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With in a loop I have few dataframes created. I can union them with out an issue if they have same schema using (df_unioned = reduce(DataFrame.unionAll, df_list). Now my problem is how to union them if one of the dataframe in df_list has different nu...
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Hi,I have come across same scenario, using reduce() and unionByname we can implement the solution as below:val lstDF: List[Datframe] = List(df1,df2,df3,df4,df5)val combinedDF = lstDF.reduce((df1, df2) => df1.unionByName(df2, allowMissingColumns = tru...
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avenu
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I need to process files of different schema coming to different folders in ADLS using Autoloader. Do I need to start a separate read stream for each file type / folder or can this be handled using a single stream ?When I tried using a single stream, ...
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As you are talking about different schemas ,perhaps schemaevolutionmode, infercolumntypes, or schemahints may help?? Check out this- 32min onward - https://youtu.be/8a38Fv9cpd8 Hope it helps, do let know how you solve it if you can.
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Guys, good morning!I am writing the results of a json in a delta table, only the json structure is not always the same, if the field does not list in the json it generates type incompatibility when I append(dfbrzagend.write .format("delta") .mode("ap...
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Hi @Tássio Santos The delta table performs schema validation of every column, and the source dataframe column data types must match the column data types in the target table. If they don’t match, an exception is raised.For reference-https://docs.dat...
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What are the best practices for schema drift using Delta Live tables, in a scenario where the main source is a no sql database and we have a lot of changes in the schema?
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Hey there @Fernando Martin Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. We'd love to hear from...
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