[Mondrian] Query performance issues

Tom Barber tom at analytical-labs.com
Fri Oct 2 13:44:07 EDT 2015


Interesting stuff thanks for the explanation Matt!

Tom
On 2 Oct 2015 18:34, "Matt Campbell" <mcampbell at pentaho.com> wrote:

> Hi Tom,
>
>
>
> Your second query involves CrossJoins with sets that include multiple
> levels of the same hierarchy, e.g. [Time].[Year] and [Time].[Quarter].
> Native CrossJoin depends on members of each set being of the same level in
> order to form proper push-down tuple queries.  So native eval is disabled
> for this query and Mondrian’s stuck loading the full Cartesian product of
> all CJ’d sets into process.
>
>
>
> We could potentially enhance native eval to cover cases like this,
> although the native eval logic is complex and it could be a big effort.
>
>
>
> -matt
>
>
>
>
>
> *From:* mondrian-bounces at pentaho.org [mailto:mondrian-bounces at pentaho.org]
> *On Behalf Of *Tom Barber
> *Sent:* Friday, October 02, 2015 5:49 AM
> *To:* Mondrian developer mailing list <mondrian at pentaho.org>
> *Subject:* Re: [Mondrian] Query performance issues
>
>
>
> Sorry should probably also point out both tests were using the same
> mondrian build 3.6.5
>
>
>
> Tom
>
>
>
> On 2 October 2015 at 10:43, Tom Barber <tom at analytical-labs.com> wrote:
>
> Hello folks,
>
>
>
> I had a query about MDX query performance between Saiku 2 and 3 and so we
> did some testing and I'd like some expert analysis if anyone has a spare 10
> minutes:
>
>
>
> SELECT
>
> NON EMPTY {Hierarchize({[Measures].[Unit Sales]})} ON COLUMNS,
>
> NON EMPTY Hierarchize(Union(CrossJoin([Time].[Year].Members,
> CrossJoin({[Store].[USA].[OR]}, CrossJoin([Customers].[Name].Members,
> [Product].[Product Name].Members))), Union(CrossJoin([Time].[Year].Members,
> CrossJoin(Filter({[Store].[USA].[OR].[Portland]},
> (Exists(Ancestor([Store].CurrentMember, [Store].[Store State]),
> {[Store].[USA].[OR]}).Count  > 0)), CrossJoin([Customers].[Name].Members,
> [Product].[Product Name].Members))), Union(CrossJoin({[Time].[1997].[Q3]},
> CrossJoin({[Store].[USA].[OR]}, CrossJoin([Customers].[Name].Members,
> [Product].[Product Name].Members))), CrossJoin({[Time].[1997].[Q3]},
> CrossJoin(Filter({[Store].[USA].[OR].[Portland]},
> (Exists(Ancestor([Store].CurrentMember, [Store].[Store State]),
> {[Store].[USA].[OR]}).Count  > 0)), CrossJoin([Customers].[Name].Members,
> [Product].[Product Name].Members))))))) ON ROWS
>
> FROM [Sales]
>
>
>
> This is the MDX created by an old Saiku 2.6 server and the query executes
> in about 20 seconds.
>
>
>
> with set [~Time_Time_Year] as 'Exists({[Time].[Time].[Year].Members},
> [~Time_Time_Quarter])'
>
>   set [~Time_Time_Quarter] as '{[Time].[Time].[1997].[Q3]}'
>
>   set [~ROWS_Time_Time] as 'Hierarchize({[~Time_Time_Year],
> [~Time_Time_Quarter]})'
>
>   set [~Store_Stores_Store State] as '{[Store].[Stores].[USA].[OR]}'
>
>   set [~Store_Stores_Store City] as
> 'Exists({[Store].[Stores].[USA].[OR].[Portland]}, [~Store_Stores_Store
> State])'
>
>   set [~ROWS_Store_Stores] as 'Hierarchize({[~Store_Stores_Store State],
> [~Store_Stores_Store City]})'
>
>   set [~ROWS_Customer_Customers] as
> '{[Customer].[Customers].[Name].Members}'
>
>   set [~ROWS_Product_Products] as '{[Product].[Products].[Product
> Name].Members}'
>
> select NON EMPTY {[Measures].[Unit Sales]} ON COLUMNS,
>
>   NON EMPTY (Crossjoin(Crossjoin(Crossjoin([~ROWS_Time_Time],
> [~ROWS_Store_Stores]), [~ROWS_Customer_Customers]),
> [~ROWS_Product_Products])) ON ROWS
>
> from [Sales]
>
>
>
> This is the much cleaner MDX from the 3.x server, but this query timesout
> every time. Can someone shed any light on why the performance is so much
> worse? I've tried cellbatch size and stuff but none of it makes a shred of
> difference.
>
>
>
> Thanks
>
>
>
> Tom
>
>
>
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>
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