[SPARK-22442][SQL][BRANCH-2.2] ScalaReflection should produce correct field names for special characters #19734
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cc @cloud-fan The backport of SPARK-22442 to branch 2.2. |
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Test build #83763 has finished for PR 19734 at commit
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ok thanks, I'm above to tag 2.2.1. technically this isn't a regression but I could wait for a few hours (need to wait for jenkins build from the branch) if we could merge this ASAP |
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merged to 2.2 |
asfgit
pushed a commit
that referenced
this pull request
Nov 13, 2017
… field names for special characters
## What changes were proposed in this pull request?
For a class with field name of special characters, e.g.:
```scala
case class MyType(`field.1`: String, `field 2`: String)
```
Although we can manipulate DataFrame/Dataset, the field names are encoded:
```scala
scala> val df = Seq(MyType("a", "b"), MyType("c", "d")).toDF
df: org.apache.spark.sql.DataFrame = [field$u002E1: string, field$u00202: string]
scala> df.as[MyType].collect
res7: Array[MyType] = Array(MyType(a,b), MyType(c,d))
```
It causes resolving problem when we try to convert the data with non-encoded field names:
```scala
spark.read.json(path).as[MyType]
...
[info] org.apache.spark.sql.AnalysisException: cannot resolve '`field$u002E1`' given input columns: [field 2, fie
ld.1];
[info] at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
...
```
We should use decoded field name in Dataset schema.
## How was this patch tested?
Added tests.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes #19734 from viirya/SPARK-22442-2.2.
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Thanks @felixcheung |
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@felixcheung Yes. Looking into it. |
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MatthewRBruce
pushed a commit
to Shopify/spark
that referenced
this pull request
Jul 31, 2018
… field names for special characters
## What changes were proposed in this pull request?
For a class with field name of special characters, e.g.:
```scala
case class MyType(`field.1`: String, `field 2`: String)
```
Although we can manipulate DataFrame/Dataset, the field names are encoded:
```scala
scala> val df = Seq(MyType("a", "b"), MyType("c", "d")).toDF
df: org.apache.spark.sql.DataFrame = [field$u002E1: string, field$u00202: string]
scala> df.as[MyType].collect
res7: Array[MyType] = Array(MyType(a,b), MyType(c,d))
```
It causes resolving problem when we try to convert the data with non-encoded field names:
```scala
spark.read.json(path).as[MyType]
...
[info] org.apache.spark.sql.AnalysisException: cannot resolve '`field$u002E1`' given input columns: [field 2, fie
ld.1];
[info] at org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
...
```
We should use decoded field name in Dataset schema.
## How was this patch tested?
Added tests.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes apache#19734 from viirya/SPARK-22442-2.2.
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What changes were proposed in this pull request?
For a class with field name of special characters, e.g.:
Although we can manipulate DataFrame/Dataset, the field names are encoded:
It causes resolving problem when we try to convert the data with non-encoded field names:
We should use decoded field name in Dataset schema.
How was this patch tested?
Added tests.