@Wenchen Fan Got your explanation, thanks! My understanding is that even if we create Spark tables using Spark's native data sources, by default, the metadata about these tables will be stored in the Hive metastore. As a consequence, a Hive upgrade can potentially affect Spark tables. For example, depending on the severity of the changes, the Hive metastore schema might change, which could require Spark code to be updated to handle these changes in how table metadata is represented. Is this assertion correct?
Thanks Mich Talebzadeh, Technologist | Architect | Data Engineer | Generative AI | FinCrime London United Kingdom view my Linkedin profile https://en.everybodywiki.com/Mich_Talebzadeh Disclaimer: The information provided is correct to the best of my knowledge but of course cannot be guaranteed . It is essential to note that, as with any advice, quote "one test result is worth one-thousand expert opinions (Werner Von Braun)". --------------------------------------------------------------------- To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
