Skip to Content
Last modified by Helena on 2025/09/10 11:19
From version 6.9
edited by Helena
on 2025/05/16 12:37
Change comment: There is no comment for this version
To version 6.7
edited by Helena
on 2025/05/16 12:35
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -414,8 +414,13 @@
414 414  
415 415  It should be noted that the desired VTL Data Sets (i.e. of the kind ‘DF1(1.0.0)/// INDICATORvalue//.//COUNTRYvalue//’) can be obtained also by applying the VTL operator “**sub**” (subspace) to the Dataflow DF1(1.0.0), like in the following VTL expression:
416 416  
417 -[[image:1747388275998-621.png]]
417 +‘DF1(1.0.0)/POPULATION.USA’ :=
418 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA” ];
418 418  
420 +‘DF1(1.0.0)/POPULATION.CANADA’ :=
421 +DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
422 +… … …
423 +
419 419  In fact the VTL operator “sub” has exactly the same behaviour. Therefore, mapping different parts of a SDMX Dataflow to different VTL Data Sets in the direction from SDMX to VTL through the ordered concatenation notation is equivalent to a proper use of the operator “**sub**” on such a Dataflow.{{footnote}}In case the ordered concatenation notation is used, the VTL Transformation described above, e.g. ‘DF1(1.0)/POPULATION.USA’ := DF1(1.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“USA”], is implicitly executed. In order to test the overall compliance of the VTL program to the VTL consistency rules, it has to be considered as part of the VTL program even if it is not explicitly coded.{{/footnote}}
420 420  
421 421  In the direction from SDMX to VTL it is allowed to omit the value of one or more
... ... @@ -426,7 +426,8 @@
426 426  
427 427  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
428 428  
429 -[[image:1747388244829-693.png]]
434 +‘DF1(1.0.0)/POPULATION.’ :=
435 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
430 430  
431 431  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
432 432  
... ... @@ -453,17 +453,36 @@
453 453  
454 454  Some examples follow, for some specific values of INDICATOR and COUNTRY:
455 455  
456 -[[image:1747388222879-916.png]]
462 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
457 457  
458 -[[image:1747388206717-256.png]]
464 +… … …
465 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
466 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
467 +… … …
459 459  
460 460  As said, it is assumed that these VTL derived Data Sets have the TIME_PERIOD as the only identifier. In the mapping from VTL to SMDX, the Dimensions INDICATOR and COUNTRY are added to the VTL data structure on order to obtain the SDMX one, with the following values respectively:
461 461  
462 -[[image:1747388148322-387.png]]
471 +VTL dataset INDICATOR value COUNTRY value
463 463  
473 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
474 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
475 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
476 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
477 +… … …
478 +
464 464  It should be noted that the application of this many-to-one mapping from VTL to SDMX is equivalent to an appropriate sequence of VTL Transformations. These use the VTL operator “calc” to add the proper VTL identifiers (in the example, INDICATOR and COUNTRY) and to assign to them the proper values and the operator “union” in order to obtain the final VTL dataset (in the example DF2(1.0.0)), that can be mapped oneto-one to the homonymous SDMX Dataflow. Following the same example, these VTL Transformations would be:
465 465  
466 -[[image:1747388179021-814.png]]
481 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
482 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
483 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
484 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
485 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
486 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
487 +DF2bis_GDPPERCAPITA_CANADA’,
488 +… ,
489 +DF2bis_POPGROWTH_USA’,
490 +DF2bis_POPGROWTH_CANADA’
491 +…);
467 467  
468 468  In other words, starting from the datasets explicitly calculated through VTL (in the example ‘DF2(1.0)/GDPPERCAPITA.USA’ and so on), the first step consists in calculating other (non-persistent) VTL datasets (in the example
469 469  
1747388148322-387.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -23.0 KB
Content
1747388179021-814.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -66.2 KB
Content
1747388206717-256.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -10.3 KB
Content
1747388222879-916.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -9.9 KB
Content
1747388244829-693.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -7.4 KB
Content
1747388275998-621.png
Author
... ... @@ -1,1 +1,0 @@
1 -XWiki.helena
Size
... ... @@ -1,1 +1,0 @@
1 -19.2 KB
Content