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@lw-lin could you address @srowen's comments. Otherwise this is good to go.
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Github user lw-lin commented on the issue:
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@HyukjinKwon thanks for the information!
@srowen yea I still think this is good to go.
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Jenkins retest this please
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I support this PR. But just to make sure, I'd like to bring a reference.
It seems at least `na.strings` option in `read.csv` in R does as proposed
here,
```r
bt <- "A,B,C,D
Github user srowen commented on the issue:
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@lw-lin just checking that you think this is still good to go? @HyukjinKwon
do you have an opinion on the current state?
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retest this please
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> What if I am writing explicitly an empty string out? Does it become just
1,,2?
Yes. It becomes `1,,2` in 2.0, and the same `1,,2` with this patch -- no
behavior changes.
> Can you
Github user HyukjinKwon commented on the issue:
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I believe we can change the default vale of `nullValue` to
`'\u'.toString` in order to express any value is not `null`. I remember
this matches with no empty string nor any other string alth
Github user HyukjinKwon commented on the issue:
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@rxin Please let me leave my though why I thought it looks good to me in
case it is helpful.
Yes, but we should set `nullValue` for writing `null`. So, I think, setting
`""` for `nullVa
Github user rxin commented on the issue:
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What if I am writing explicitly an empty string out? Does it become just
1,,2?
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@rxin yes all empty (e.g. zero sized string) values become null values once
they are read back.
E.g. given `test.csv`:
```
1,,3,
```
`spark.read.csv("test.csv").show()` produc
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Also LGTM other than that major question.
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Github user rxin commented on the issue:
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With this change, do all empty (e.g. zero sized string) values become null
values once they are read back?
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Github user HyukjinKwon commented on the issue:
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This change looks good to me - I don't see any other reasons that `null`
should not be read for `Boolean`, `TimestampType`, `DateType` and `StringType`
inconsistently with other types.
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Github user srowen commented on the issue:
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CC @HyukjinKwon -- WDYT?
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Jenkins retest this please
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This is ready for review.
To summarize, this patch casts user-specified `nullValue`s to `null`s for
all supported types including the string type:
- this fixes the problem where null date
Github user devmanhinton commented on the issue:
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Just as a +1 would at least like the option to have `""` autocast to `null`
when read in from csv. Helpful for me in production given UDFs skip function
application when input is `null` but not
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Github user HyukjinKwon commented on the issue:
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BTW, this problem exists in the external CSV data source as well. The root
cause of https://github.com/databricks/spark-csv/issues/370 is this issue and
also if my understanding is correct, the
Github user djk121 commented on the issue:
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I'm doing this:
val dataframe = sparkSession.read
.format("com.databricks.spark.csv")
.option("header", "true")
.option("nullValue", "null")
.schema
Github user rxin commented on the issue:
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You can specify "com.databricks.spark.csv" as the source.
On Fri, Aug 5, 2016 at 11:58 PM, djk121 wrote:
> Is there a way to fall back to the old databricks csv library in spark 2
Github user djk121 commented on the issue:
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Is there a way to fall back to the old databricks csv library in spark 2.0
to work around this? Round-tripping worked there with .option("nullValue",
"null"), but I don't see a way to get round-tripp
Github user HyukjinKwon commented on the issue:
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This change looks reasonable to me.
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Github user lw-lin commented on the issue:
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@falaki could you take a look at the lasted update: [[bf01cea] StringType
should also respect
`nullValue`](https://github.com/apache/spark/pull/14118/commits/bf01cea8273f00386ceef6459f8b8fe2c169e12a)
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Github user falaki commented on the issue:
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@lw-lin thanks a lot for the clear summary.
After seeing some use cases, I think it is better to apply nullValue to all
types, including `StringType`. `treatEmptyValuesAsNulls` seems a special ca
Github user lw-lin commented on the issue:
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Here are some findings as I dug a little:
1. Since https://github.com/databricks/spark-csv/pull/102(Jul, 2015), we
would cast `""` as `null` for all types other than strings. For strings, `""
Github user deanchen commented on the issue:
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Would be great to get a resolution to this. We're running into issues in
production attempting to parse csv's with nullable dates. Personally prefer
option b for our use case.
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Github user lw-lin commented on the issue:
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I think @HyukjinKwon has made a good point: it's kind of strange null
strings can be written out, but can not be read back as nulls.
So for `StringType`:
nulls writ
Github user HyukjinKwon commented on the issue:
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IMHO, handling `StringType` at least lets users handling `null`s in
roundtrip in writing and reading. CSV writes `null` according to `nullValue`
[here](https://github.com/apache/spark/blob/38cf8
Github user rxin commented on the issue:
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Thanks for the information. I'm still confused. From an end-user
perspective, do we need to handle StringType there?
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