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Release 1.x.x

Version 1.12.0 - 08/25/25​

(See technical release on Github)

  • Improve vtl-prov module

Version 1.11.0 - 08/03/25​

(See technical release on Github)

  • Implement pivot
  • Support boolean and date for min/max in aggregation

Version 1.10.0 - 07/21/25​

(See technical release on Github)

  • Fix Spark issue to optimize the construction of a dataset
  • Fix provenance issue with validation

Version 1.9.0 - 05/26/25​

(See technical release on Github)

  • Upgrade to Java 17

Version 1.8.0 - 11/12/24​

(See technical release on Github)

  • Improve Provenance module

Version 1.7.0 - 10/09/24​

(See technical release on Github)

  • Upgrade to version 2.1 of VTL

Version 1.6.0 - 10/07/24​

(See technical release on Github)

  • Add provenance module

Version 1.5.0 - 06/28/24​

(See technical release on Github)

  • Requires Java 8 or above

Version 1.4.1 - 06/25/24​

(See technical release on Github)

  • Fix VTL SDMX module visibility

Version 1.4.0 - 06/07/24​

(See technical release on Github)

  • Support temporal operators
  • Add VTL CSV module
  • Add VTL SDMX module

Version 1.3.0 - 01/17/24​

(See technical release on Github)

  • Fix Analytics implementations when operators are applied to datasets

Version 1.2.0 - 11/22/23​

(See technical release on Github)

  • Java 17 support
  • Persistent assignments (<-)

Version 1.1.1 - 09/09/23​

(See technical release on Github)

  • Fix check_hierarchy issues: serialization and possibility to return empty dataset

Version 1.1.0 - 09/01/23​

(See technical release on Github)

  • Validation: define hierarchical ruleset, check_hierarchy

Version 1.0.2 - 06/30/23​

(See technical release on Github)

  • Split VTL engine method registrations with 2 methods: registerMethod and registerGlobalMethod
  • Fix in / not_in bug with null

Version 1.0.1 - 05/23/23​

(See technical release on Github)

  • Fix Spark serialization issue in check_datapoint implementation

Version 1.0.0 - 05/12/23​

(See technical release on Github)

  • Membership: #
  • Validation: check, check_datapoint
  • Dataset operators (ceil(ds), ds1 < ds2, mod(ds, 5), ...)
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