Mondrian: sum aggregator gives unexpected results -


i have cube following measures :

<measure name="nbrsecrets" column="issecret" aggregator="sum"/> <measure name="montant du contrat" column="montantcontrat" aggregator="sum" formatstring="$#,##0" />

the column 'issecret either 0 or 1 (of type int in postgres)

the following query returns sums of 0 column / measure nbrsecrets, behaving differently 'montant du contrat', correctly sums values in fact table. result if issecret column of fact table contained 0 rows, know fact many of rows have issecret=1.

 select non empty   {hierarchize({[time].[year].members})}   on columns, non empty   {hierarchize({     [measures].[nbrsecrets],      [measures].[montant du contrat]})}   on rows [contrats] 
 axis #0: {} axis #1: {[time].[2000]} {[time].[2001]} {[time].[2003]} {[time].[2004]} {[time].[2005]} {[time].[2006]} {[time].[2007]} {[time].[2008]} {[time].[2009]} {[time].[2010]} {[time].[2011]} {[time].[2012]} {[time].[2013]} axis #2: {[measures].[montant du contrat]} {[measures].[nbrsecrets]} row #0: $24,906 row #0: $798,634 row #0: $8,381 row #0: $56,281 row #0: $1,683,772 row #0: $614,878 row #0: $4,983,809 row #0: $409,447,717 row #0: $7,769,408,600 row #0: $7,451,808,764 row #0: $10,240,167,750 row #0: $12,675,764,184 row #0: $2,328,797,494 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0 row #1: 0

this mdx seems contradict previous results (issecret returns correct sums in case) :

select non empty crossjoin([transparence (montant des contrats secrets ou non)].[montant secrets].members, [time].[year].members) on columns, non empty {hierarchize({[measures].[nbrsecrets]})} on rows [contrats]

result : 

 axis #0: {} axis #1: {[interneouexterne].[false], [time].[2000]} {[interneouexterne].[false], [time].[2001]} {[interneouexterne].[false], [time].[2003]} {[interneouexterne].[false], [time].[2004]} {[interneouexterne].[false], [time].[2005]} {[interneouexterne].[false], [time].[2006]} {[interneouexterne].[false], [time].[2007]} {[interneouexterne].[false], [time].[2008]} {[interneouexterne].[false], [time].[2009]} {[interneouexterne].[false], [time].[2010]} {[interneouexterne].[false], [time].[2011]} {[interneouexterne].[false], [time].[2012]} {[interneouexterne].[false], [time].[2013]} {[interneouexterne].[true], [time].[2001]} {[interneouexterne].[true], [time].[2008]} {[interneouexterne].[true], [time].[2009]} {[interneouexterne].[true], [time].[2010]} {[interneouexterne].[true], [time].[2011]} {[interneouexterne].[true], [time].[2012]} {[interneouexterne].[true], [time].[2013]} axis #2: {[measures].[nbrsecrets]} row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 0 row #0: 1 row #0: 14 row #0: 336 row #0: 486 row #0: 1,227 row #0: 1,736 row #0: 412


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