aggregate

问题 To prevent reinventing the wheel, I'd like to use MediatR in the Aggregates to publish domain events. (Un)Fortunately(?) MediatR works as a dependency that is injected into the classes, and not something that I can call statically. Therefore I'd end up creating a direct dependency on the library via the constructor. I don't remember where I read it (and if I read it right), that I should avoid non-business dependencies in the constructors of the Aggregates. Therefore, I shouldn't do something

问题 To prevent reinventing the wheel, I'd like to use MediatR in the Aggregates to publish domain events. (Un)Fortunately(?) MediatR works as a dependency that is injected into the classes, and not something that I can call statically. Therefore I'd end up creating a direct dependency on the library via the constructor. I don't remember where I read it (and if I read it right), that I should avoid non-business dependencies in the constructors of the Aggregates. Therefore, I shouldn't do something

问题 I've been struggling with this one fetchxml report for Dynamics CRM online. The report is using aggregate to detect duplications based on certain fields. So, even though it is an aggregate report, the data set will return a lot of rows. Then I found out that the number of rows returned for aggregate fetchxml is limited to 5000. I understand that normal fetchxml report will return records more than 5000 but for aggregate report, this doesn't seem to be the case. In the resultset, the

问题 I have been struggling with this for a while. I am new to working with ts data and all related R packages. I have a df with several variables including what 'time of day'in GMT "%H%M" and date "%Y/%m/%e" sampling occurred. I want to bin/aggregate my date data into "weeks" (i.e., %W/%g) and calculate the mean 'time of the day' when sampling occurred during that week. I was able to calculate other FUN on numerical variables (e.g., weight) by first transforming my df into a zoo object and then

问题 we have several internal p2 repositories. Each repository has many versions of different features. We need to have an external update site for our clients. We would like to aggregate only specific versions of specific features. Would is a good way/tool to "aggregate" them? For example we have a p2 repository repo1 with feature feature1 with versions 1.0.0 , 2.0.0 , 3.0.0 and another p2 repository repo2 with feature feature2 with versions 1.0.0 and 2.0.0 . We would like to aggregate versions 1

问题 we have several internal p2 repositories. Each repository has many versions of different features. We need to have an external update site for our clients. We would like to aggregate only specific versions of specific features. Would is a good way/tool to "aggregate" them? For example we have a p2 repository repo1 with feature feature1 with versions 1.0.0 , 2.0.0 , 3.0.0 and another p2 repository repo2 with feature feature2 with versions 1.0.0 and 2.0.0 . We would like to aggregate versions 1

问题 When using the Scala standard lib, I can do somthing like this: scala> val scalaList = List(1,2,3) scalaList: List[Int] = List(1, 2, 3) scala> scalaList.foldLeft(0)((acc,n)=>acc+n) res0: Int = 6 Making one Int out of many Ints. And I can do something like this: scala> scalaList.foldLeft("")((acc,n)=>acc+n.toString) res1: String = 123 Making one String out of many Ints. So, foldLeft could be either homogeneous or heterogeneous, whichever we want, it's in one API. While in Spark, if I want one

问题 The ultimate goal is to sum the total quantity( transact_data$qty ) for each record in product_info where the transact_data$productId exists in product_info , and where transact_data$date is between product_info$beg_date and product_info$end_date . The dataframes are below: product_info <- data.frame(productId = c("A", "B", "A", "C","C","B"), old_price = c(0.5,0.10,0.11,0.12,0.3,0.4), new_price = c(0.7,0.11,0.12,0.11,0.2,0.3), beg_date = c("2014-05-01", "2014-06-01", "2014-05-01", "2014-06-01

问题 It seems like this code: #include <string> #include <vector> struct bla { std::string a; int b; }; int main() { std::vector<bla> v; v.emplace_back("string", 42); } could be made to work properly in this case, but it doesn't (and I understand why). Giving bla a constructor solves this, but removes the aggregateness of the type, which can have far-reaching consequences. Is this an oversight in the Standard? Or am I missing certain cases where this will blow up in my face, or is it just not as

问题 I am concerned whether Rails can handle the types of complex aggregations that are needed for a financial application and particularly whether the ORM can handle these effectively. In a financial application that I am thinking of using this for, there is a need to do lots of reporting of detailed financial data, aggregated in various ways. Without support in the Rails ORM, I would need to write direct SQL. But I am concerned that once I start this, other parts of Rails may not work as well