[Mondrian] Except function performance

Matt Campbell mcampbell at pentaho.com
Mon Jun 15 13:26:53 EDT 2015

Except() is not handled natively.  You can try setting “mondrian.native.ExpandNonNative=true”, which will evaluate the except non-natively and attempt to include the resulting tuples in a native context.  That property is enabled by default in Pentaho biserver, but false by default in Mondrian.

Another thing that caught my eye- the ‘*’ crossjoin operator in your query is not mapped to native crossjoin (MONDRIAN-2284).  So that could also be a factor.  Try replacing the crossjoins with nested NonEmptyCrossJoin().

From: mondrian-bounces at pentaho.org [mailto:mondrian-bounces at pentaho.org] On Behalf Of Hilario Fernandes
Sent: Monday, June 15, 2015 12:41 PM
To: Mondrian mailing list
Subject: Re: [Mondrian] Except function performance


I've sent this question a while ago without any replay, bringing it up again.

As I could see, using something like except in that crossjoin, it cannot use a native evaluation and that slows things really a lot. This is as far as i've gotten, maybe someone that knows how things work more in dept can throw some comments in?


On Wed, Mar 4, 2015 at 2:15 PM, Hilario Fernandes <hilario.fernandes at cortex-intelligence.com<mailto:hilario.fernandes at cortex-intelligence.com>> wrote:

I'm having somewhat of a performance problem when trying execute the following query:

MEMBER [Measures].[TotalA] AS
IIF((NOT IsEmpty([Measures].[M1])), Aggregate({[A].CurrentMember} * {[B].[Total B]} * {[C].[Total C]} * {[FILTERED_D]} * {[E].[Total E]}, [Measures].[M1]), NULL)

Except({[D].[D].Members},{[D].[D].[member1], [D].[D].[member2]})})

NON EMPTY ({[Measures].[M1], [Measures].[TotalA]}) ON COLUMNS,
NON EMPTY [A].[A].Members * [B].[B].Members * [C].[C].Members * [FILTERED_D] * [E].[E].Members ON ROWS

The point of the TotalA measure is to return the total of the measure for every A member, repeating it for the rest of the other dimension members on the axis. The problem is this measure must respect the filters in that axis, so the except is placed both on the rows and used on the aggregate.

Thing is, when the except is used in the TotalA calculation its makes the evaluation a lot slower. This only happens with except, if something like Filter(members, measure >100) is used then there is no major difference.

Can anyone shed some light on why this happens? And maybe some ideas to work around it with some other way to achieve the same result.


Hilario Fernandes

Hilario Fernandes
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