In propel there is this doUpdate function, that will return the numbers of affected rows by this query.
The question is, if there is no need to update the row ( because the set value is already the same as the field value), will those rows counted as the affected row?
Take for example, I have the following table:
ID | Name | Books
1 | S1oon | Me
2 | S1oon | Me
Let's assume that I write a ORM function of the equivalent of the following query:
update `new table` set
Books='Me'
where Name='S1oon';
What will the doUpdate result return? Will it return 0 ( because all the Books column are already Me, hence there is no need to update), or will it be 2 ( because there are 2 rows that fulfill the where condition) ?
Under the hood, Propel is using PDO's PDOStatement::rowCount() method to return the number of affected rows. So, the short answer is that you'll get "2" as you expect here, but the longer answer is that it may depend slightly on how PDO implements that function for your specific database. (I think if you did not get 2, it should be a bug for PDO, however.)
See the description of rowCount() in the PHP manual for more info.
One other thing to bear in mind is that when Propel calls methods (like save() or delete()) which are expected to return number-of-rows-modified and which may result in more than one row being modified (e.g. if you add a Book and its Author and then cause both to be INSERTed by calling book->save()), you will get the total number of rows modified.
It will return 2.
Related
I'm learning about Power Builder, and i don't know how to use these, (DWitemstatus, getnextmodified, modifiedcount, getitemstatus, NotModified!, DataModified!, New!, NewModified!)
please help me.
Thanks for read !
These relate to the status of rows in a datawindow. Generally the rows are retrieved from a database but this doesn't always have to be the case - data can be imported from a text file, XML, JSON, etc. as well.
DWItemstatus - these values are constants and describe how the data would be changed in the database.
Values are:
NotModified! - data unchanged since retrieved
DataModified! - data in one or more columns has changed
New! - row is new but no values have been assigned
NewModifed! - row is new and at least one value has been assigned to a column.
So in terms of SQL, a row which is not modified would not generate any SQL to the DBMS. A DataModified row would typically generate an UPDATE statement. New and NewModifed would typically generate INSERT statements.
GetNextModifed is a method to search a set of rows in a datawindow to find the modified rows within that set. The method takes a buffer parameter and a row parameter. The datawindow buffers are Primary!, Filter!, and Delete!. In general you would only look at the Primary buffer.
ModifedCount is a method to determine the number of rows which have been modifed in a datawindow. Note that deleting a row is not considered a modification. To find the number of rows deleted use the DeletedCount method.
GetItemStatus is a method to get the status of column within a row in a data set in a datawindow. It takes the parameters row, column (name or number), and DWBuffer.
So now an example of using this:
// loop through rows checking for changes
IF dw_dash.Modifiedcount() > 0 THEN
ll = dw_dash.GetNextModified(0,Primary!)
ldw = dw_dash
DO WHILE ll > 0
// watch value changed
IF ldw.GetItemStatus(ll,'watch',Primary!) = DataModified! THEN
event we_post_item(ll, 'watch', ldw)
END IF
// followup value changed
IF ldw.GetItemStatus(ll,'followupdate',Primary!) = DataModified! THEN
event we_post_item(ll, 'followupdate', ldw)
END IF
ll = ldw.GetNextModified(ll,Primary!)
LOOP
ldw.resetupdate() //reset the modifed flags
END IF
In this example we first check to see if any row in the datawindow has been modified. Then we get the first modified row and check if either the 'watch' or 'followupdate' columns were changed. If they were we trigger an event to do something. We then loop to the next modified row and so on. Finally we reset the modified flags so the row would now show as not being mofified.
I have two facts tables, First and Second, and two dimension tables, dimTime and dimColour.
Fact table First looks like this:
and facet table Second looks like this:
Both dim-tables have 1:* relationships to both fact tables and the filtering is one-directional (from dim to fact), like this:
dimColour[Color] 1 -> * First[Colour]
dimColour[Color] 1 -> * Second[Colour]
dimTime[Time] 1 -> * First[Time]
dimTime[Time] 1 -> * Second[Time_]
Adding the following measure, I would expect the FILTER-functuion not to have any affect on the calculation, since Second does not filter First, right?
Test_Alone =
CALCULATE (
SUM ( First[Amount] );
First[Alone] = "Y";
FILTER(
'Second';
'Second'[Colour]="Red"
)
)
So this should evaluate to 7, since only two rows in First have [Alone] = "Y" with values 1 and 6 and that there is no direct relationship between First and Second. However, this evaluates to 6. If I remove the FILTER-function argument in the calculate, it evaluates to 7.
There are thre additional measures in the pbix-file attached which show the same type of behaviour.
How is filtering one fact table which has no direct relationship to a second fact table affecting the calculation done on the second table?
Ziped Power BI-file: PowerBIFileDownload
Evaluating the table reference 'Second' produces a table that includes the columns in both the Second table, as well as those in all the (transitive) parents of the Second table.
In this case, this is a table with all of the columns in dimColour, dimTime, Second.
You can't see this if you just run:
evaluate 'Second'
as when 'evaluate' returns the results to the user, these "Parent Table" (or "Related") columns are not included.
Even so, these columns are certainly present.
When a table is converted to a row context, these related columns become available via RELATED.
See the following queries:
evaluate FILTER('Second', ISBLANK(RELATED(dimColour[Color])))
evaluate 'Second' order by RELATED(dimTime[Hour])
Similarly, when arguments to CALCULATE are used to update the filter context, these hidden "Related" columns are not ignored; hence, they can end up filtering First, in your example. You can see this, by using a function that strips the related columns, such as INTERSECT:
Test_ActuallyAlone = CALCULATE (
SUM ( First[Amount] ),
First[Alone] = "Y",
//This filter now does nothing, as none of the columns in Second
//have an impact on 'SUM ( First[Amount] )'; and the related columns
//are removed by the INTERSECT.
FILTER(
INTERSECT('Second', 'Second')
'Second'[Colour]="Red"
)
)
(See these resources that describe the "Expanded Table"
(this is an alternative but equivalent explanation of this behaviour)
https://www.sqlbi.com/articles/expanded-tables-in-dax/
https://www.sqlbi.com/articles/context-transition-and-expanded-tables/
)
This is too tough for me guys. It's for Jeremy!
I have two tables (although I can also envision needing to join a third table) and I want to sum one field and count rows, in the same, table while joining with another table and return the result in json format.
First of all, the data type field that needs to be summed, is numeric(10,2) and the data is inserted as params['amount'].to_f.
The tables are expense_projects which has the name of the project and the company id and expense_items which has the company_id, item and amount (to mention just the critical columns) - the "company_id" columns are disambiguated.
So, the following code:
expense_items = DB[:expense_projects].left_join(:expense_items, :expense_project_id => :project_id).where(:project_company_id => company_id).to_a.to_json
works fine but when I add
expense_total = expense_items.sum(:amount).to_f.to_json
I get an error message which says
TypeError - no implicit conversion of Symbol into Integer:
so, the first question is why and how can this be fixed?
Then I want to join the two tables and get all the project names form the left (first table) and sum amount and count items in the second table. I have tried
DB[:expense_projects].left_join(:expense_items, :expense_items_company_id => expense_projects_company_id).count(:item).sum(:amount).to_json
and variations of this, all of which fails.
I would like a result which gets all the project names (even if there are no expense entries and returns something like:
project item_count item_amount
pr 1 7 34.87
pr 2 0 0
and so on. How can this be achieved with one query returning the result in json format?
Many thanks, guys.
Figured it out, I hope this helps somebody else:
DB[:expense_projects___p].where(:project_company_id=>user_company_id).
left_join(:expense_items___i, :expense_project_id=>:project_id).
select_group(:p__project_name).
select_more{count(:i__item_id)}.
select_more{sum(:i__amount)}.to_a.to_json
The Programming Hive book lists a test in built in function in Hive, but it is not obvious how to use it and I've been unable to find examples
Here is the information from Programming Hive:
Return type Signature Description
----------- --------- -----------
BOOLEAN test in(val1, val2, …) Return true if testequals one of the values in the list.
I want to know if it can be used to say whether a value is in a Hive array.
For example if I do the query:
hive > select id, mcn from patients limit 2;
id mcn
68900015 ["7382771"]
68900016 ["8847332","60015163","63605102","63251683"]
I'd like to be able to test whether one of those numbers, say "60015163" is in the mcn list for a given patient.
Not sure how to do it.
I've tried a number of variations, all of which fail to parse. Here are two examples that don't work:
select id, test in (mcn, "60015163") from patients where id = '68900016';
select id, mcn from patients where id = '68900016' and test mcn in('60015163');
The function is not test in bu instead in. In the table 6-5 test is a colum name.
So in order to know whether a value is in a Hive array, you need first to use explode on your array.
Instead of explode the array column, you can create an UDF, as it is explain here http://souravgulati.webs.com/apps/forums/topics/show/8863080-hive-accessing-hive-array-custom-udf-
I'm having some MDX issues, I want to calculate how many products I have per type per version, this would be my output.
ProductID | QtyProductAVersionA | QtyProductAVersionB | QtyProductBVersionA | QtyProductBVersionB |
I have this MDX so far
WITH MEMBER [Measures].[ProductAVersionA]
AS SUM([DimProduct].[ProductName].&[ProductA],[Measures].[ProductQty])
SELECT NON EMPTY (
[Measures].[ProductAVersionA]) ON COLUMNS,
NON EMPTY [DimOrg].[ProductID].[ProductID].MEMBERS ON ROWS
FROM [Sales]
WHERE([DimCustomers].[Customer Area].&[United States])
But this returns the total of product A, I want only the product A filtered by version A. I can't use it in the WHERE clause since not all my products have the same versions.
Is there any way I can achieve this with a Filter expression inside the calculated memeber? I tried to used but I kept getting an error.
FYI product version is in another dimension [DimVersion]
Any help would be appreciated
You could try filtering the ProductAVersionA calculated member by the DimVersion 'A' member as follows:
member [Measures].[ProductAVersionA] as
sum(([DimProduct].[ProductName].&[ProductA], [DimVersion].[VersionName].&[VersionA]), [Measures].[ProductQty])