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[SPARK-15125][SQL] Changing CSV data source mapping of empty quoted strings in the data to empty strings instead of null #12904
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sureshthalamati
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This patch adds boolean option emptyAsNull to CSV datasource for user…
sureshthalamati b128fbb
Adding emptyValue option to will allow user to speify the mapping for…
sureshthalamati c7aa4aa
Merge remote-tracking branch 'upstream/master' into empstring_fix_spa…
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| col1,col2 | ||
| 1,"-" | ||
| 2,"" | ||
| 3, | ||
| 4,"A" |
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When
nullValueandemptyValueare both""in default, don't they conflict?Uh oh!
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+1 for documenting the explicit precedence
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Yes, null and empty can not be differentiated when they are set to same value. Currently null value check has higher precedence than the empty value.
input.csv
1,
2,””
Output will be:
1, null
2, null
I think this behavior is ok. By default Univocity CSV parser used in spark also returns null for empty strings.
I agree we should document this behavior.