Pentaho Mondrian: Custom Formatting with Cell Formatter


Repost from http://diethardsteiner.github.io/mondrian/2015/07/29/Mondrian-Cell-Formatter.html

Formatting measures in cubes is quite essential for the readability of any analysis results. Pentaho Mondrian features a formatString (attribute of measure declaration in a Mondrian Cube Definition) and FORMAT_STRING (MDX query) options which allow you to define the format in a Visual Basic syntax. Say you want to display 12344 as 12,333 you can easily create following formatting mask: #,###. This kind of approach works for most use cases.

However, sometimes you might required a custom formatting option which is not covered by the Visual Basic formatting options. Imagine e.g. that one of the measures of your cube is a duration in seconds. The integer value that you store in your database is not really a nice way of presenting this measure, unless of course you are only dealing with very small figures. But what if you have e.g. a figure like 102234 seconds. How many days, hours etc is this?

One approach of dealing with this is to create hidden calculated members which break this figure down into days, hours, minutes etc:

measure mdx calculation
days CAST(INT(sec/(60*60*24)) AS INTEGER)
hours CAST(INT((sec/(60*60))-(days*24)) AS INTEGER)
minutes CAST(INT((sec/60)-(days*(24*60))-(hours*60)) AS INTEGER)
seconds CAST(ROUND(sec-(days*(24*60*60))-(hours*60*60)-(minutes*60),0) AS INTEGER)

You could then create a visible measure which concatenates all these invisible measures and displays the figure as 1d 4h 24min 54sec. Example final calculated visible measure:

CAST([Measures].[Days] AS STRING) || "d " || IIF([Measures].[Hours] < 10, "0", "") || CAST([Measures].[Hours] AS STRING) || ... and so forth

However, while this approach works, you will realize that you cannot sort by this measure properly! That’s rather inconvenient.

Fortunately enough, Mondrian also provides a Cell Formatter, which allows you to access the value of e.g. a measure and manipulate it any way for display purposes, but – and this is the very important bit – this does not influence the underlying data type. So in our example, the integer value for the duration will still be an integer value and hence the sorting will work! The other really good point is that you can use various languages to manipulate the value, e.g. Java or JavaScript.

To add a special Cell Formatter, simply nest the CellFormatter XML element within the Measure or CalculatedMeasure XML element. Then nest another Script XML element within this one to specify the Script Language and finally nest your code within this element. Example (this time including weeks as well):

<Measure name="Duration" column="duration" visible="true" aggregator="sum">
    <CellFormatter>
         language="JavaScript">
            var result_string = '';
            // access Mondrian value
            var sec =  value;
            var weeks = Math.floor(sec/(60*60*24*7));
            var days = Math.floor((sec/(60*60*24)) - (weeks*7));
            var hours = Math.floor(sec/(60*60) - (weeks*7*24) - (days*24));
            var minutes = Math.floor((sec/60) - (weeks*7*24*60) - (days*24*60) - (hours*60));
            var seconds = Math.floor(sec - (weeks*7*24*60*60) - (days*24*60*60) - (hours*60*60) - (minutes*60));
            result_string = weeks.toString() + 'w ' + days.toString() + 'd ' + hours.toString() + 'h ' + minutes.toString() + 'min ' + seconds.toString() + 'sec';
            return result_string;
        
    </CellFormatter>
</Measure>

You could of course improve the JavaScript further by only showing the relevant duration portions:

var result_string = '';
// access Mondrian value
var sec =  value;
var weeks = Math.floor(sec/(60*60*24*7));
var days = Math.floor((sec/(60*60*24)) - (weeks*7));
var hours = Math.floor(sec/(60*60) - (weeks*7*24) - (days*24));
var minutes = Math.floor((sec/60) - (weeks*7*24*60) - (days*24*60) - (hours*60));
var seconds = Math.floor(sec - (weeks*7*24*60*60) - (days*24*60*60) - (hours*60*60) - (minutes*60));
if(weeks !== 0){
    result_string = weeks.toString() + 'w ' + days.toString() + 'd ' + hours.toString() + 'h ' + minutes.toString() + 'min ' + seconds.toString() + 'sec';
} else if(days !== 0){
    result_string = days.toString() + 'd ' + hours.toString() + 'h ' + minutes.toString() + 'min ' + seconds.toString() + 'sec';
} else if(hours !== 0){
    result_string = hours.toString() + 'h ' + minutes.toString() + 'min ' + seconds.toString() + 'sec';
} else if(minutes !== 0){
    result_string = minutes.toString() + 'min ' + seconds.toString() + 'sec';
} else if(seconds !== 0){
    result_string = seconds.toString() + 'sec';
} else {
    // always provide a display value - do not return null
    result_string = '0sec';
}
return result_string;

Note: The script has to return a value in any situation – it must not return null, otherwise there can be issues with the client tool. E.g. Analyzer doesn’t display all the results properly if null is returned.

Important: When adding the CellFormatter make sure that you removed the formatString attribute from the Measure or CalculatedMeasure XML Element, otherwise this attribute will take precedence over the CellFormatter.

Amazing isn’t it? If I had only known about this feature earlier on! A big thanks to Matt Campbell for pointing out that Mondrian has a Cell Formatter.

Advertisements

Pentaho Mondrian: The MDX Generate Function


Repost from http://diethardsteiner.github.io/cde/2015/04/23/MDX-Generate-Function.html

This is a brief overview of how you can use the MDX GENERATE() function. All the examples below work with the SteelWheelsSales Cube, which ships with the Pentaho BA Server. Try the examples listed below either with Pentaho Analyzer, the Saiku CE plugin, Pivot4J or Roland Bouman’s Pentaho Analysis Shell (Pash) (The last 3 ones are plugins, which you can download via the Pentaho Marketplace).

The GENERATE() function has two different applications:

  • If the second parameter is a set, it will return the members that exist in both sets ( a UNION() of the sets). You can think of it as a kind of for-each function which checks if members in the first set exist in the second one. ALL can be used as a third parameter to keep any duplicates.
  • If the second parameter is a string expression then the members will be concatenated.

Examples:

Find the members that are in both sets:

SELECT
    [Measures].[Sales] ON 0
    , NON EMPTY GENERATE(
        {[Markets].[Country].[Australia], [Markets].[Country].[USA]}
        , [Markets].[Country].[Australia]
    ) ON 1
FROM [SteelWheelsSales]
Country Sales
Australia 630,623

In this case Australia survives, because it is a member of the first as well as the second set.

For each member of the first set retrieve the first child:

SELECT
    [Measures].[Sales] ON 0
    , NON EMPTY GENERATE(
        {[Markets].[Country].[Australia], [Markets].[Country].[USA]}
        , [Markets].currentMember.firstChild
    ) ON 1
FROM [SteelWheelsSales]
State Province Sales
NSW 305,567
CA 1,505,542

Next we’d like to know the top performing country within each territory:

SELECT
    [Measures].[Sales] ON 0
    , NON EMPTY GENERATE(
        [Markets].[Territory].Members
        , TOPCOUNT([Markets].CurrentMember.Children, 1, [Measures].[Sales])
    ) ON 1
FROM [SteelWheelsSales]
Country Sales
Australia 630623
Spain 1215687
Japan 188168
USA 3627983

Taking the previous example a bit further, we can get the top performing country and customer combination based on sales for each territory:

SELECT
    [Measures].[Sales] ON 0
    , NON EMPTY GENERATE(
        [Markets].[Territory].Members
        , TOPCOUNT([Markets].CurrentMember.Children * [Customers].[Customer].Members, 1, [Measures].[Sales])
    ) ON 1
FROM [SteelWheelsSales]
Country Customer Sales
Australia Australian Collectors, Co. 200,995
Spain Euro+ Shopping Channel 912,294
Singapore Dragon Souveniers, Ltd. 172,990
USA Mini Gifts Distributors Ltd. 654,858

There is also an option to retain duplicates in the results using the ALL flag as the third argument:

SELECT
    [Measures].[Sales] ON 0
    , NON EMPTY GENERATE(
        {[Markets].[Country].[Australia], [Markets].[Country].[Australia]}
        , [Markets].currentMember.firstChild
        , ALL
    ) ON 1
FROM [SteelWheelsSales]
State Province Sales
NSW 305,567
NSW 305,567

Now let’s have a look at a completely different way we can use the GENERATE() function:

Let’s show the territories with all their countries next to each other in one line. We can define a delimiter as the third parameter of the GENERATE() function:

WITH 
MEMBER [Measures].[Countries] AS
    GENERATE(
            [Markets].CurrentMember.Children
            , [Markets].CurrentMember.Name
            , "-"
        )
SELECT
    {[Measures].[Countries]} ON 0
    , NON EMPTY [Markets].[Territory].Members ON 1
FROM [SteelWheelsSales]
Territory Countries
#null Germany-Ireland-Israel-Netherlands-Poland-Portugal-Russia-Singapore-South Africa-Spain-Switzerland
APAC Australia-New Zealand-Singapore
EMEA Austria-Belgium-Denmark-Finland-France-Germany-Ireland-Italy-Norway-Spain-Sweden-Switzerland-UK
Japan Hong Kong-Japan-Philippines-Singapore
NA Canada-USA

As mentioned earlier, this is just a brief intro the extremely useful GENERATE() function. I hope that the example gave you some ideas on how to use this function.