Difference between revisions of "Datamart DSL"

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Introduction

MDX (MultiDimensional eXpressions)

MDX is a query language for OLAP databases, much like SQL is a query language for relational databases. It is also a calculation language, with syntax similar to spreadsheet formulas.

MDX has several elements that are used by, or influence, most statements:

• Identifiers - Identifiers are the names of objects such as cubes, dimensions, members, and measures, e.g. [Time], [Measures].
• Data Types - Define the types of data that are contained by cells, member properties, and cell properties. (details see Section #Data types )
• Expressions (MDX) - An expression is a combination of identifiers, values, and operators. You can use an expression as part of the data to be retrieved by a query or as a search condition to look for data that meets a set of criteria. Expressions include functions that return a single value, a set expression, e.g. [Measures].[Discount Amount] * 1.5.
• Operators - Operators are syntax elements that work with one or more simple MDX expressions to make more complex MDX expressions, e,g, +,-,*,/, <, >, AND, OR etc.
• Functions - Functions are syntax elements that take zero, one, or more input values, and return a scalar value or an object, e.g. .Dimension, .Level , IsEmpty(),Order(), .CurrentMember etc.
• Comments - Comments are pieces of text that are inserted into MDX statements or scripts to explain the purpose of the statement. MDX supports //, -- and /* ... */ as commenting characters.
• Reserved Keywords - Reserved keywords are words that are reserved for the use of MDX and should not be used for object names used in MDX statements, e.g. SELECT, WHERE etc.

Data types

There are six primary data types in MDX:

Basic Syntax of MDX query

► Syntax:

-- One of the three ways to write comments
SELECT {set 0} on COLUMNS, /* block comment */
  {set 1} on ROWS // line comment
  ...
  {set n} on AXIS(n)
FROM [cube]
WHERE (tuple) // called "slicer dimension"

Note: Key differences between MDX and SQL

• “Cube in, Cube out” for MDX.
• set notation needs to be used after SELECT.
• FROM clause can name only one cube
• The WHERE clause describes the slicer axis (i.e., all the axes that is not a query axis) and is filtered by its default members

Examples

A typical query

► Example:

SELECT {[Time].[Calendar].[Year].[2013], 
   [Time].[Calendar].[Year].[2014]} ON COLUMNS,
  {[Store].[Store Name].MEMBERS} ON ROWS
FROM [Sales]
WHERE ([Measures].[Store Sales])

.MEMBERS and .CHILDREN functions

► Syntax:

Hierarchy.Members
Level.Members
...
Member.Children

Notes:

• .Members returns the set of members in a dimension, level, or hierarchy.
• .Children returns the set of children of a specified member.

► Example:

SELECT {[Time].[Calendar].[Year].[2014].CHILDREN} ON COLUMNS,
  {[Store].[Store City].MEMBERS} ON ROWS
FROM [Sales]
WHERE ([Measures].[Store Sales])

Calculate Member

► Syntax:

WITH MEMBER parent1.name1 AS ’expression1’
  MEMBER parent2.name2 AS ’expression2’

Notes:

• If a calculated member is only required for a single MDX query, you can define that calculated member by using the “WITH” keyword. A calculated member that is created by using the “WITH” keyword no longer exists after the query has finished running.

► Example 1:

WITH MEMBER [Time].[Calendar].[Year].[2014].[H1] AS
’[Time].[Calendar].[Year].[2014].[Q1] + [Time].[Calendar].[Year].[2014].[Q2]’
MEMBER [Time].[Calendar].[Year].[2014].[H2] AS
’[Time].[Calendar].[Year].[2014].[Q3] + [Time].[Calendar].[Year].[2014].[Q4]’
SELECT {[Time].[Calendar].[Year].[2014].[H1], 
   [Time].[Calendar].[Year].[2014].[H2]} ON COLUMNS
  [Store].[Store Name].MEMBERS ON ROWS
FROM [Sales]
WHERE ([Measures].[Profit])

► Example 2: define and use new measures

WITH MEMBER [Measures].[ProfitPercent] AS
’([Measures].[Store Sales] – [Measures].[Store Cost]) / ([Measures].[Store Cost])’
SELECT [Time].[Calendar].[Year].[2014].CHILDREN ON COLUMNS,
 [Store].[Store Name].MEMBERS ON ROWS
FROM [Sales]
WHERE ([Measures].[ProfitPercent])

Slicer Dimension

► Example: Slice on the [Product] dimension

SELECT {[Time].[Calendar].[Year].[2014].CHILDREN} ON COLUMNS,
  {[Store].[Store City].MEMBERS} ON ROWS
FROM [Sales]
WHERE ([Product].[Product Family].[Drink],
[Measures].[Store Sales])

Filter() function

► Syntax:

FILTER(set, logical expression )

Notes:

• Returns the set that results from filtering a specified set based on a search condition.

► Example: If we are only interested in stores whose 2014 unit sales exceed 1000

SELECT {[Time].[Calendar].[Year].[2014].CHILDREN} ON COLUMNS,
   FILTER( {[Store].[Store City].MEMBERS},
           ([Measures].[Unit Sales], [Time].[Calendar].[Year].[2014]) > 1000 ) ON ROWS
FROM [Sales]
WHERE ([Measures].[Store Sales])

Order() function

► Syntax:

ORDER(set, numeric/string expression, [, ASC | DESC | BASC | BDESC]

Notes:

• Arranges members of a specified set, optionally preserving or breaking the hierarchy.

► Example 1: List all measures for each city in decreasing order of their sales count

SELECT [Measures].MEMBERS ON COLUMNS,
    ORDER(
        [Store].[Store City].MEMBERS,
        [Measures].[Sales Count], 
        BDESC
    ) ON ROWS
FROM [Sales]

► Example 2: If we are only interested in stores whose name is between “Berlin” and “Heidelberg”

SELECT [Measures].MEMBERS ON COLUMNS,
    ORDER(
        {[Store].[Store City].[Berlin]:[Heidelberg]},
        [Store].CURRENTMEMBER.Name,
        BASC
    ) ON ROWS
FROM [Sales]

Lag() function

► Syntax:

Member.LAG(index)

Notes:

• returns the member that is a specified number of positions before a specified member at the member's level.
• .Lag(1) is equivalent to the .PrevMember function.
• .Lag(-1) is equivalent to the .NextMember function.

► Example: list all measures for December 2014

SELECT [Measures].MEMBERS ON COLUMNS,
       [Time].[Fiscal].[Month].[February 2015].LAG(2) ON ROWS
FROM [Sales]

Lead() function

► Syntax:

Member.LEAD(index)

Notes:

• returns the member that is a specified number of positions following a specified member at the member's level.
• .Lead(n) is equivalent to .Lag(-n) function.

► Example: list all measures for December 2014

SELECT  [Measures].MEMBERS ON COLUMNS,
        [Time].[Fiscal].[Month].[February 2015].LEAD(-2) ON ROWS
FROM [Sales]

PrevMember function

► Syntax:

Member.PREVMEMBER

Notes:

• the previous member in the level that contains a specified member.

► Example: list all measures for January 2014

SELECT  [Measures].MEMBERS ON COLUMNS,
        [Time].[Fiscal].[Month].[February 2015].PREVMEMBER ON ROWS
FROM [Sales]

NextMember function

► Syntax:

Member.NEXTMEMBER

Notes:

• Returns the next member in the level that contains a specified member.

► Example: list all measures for March 2015

SELECT  [Measures].MEMBERS ON COLUMNS,
        [Time].[Fiscal].[Month].[February 2015].NEXTMEMBER ON ROWS
FROM [Sales]

FirstChild function

► Syntax:

Member.FIRSTCHILD

Notes:

• Returns the first child of a specified member.
• Leaf members have no children and therefore no first child.

► Example: list all measures for first quarter of 2015, which is the first child of year 2015

SELECT  [Measures].MEMBERS ON COLUMNS,
        [Time].[Calendar].[Year].[2015].FIRSTCHILD ON ROWS
FROM [Sales]

LastChild function

► Syntax:

Member.LASTCHILD

Notes:

• Returns the last child of a specified member.
•  Leaf members have no children and therefore no last child.

► Example: list all measures for march 2015, which is the last child of first quarter of year 2015

SELECT  [Measures].MEMBERS ON COLUMNS,
        [Time].[Calendar].[Quarter].[Q1 2015].LASTCHILD ON ROWS
FROM [Sales]

Head() function

► Syntax:

HEAD(set [ ,count ] )

Notes:

• returns the first specified number of elements in a set.

► Example: show the profit of top-5 cities in terms of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    HEAD( ORDER( {[Store].[Store City].MEMBERS},
                [Measures].[Sales Count],
                BDESC 
               ), 
          5
        ) ON ROWS
FROM [Sales]

Tail() function

► Syntax:

TAIL(set [ ,count ] )

Notes:

• returns a subset from the end of a set.

► Example: show the profit of bottom-5 cities in terms of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    TAIL( ORDER( {[Store].[Store City].MEMBERS},
                [Measures].[Sales Count],
                BDESC 
               ), 
          5
        ) ON ROWS
FROM [Sales]

TopCount() function

► Syntax:

TOPCOUNT(set, count [ ,numeric expression ] )

Notes:

• Sorts a set in descending order and returns the specified number of elements with the highest values.
• The numeric expression is used to evaluate the tuple values. If a numeric expression is not specified, the function returns the set of members in a natural order, without any sorting, behaving like Head() function.

► Example: show the profit of top-5 cities in terms of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    TOPCOUNT( [Store].[Store City].MEMBERS,
                5,
                [Measures].[Sales Count]
            ) ON ROWS
FROM [Sales]

BottomCount() function

► Syntax:

BOTTOMCOUNT(set, count [ ,numeric expression ] )

Notes:

• Sorts a set in ascending order, and returns the specified number of tuples in the specified set with the lowest values.
• If a numeric expression is not specified, the function returns the set of members in a natural order, without any sorting, behaving like Tail() function.

► Example: show the profit of bottom-5 cities in terms of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    BOTTOMCOUNT( [Store].[Store City].MEMBERS,
                5,
                [Measures].[Sales Count]
            ) ON ROWS
FROM [Sales]

TopPercent() function

► Syntax:

TOPPERCENT(set, percentage, numeric expression)

Notes:

• Sorts a set in descending order, and returns a set of tuples with the highest values whose cumulative total is equal to or greater than a specified percentage.
•  Percentage must be a positive value between 0 and 100.

► Example: show the best profit and cities that make the top 10% of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    TOPPERCENT( [Store].[Store City].MEMBERS,
                10,
                [Measures].[Sales Count]
            ) ON ROWS
FROM [Sales]

BottomPercent() function

► Syntax:

BOTTOMPERCENT(set, percentage, numeric expression)

Notes:

• Sorts a set in ascending order, and returns a set of tuples with the lowest values whose cumulative total is equal to or greater than a specified percentage.
• Percentage must be a positive value between 0 and 100.

► Example: show the worst profit and cities that make the bottom 10% of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    BOTTOMPERCENT( [Store].[Store City].MEMBERS,
                    10,
                    [Measures].[Sales Count]
                 ) ON ROWS
FROM [Sales]

TopSum() function

► Syntax:

TOPSUM(set, value, numeric expression)

Notes:

• Sorts a set and returns the topmost elements whose cumulative total is at least a specified value.

► Example: show the smallest set of whose cumulative total using the profit measure is at least the sum of 50000, beginning with the members of this set with the largest number of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    TOPSUM ( [Store].[Store City].MEMBERS,
             50000,
             [Measures].[Sales Count]
           ) ON ROWS
FROM [Sales]

BottomSum() function

► Syntax:

BOTTOMSUM(set, value, numeric expression)

Notes:

• Sorts a set in ascending order and returns a set of tuples with the lowest values whose sum is equal to or less than a specified value.

► Example: Show the smallest set of whose cumulative total using the profit measure is at least the sum of 50000, beginning with the members of this set with the smallest number of sales count

SELECT [Measures].[Profit] ON COLUMNS,
    BOTTOMSUM( [Store].[Store City].MEMBERS,
               50000,
               [Measures].[Sales Count]
             ) ON ROWS
FROM [Sales]

Aggregate() function

► Syntax:

AGGREGATE(set [, numeric expression])

Notes:

• Returns a number that is calculated by aggregating over the cells returned by the set expression.
• If a numeric expression is not provided, this function aggregates each measure within the current query context by using the default aggregation operator that is specified for each measure.
• If a numeric expression is provided, this function first evaluates, and then sums, the numeric expression for each cell in the specified set.

► Example: aggregate profit for all the calendar months

WITH MEMBER [Time].[Calendar].[All sales] AS
    AGGREGATE([Time].[Calendar].[Month].MEMBERS, [Measures].[Amount])
SELECT [Time].[Calendar].[All sales] ON COLUMNS,
  [Store].[Store City].MEMBERS ON ROWS
FROM [Sales]
WHERE [Measures].[Profit]

Avg() function

► Syntax:

AVG(set [, numeric expression])

Notes:

• Evaluates a set and returns the average of the non-empty values of the cells in the set, averaged over the measures in the set or over a specified measure.

► Example: show the average profit for each calendar year

WITH MEMBER [Measures].[Avg Profit] AS
      AVG( [Time].[Calendar].[Month].MEMBERS, Measures.[Profit])
SELECT
      Measures.[Avg Profit] ON COLUMNS,
      [Time].[Calendar].[Year].MEMBERS ON ROWS
FROM  [Sales]

Sum() function

► Syntax:

SUM(set [, numeric expression])

Notes:

• Show the sum of profit for all members of the [Product].[Category] hierarchy for calendar years 2013 and 2014

► Example: show the average profit for each calendar year

WITH MEMBER [Measures].[Sum Profit] AS 
        SUM( { [Time].[Calendar].[Year].[2013],
               [Time].[Calendar].[Year].[2014] }
           , [Measures].[Profit]
           )
SELECT [Measures].[Sum Profit] ON COLUMNS,
         [Product].[Category].Members ON ROWS
FROM [Sales]

StdDev() function

► Syntax:

STDDEV(set [, numeric expression])

Notes:

• returns the sample standard deviation of a numeric expression evaluated over a set, using the unbiased population formula (dividing by n-1).

► Example: Show the standart deviation of profit, evaluated over the first 3 months of calendar years 2014, using the unbiased population formula

WITH MEMBER [Measures].[Stddev Profit] AS 
	STDDEV( { [Time].[Calendar].[Month].[January 2014],
               [Time].[Calendar].[Month].[February 2014],
               [Time].[Calendar].[Month].[March 2014]}
           , [Measures].[Profit]
	   )

PeriodsToDate() function

► Syntax:

PERIODSTODATE([level [, member]])

Notes:

• returns a set of sibling members from the same level as a given member, starting with the first sibling and ending with the given member, as constrained by a specified level in the Time dimension.
• If the member expression is missing, then the level hierarchy.CurrentMember will be used.
• If level expression is missing, the parent level of the [Time].CurrentMember in the default time dimension of the cube will be used.

► Example: aggregate profit for first 8 calendar months of year 2014

WITH MEMBER [Time].[Calendar].[first8Months2014] AS
    AGGREGATE (
        PERIODSTODATE(  [Time].[Calendar].[Year], 
                        [Time].[Calendar].[Month].[August 2014],
                     )
              )		
SELECT [Time].[Calendar].[All sales] ON COLUMNS,
    [Store].[Store City].MEMBERS ON ROWS
FROM [Sales]
WHERE [Measures].[Profit]

YTD() function

► Syntax:

YTD([member])

Notes:

• returns a set of sibling members from the same level as a given member, starting with the first sibling and ending with the given member, as constrained by the Year level in the Time dimension.
• Ytd(member) is equivalent to PeriodsToDate(Year level, member).
• if no member is defined, then [Time].currentMember is used.
• this function will not work when the Type property is set to FiscalYears.

► Example: aggregate profit for first 8 calendar months of year 2014

WITH MEMBER [Time].[Calendar].[first8Months2014] AS
    AGGREGATE (
                YTD( [Time].[Calendar].[Month].[August 2014] )
              )		
SELECT [Time].[Calendar].[All sales] ON COLUMNS,
    [Store].[Store City].MEMBERS ON ROWS
FROM [Sales]
WHERE [Measures].[Profit]

CROSSJOIN() function

► Syntax:

CROSSJOIN(set1, set2)

Notes:

• Returns the cross product of one or more sets.

► Example: the query axis (ROWS) is the combination of 2 cube dimensions

SELECT [Time].[Calendar].[Year].[2014].CHILDREN ON COLUMNS,
    CROSSJOIN( [Store].[Store State].MEMBERS,
                [Product].[Product Family].MEMBERS
             ) ON ROWS
FROM [Sales]
WHERE ([Measures].[Profit])

NonEmpty() function

► Syntax:

NONEMPTY(set1 [,set2])

Notes:

• returns the set of tuples that are not empty from a specified set, based on the cross product of the specified set with a second set.

► Example:

SELECT [Time].[Calendar].[Year].[2014].CHILDREN ON COLUMNS,
    NONEMPTY(
        CROSSJOIN( [Store].[Store State].MEMBERS,
                   [Product].[Product Family].MEMBERS
                 )
            ) ON ROWS
FROM [Sales]
WHERE ([Measures].[Profit])

NonEmptyCrossjoin() function

► Syntax:

NONEMPTYCROSSJOIN(set1 [,set2, . . .][, count])

Notes:

• returns a set that contains the cross product of one or more sets, excluding empty tuples and tuples without associated fact table data.
• If count is not specified, the function cross joins all specified sets and excludes empty members from the resulting set.
• If a number of sets is specified, the function cross joins the numbers of sets specified, starting with the first specified set.

► Example:

SELECT [Time].[Calendar].[Year].[2014].CHILDREN ON COLUMNS,
    NONEMPTYCROSSJOIN( [Store].[Store State].MEMBERS,
                       [Product].[Product Family].MEMBERS
                     ) ON ROWS
FROM [Sales]
WHERE ([Measures].[Profit])

Except() function

► Syntax:

EXCEPT(set1 ,set2 [, ALL])

Notes:

• Evaluates two sets and removes those tuples in the first set that also exist in the second set, duplicates are removed.
• If ALL is specified, the function retains duplicates found in the first set; duplicates found in the second set will still be removed. The members are returned in the order they appear in the first set.

► Example:

SELECT [Time].[Calendar].[Month].CHILDREN ON COLUMNS,
    EXCEPT( [Product].[Product Categories].[All].Children ,
            {[Product].[Product Categories].[Components]}
          ) ON ROWS
FROM [Sales]
WHERE ([Measures].[Profit])

Jboss JBPM 5.4

jBPM is a flexible Business Process Management (BPM) Suite. It allows you to model, execute and monitor business processes, throughout their life cycle.

jBPM focuses on executable business process, which are business processes that contain enough detail so they can actually be executed on a BPM engine. Executable business processes bridge the gap between business users and developers as they are higher-level and use domain-specific concepts that are understood by business users but can also be executed directly.

To interact with the process engine (for example, to start a process), you need to set up a session. This session will be used to communicate with the process engine. A session needs to have a reference to a knowledge base, which contains a reference to all the relevant process definitions. This knowledge base is used to look up the process definitions whenever necessary. To create a session, you first need to create a knowledge base, load all the necessary process definitions (this can be from various sources, like from classpath, file system or process repository) and then instantiate a session.

For example, imagine you are writing an application to process sales orders. You could then define one or more process definitions that define how the order should be processed. When starting up your application, you first need to create a knowledge base that contains those process definitions. You can then create a session based on this knowledge base so that, whenever a new sales order comes in, a new process instance is started for that sales order. That process instance contains the state of the process for that specific sales request.

The jBPM project has a clear separation between the API the users should be interacting with and the actual implementation classes. The public API exposes most of the features we believe "normal" users can safely use and should remain rather stable across releases. Expert users can still access internal classes but should be aware that they should know what they are doing and that the internal API might still change in the future.

As explained above, the jBPM API should thus be used to create a knowledge base that contains your process definitions, and to create a session to start new process instances, signal existing ones, register listeners, etc.

More information: http://docs.jboss.org/jbpm/v5.4/userguide/

Datamart DSL