SNOW-1830524 Add decoder logic for Dataframe.join
#2802
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| @@ -6,9 +6,10 @@ df2 = session.create_dataframe([[1, 2, 3, 4, 5]], schema=['\"A\"','\"B\"','\"C\" | |||
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| df3 = df1.filter(col("\"A\"") == 1).join(df2.select((col("\"A\"") + 1).as_("\"A\""), col("\"B\""), col("\"C\""), col("\"l_0001_C\""), col("\"l_0003_B\""))) | |||
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| df4 = df3.sort(df3.columns) | |||
| # Commented out since df3.columns produces different results in the first encoding and in the encode-decode-encode result. | |||
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Can you find out why this is happening? We shouldn't be removing valid test cases here. I don't see a reason why encode-decode-encode needs to be value equivalent, this is a good example, as long as they are semantically equivalent (the uniqueness of generated columns correspond correctly) that is all that is required.
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The unique columns correspond to each other in both cases but the values are different. I'm not sure what the best way around this is since hardcoding the decoder seems like a bad idea. I can add the test back in.
I'm not familiar with how the column names are generated but can try to figure that out.
…wflakedb/snowpark-python into vbudati/SNOW-1830524-decoder-df-join
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Which Jira issue is this PR addressing? Make sure that there is an accompanying issue to your PR.
Fixes SNOW-1830524
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Please describe how your code solves the related issue.
Added decoder logic for
Dataframe.join. All join tests should work now.