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Last modified by Helena on 2025/09/10 11:19
From version 6.8
edited by Helena
on 2025/05/16 12:37
Change comment: There is no comment for this version
To version 6.5
edited by Helena
on 2025/05/16 12:34
Change comment: There is no comment for this version

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... ... @@ -419,6 +419,7 @@
419 419  
420 420  ‘DF1(1.0.0)/POPULATION.CANADA’ :=
421 421  DF1(1.0.0) [ sub INDICATOR=“POPULATION”, COUNTRY=“CANADA” ];
422 +
422 422  … … …
423 423  
424 424  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}}
... ... @@ -431,7 +431,8 @@
431 431  
432 432  This is equivalent to the application of the VTL “sub” operator only to the identifier //INDICATOR//:
433 433  
434 -[[image:1747388244829-693.png]]
435 +‘DF1(1.0.0)/POPULATION.’ :=
436 +DF1(1.0.0) [ sub INDICATOR=“POPULATION” ];
435 435  
436 436  Therefore the VTL Data Set ‘DF1(1.0.0)/POPULATION.’ would have the identifiers COUNTRY and TIME_PERIOD.
437 437  
... ... @@ -458,18 +458,51 @@
458 458  
459 459  Some examples follow, for some specific values of INDICATOR and COUNTRY:
460 460  
461 -[[image:1747388222879-916.png]]
463 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ <- expression11; ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ <- expression12;
462 462  
463 -[[image:1747388206717-256.png]]
465 +… … …
466 +‘DF2(1.0.0)/POPGROWTH.USA’ <- expression21;
467 +‘DF2(1.0.0)/POPGROWTH.CANADA’ <- expression22;
468 +… … …
464 464  
465 465  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:
466 466  
467 -[[image:1747388148322-387.png]]
472 +VTL dataset INDICATOR value COUNTRY value
468 468  
474 +‘DF2(1.0.0)/GDPPERCAPITA.USA’ GDPPERCAPITA USA
475 +
476 +‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ GDPPERCAPITA CANADA … … …
477 +
478 +‘DF2(1.0.0)/POPGROWTH.USA’ POPGROWTH USA
479 +
480 +‘DF2(1.0.0)/POPGROWTH.CANADA’ POPGROWTH CANADA
481 +
482 +… … …
483 +
469 469  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:
470 470  
471 -[[image:1747388179021-814.png]]
486 +DF2bis_GDPPERCAPITA_USA := ‘DF2(1.0.0)/GDPPERCAPITA.USA’ [calc identifier INDICATOR := ”GDPPERCAPITA”, identifier COUNTRY := ”USA”];
472 472  
488 +DF2bis_GDPPERCAPITA_CANADA := ‘DF2(1.0.0)/GDPPERCAPITA.CANADA’ [calc identifier INDICATOR:=”GDPPERCAPITA”, identifier COUNTRY:=”CANADA”]; … … …
489 +
490 +DF2bis_POPGROWTH_USA := ‘DF2(1.0.0)/POPGROWTH.USA’
491 +
492 +[calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”USA”];
493 +
494 +DF2bis_POPGROWTH_CANADA’ := ‘DF2(1.0.0)/POPGROWTH.CANADA’ [calc identifier INDICATOR := ”POPGROWTH”, identifier COUNTRY := ”CANADA”]; … … …
495 +
496 +DF2(1.0) <- UNION (DF2bis_GDPPERCAPITA_USA’,
497 +
498 +DF2bis_GDPPERCAPITA_CANADA’,
499 +
500 +… ,
501 +
502 +DF2bis_POPGROWTH_USA’,
503 +
504 +DF2bis_POPGROWTH_CANADA’
505 +
506 +…);
507 +
473 473  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
474 474  
475 475  DF2bis_GDPPERCAPITA_USA and so on) by adding the identifiers INDICATOR and COUNTRY with the desired values (//INDICATORvalue// and //COUNTRYvalue)//. Finally, all these non-persistent Data Sets are united and give the final result DF2(1.0){{footnote}}The result is persistent in this example but it can be also non persistent if needed.{{/footnote}}, which can be mapped one-to-one to the homonymous SDMX Dataflow having the dimension components TIME_PERIOD, INDICATOR and COUNTRY.
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