage that it's pure Django ORM.

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