[SPARK-45552][PS] Introduce flexible parameters to assertDataFrameEqual
#43433
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cc @HyukjinKwon @allanf-db FYI |
itholic
changed the title
assertDataFrameEqualassertDataFrameEqual
itholic
changed the title
assertDataFrameEqualassertDataFrameEqual
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Gentle reminder for @HyukjinKwon as CI passed. Also cc @ueshin @zhengruifeng |
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| ignoreColumnOrder: bool = False, | ||
| ignoreColumnName: bool = False, | ||
| ignoreColumnType: bool = False, |
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have we considered ignoreSchema?
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It sounds worth to have it for some scenarios. Let's discuss in the separate thread!
HyukjinKwon
approved these changes
Oct 30, 2023
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Merged to master. |
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What changes were proposed in this pull request?
This PR proposes to add six new parameters to the
assertDataFrameEqual:ignoreNullable,ignoreColumnOrder,ignoreColumnName,ignoreColumnType,maxErrors, andshowOnlyDiffto provide users with more flexibility in DataFrame testing.Why are the changes needed?
To enhance the utility of
assertDataFrameEqualby accommodating various common DataFrame comparison scenarios that users might encounter, without necessitating manual adjustments or workarounds.Does this PR introduce any user-facing change?
Yes.
assertDataFrameEqualnow have the option to use the six new parameters:When set to True (default), the nullable property of the columns being compared is not taken into account and the columns will be considered equal even if they have different nullable settings.
When set to False, columns are considered equal only if they have the same nullable setting.
When set to False (default), columns are compared in the order they appear in the DataFrames.
When set to True, a column in the expected DataFrame is compared to the column with the same name in the actual DataFrame.
ignoreColumnOrder cannot be set to True if ignoreColumnNames is also set to True.
When set to False (default), column names are checked and the function fails if they are different.
When set to True, the function will succeed even if column names are different. Column data types are compared for columns in the order they appear in the DataFrames.
ignoreColumnNames cannot be set to True if ignoreColumnOrder is also set to True.
When set to False (default), column data types are checked and the function fails if they are different.
When set to True, the schema equality check will succeed even if column data types are different and the function will attempt to compare rows.
When this number of row comparisons have failed, the function returns independent of how many rows have been compared.
Set to None by default which means compare all rows independent of number of failures.
If set to False (default), the error message will include all rows (when there is at least one row that is different).
How was this patch tested?
Added usage examples into doctest for each parameter.
Was this patch authored or co-authored using generative AI tooling?
No.