[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-13 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
Given the existing logic below:

```
if (lowerCaseValue.equals("nan") ||
  lowerCaseValue.equals("infinity") ||
  lowerCaseValue.equals("-infinity") ||
  lowerCaseValue.equals("inf") ||
  lowerCaseValue.equals("-inf")) {
value.toFloat
```

It looks we have try all the combinations (lowercase and uppcass) of 
`"nan", "infinity", "-infinity", "inf", "-inf"` sofar.

```python
import itertools
items = ["nan", "infinity", "-infinity", "inf", "-inf"]
comb = []
for item in items:
   comb.extend(map(''.join, itertools.product(*zip(item.upper(), 
item.lower()

print("Set(%s)" % ", ".join(map(lambda c: '"%s"' % c, comb)))
```

This code is to generate the combinations. (I feel convenient for dealing 
with strings in Python). 


```scala
val s = Set("NAN", "NAn", ... "-inf")
s.foreach { w =>
  try {
w.toDouble // or w.toFloat
println(w)
  } catch {
case _ => // pass
  }
}
```

It looks we have supported the cases below so far:

```
NaN
-Infinity
Infinity
```

Let me update this.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
Yea, Let's focus on the topic. For the cases below:

```
{"a": NaN}
{"a": Infinity}
{"a": +Infinity}
{"a": -Infinity}
```

They are related with `allowNonNumericNumbers` and related tests are 
already being ignored. 

Okay. So the point is behaviour change, right? Let me give a shot to remove 
the behaviour changes here.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
BTW, if we want to support the JSON strings like `{"a": "-Infinity"}` as 
the FLOAT type, I think we also should support the float data in a string. 
Below is an example. 
```Scala
def floatRecords: Dataset[String] =
  spark.createDataset(spark.sparkContext.parallelize(
"""{"f": "18.00"}""" ::
  """{"f": "18.30"}""" ::
  """{"f": "20.00"}""" :: Nil))(Encoders.STRING)
val jsonDF = spark.read.schema("f float").json(floatRecords)
```

If we want to support parsing float data in a string, we should also 
support the other data types. Thus, this is another to-do issue, we should do 
an investigation. 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
Based on my previous work experience, I am very conservative to introduce 
any behavior change unless we are sure this is the right thing to do. I do not 
think this is a high priority PR. I can put it in my to-do list. When I am 
free, I can work on it. 

To prove the significance of this change, we need to check whether the 
other projects/products have the same/similar behavior? We do not want to 
introduce anything new or different. This is my concern. 

Below is the list we need to check. 
```
{"a": "+INF"}
{"a": "INF"}
{"a": "-INF"}
{"a": "NaN"}
{"a": "+NaN"}
{"a": "-NaN"}
{"a": "Infinity"}
{"a": "+Infinity"}
{"a": "-Infinity"}
```

Note, the above is different from the following JSON strings. 
```
{"a": NaN}
{"a": Infinity}
{"a": +Infinity}
{"a": -Infinity}
```

In my previous comment, I just want to share something for the people who 
want to be a committer in Spark. It is not related to this PR. 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
1. It is not good to hold off PRs. If a PR looks good and coherent, I think 
we could merge.

2. "How many JSON writers write a float "INF" as a string?", if it is your 
worry, I will take out the all newly added cases here. This is why I am 
thinking we should add this case via options.

3. My question was to ask taking over this. Please answer to this question.

4. Other information looks not related with the topic in this PR.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
Let me share my understanding. 

First, we do not have a deadline for any non-urgent fixes. This PR is an 
example. How many JSON writers write a float "INF" as a string? 

Being a committer needs to make a judgement to see how critical a PR is. My 
personal judgement is that we do not need to rush to merge it. I even want to 
wait for understanding how the other platforms handle **such a 
string-represented "INF" in a float-type column**. I believe we are not the 
first platform to face such an issue. That is why @cloud-fan and I asked the 
question above.

Second, we have to be careful to avoid introducing bugs when fixing the old 
issue. Spark is an infrastructure open-source project. We have to be very 
careful when doing the code reviews and code changes. If we accidentally 
introduced some supports, it is painful to remove the support and thus we have 
to keep it maybe forever. @viirya just found it very recently. Thus, please be 
careful when you do the code review and code changes. 

If the users really need such a fix, they also can fix it and make a build 
by themselves. I believe that is why people like open source projects. 

At the end, I want to share you a slides about bug costs. You might already 
saw similar figure before. 

https://cloud.githubusercontent.com/assets/11567269/26012021/00f34d82-3708-11e7-9271-1a97ecef0fff.png";>



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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
WDYT? I think it'd be faster to get this merged.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
Hey @gatorsmile, how about picking up the commits here and opening a PR?


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
We really need to be careful when making the code changes. If we support 
such a feature, we need to support all the data types. This is unexpected to 
users. 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
Yea, I am aware of it because we support special floating cases in string 
and I think we'd expect other doubles could be in string?


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
This PR also introduces the following behavior changes. 

```Scala
def floatRecords: Dataset[String] =
  spark.createDataset(spark.sparkContext.parallelize(
"""{"f": "18.00"}""" ::
  """{"f": "18.30"}""" ::
  """{"f": "20.00"}""" :: Nil))(Encoders.STRING)

val jsonDF = spark.read.schema("f float").json(floatRecords)
```

Before this PR, the output is like
```
++
|   f|
++
|null|
|null|
|null|
++
```
After this PR, the output is like
```
++
|   f|
++
|18.00|
|18.30|
|20.00|
++
```


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
`allowNonNumericNumbers` option is undocumented and incomplete for now - 
https://github.com/apache/spark/pull/9724#r44883828

> allowNonNumericNumbers is undocumented for now, since I can't figure out 
how it works.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
Before this PR, the option `allowNonNumericNumbers` affects the results of 
the following four cases:
```Json
{"a": NaN}
{"a": Infinity}
{"a": +Infinity}
{"a": -Infinity}
```

We should also enable this flag for the following cases too. 
```Json
{"a": "+INF"}
{"a": "INF"}
{"a": "-INF"}
{"a": "NaN"}
{"a": "+NaN"}
{"a": "-NaN"}
{"a": "Infinity"}
{"a": "+Infinity"}
{"a": "-Infinity"}
```

In addition, we almost introduced a very serious regression defect, because 
we do not have the test case to cover the following scenarios:

```Json
{"a": "4.0"}
```
Thus, we also should include the above test case. 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread AmplabJenkins
Github user AmplabJenkins commented on the issue:

https://github.com/apache/spark/pull/17956
  
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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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https://github.com/apache/spark/pull/17956
  
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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17956
  
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 * This patch passes all tests.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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https://github.com/apache/spark/pull/17956
  
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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
(Ah, it was about Jackson's `JsonParser.Feature.ALLOW_NON_NUMERIC_NUMBERS` 
... I see.)


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread viirya
Github user viirya commented on the issue:

https://github.com/apache/spark/pull/17956
  
> Do we need to follow allowNonNumericNumbers when parsing """{"a": 
"-Infinity"}"""? cc @cloud-fan @viirya

`allowNonNumericNumbers` supports it and Scala supports it too. It seems to 
me that we should follow them.



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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
I didn't understand what ^ means. Could you elaborate please? 
`allowNonNumericNumbers` option here for now is incomplete up to my knowledge.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
Do we need to follow `allowNonNumericNumbers` when parsing ` """{"a": 
"-Infinity"}"""`? cc @cloud-fan @viirya 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
uh... That is different... This is String. That is Float. nvm. They are 
different issues.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
Yes, thanks.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
If we do not upgrade `Jackson`, is that possible we can do it by checking 
the flag `allowNonNumericNumbers` before [doing the 
conversion](https://github.com/HyukjinKwon/spark/blob/fa63ff4e63bfcb3d780183528663223ab63891a3/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JacksonParser.scala#L129-L131)?


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
We should upgrade Jackson accordingly to support that option correctly. 
This looks reverted due to dependency problem - 
https://github.com/apache/spark/pull/9759#issuecomment-222759764. It sounds a 
bigger problem to me. (Also, strictly, it looks rather related with parsing 
itself). We already support the special floating cases and it might be fine 
just to improve this case.

I updated PR title and description already. I will fix JIRA as well (I was 
hesitated because that was not open by me).


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread gatorsmile
Github user gatorsmile commented on the issue:

https://github.com/apache/spark/pull/17956
  
Could we update the JIRA, PR title, and PR description? 

Also check the JSON flag `allowNonNumericNumbers` when doing the 
conversion? 


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17956
  
**[Test build #76858 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/76858/testReport)**
 for PR 17956 at commit 
[`fa63ff4`](https://github.com/apache/spark/commit/fa63ff4e63bfcb3d780183528663223ab63891a3).


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17956
  
**[Test build #76857 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/76857/testReport)**
 for PR 17956 at commit 
[`d581467`](https://github.com/apache/spark/commit/d5814678e488f6a28c33f5e8a31fde9d6d0b25a7).


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread HyukjinKwon
Github user HyukjinKwon commented on the issue:

https://github.com/apache/spark/pull/17956
  
@gatorsmail, I added some more cases I could identify based on 
http://docs.oracle.com/javase/7/docs/api/java/lang/Double.html#valueOf(java.lang.String)
 (this looks calling `java.lang.Double.parseDouble` which `toDouble` calls).

And also, for sure, I made this falls back to `toDouble` or `toFloat` and 
throw the same exceptions.


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[GitHub] spark issue #17956: [SPARK-18772][SQL] Avoid unnecessary conversion try and ...

2017-05-12 Thread SparkQA
Github user SparkQA commented on the issue:

https://github.com/apache/spark/pull/17956
  
**[Test build #76854 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/76854/testReport)**
 for PR 17956 at commit 
[`e858789`](https://github.com/apache/spark/commit/e85878917d6ff1fe107efc59bb1d403401a2441f).


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