[jira] [Commented] (SPARK-15804) Manually added metadata not saving with parquet

2016-07-08 Thread Wenchen Fan (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-15804?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15367974#comment-15367974
 ] 

Wenchen Fan commented on SPARK-15804:
-

this will be fixed by https://github.com/apache/spark/pull/14106

> Manually added metadata not saving with parquet
> ---
>
> Key: SPARK-15804
> URL: https://issues.apache.org/jira/browse/SPARK-15804
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.0
>Reporter: Charlie Evans
>Assignee: kevin yu
>
> Adding metadata with col().as(_, metadata) then saving the resultant 
> dataframe does not save the metadata. No error is thrown. Only see the schema 
> contains the metadata before saving and does not contain the metadata after 
> saving and loading the dataframe. Was working fine with 1.6.1.
> {code}
> case class TestRow(a: String, b: Int)
> val rows = TestRow("a", 0) :: TestRow("b", 1) :: TestRow("c", 2) :: Nil
> val df = spark.createDataFrame(rows)
> import org.apache.spark.sql.types.MetadataBuilder
> val md = new MetadataBuilder().putString("key", "value").build()
> val dfWithMeta = df.select(col("a"), col("b").as("b", md))
> println(dfWithMeta.schema.json)
> dfWithMeta.write.parquet("dfWithMeta")
> val dfWithMeta2 = spark.read.parquet("dfWithMeta")
> println(dfWithMeta2.schema.json)
> {code}



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[jira] [Commented] (SPARK-15804) Manually added metadata not saving with parquet

2016-06-08 Thread Apache Spark (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-15804?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15320182#comment-15320182
 ] 

Apache Spark commented on SPARK-15804:
--

User 'kevinyu98' has created a pull request for this issue:
https://github.com/apache/spark/pull/13555

> Manually added metadata not saving with parquet
> ---
>
> Key: SPARK-15804
> URL: https://issues.apache.org/jira/browse/SPARK-15804
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.0
>Reporter: Charlie Evans
>
> Adding metadata with col().as(_, metadata) then saving the resultant 
> dataframe does not save the metadata. No error is thrown. Only see the schema 
> contains the metadata before saving and does not contain the metadata after 
> saving and loading the dataframe. Was working fine with 1.6.1.
> {code}
> case class TestRow(a: String, b: Int)
> val rows = TestRow("a", 0) :: TestRow("b", 1) :: TestRow("c", 2) :: Nil
> val df = spark.createDataFrame(rows)
> import org.apache.spark.sql.types.MetadataBuilder
> val md = new MetadataBuilder().putString("key", "value").build()
> val dfWithMeta = df.select(col("a"), col("b").as("b", md))
> println(dfWithMeta.schema.json)
> dfWithMeta.write.parquet("dfWithMeta")
> val dfWithMeta2 = spark.read.parquet("dfWithMeta")
> println(dfWithMeta2.schema.json)
> {code}



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[jira] [Commented] (SPARK-15804) Manually added metadata not saving with parquet

2016-06-08 Thread kevin yu (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-15804?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15320180#comment-15320180
 ] 

kevin yu commented on SPARK-15804:
--

https://github.com/apache/spark/pull/13555

> Manually added metadata not saving with parquet
> ---
>
> Key: SPARK-15804
> URL: https://issues.apache.org/jira/browse/SPARK-15804
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.0
>Reporter: Charlie Evans
>
> Adding metadata with col().as(_, metadata) then saving the resultant 
> dataframe does not save the metadata. No error is thrown. Only see the schema 
> contains the metadata before saving and does not contain the metadata after 
> saving and loading the dataframe. Was working fine with 1.6.1.
> {code}
> case class TestRow(a: String, b: Int)
> val rows = TestRow("a", 0) :: TestRow("b", 1) :: TestRow("c", 2) :: Nil
> val df = spark.createDataFrame(rows)
> import org.apache.spark.sql.types.MetadataBuilder
> val md = new MetadataBuilder().putString("key", "value").build()
> val dfWithMeta = df.select(col("a"), col("b").as("b", md))
> println(dfWithMeta.schema.json)
> dfWithMeta.write.parquet("dfWithMeta")
> val dfWithMeta2 = spark.read.parquet("dfWithMeta")
> println(dfWithMeta2.schema.json)
> {code}



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[jira] [Commented] (SPARK-15804) Manually added metadata not saving with parquet

2016-06-07 Thread kevin yu (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-15804?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15319706#comment-15319706
 ] 

kevin yu commented on SPARK-15804:
--

I will submit a PR soon. Thanks.

> Manually added metadata not saving with parquet
> ---
>
> Key: SPARK-15804
> URL: https://issues.apache.org/jira/browse/SPARK-15804
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.0
>Reporter: Charlie Evans
>
> Adding metadata with col().as(_, metadata) then saving the resultant 
> dataframe does not save the metadata. No error is thrown. Only see the schema 
> contains the metadata before saving and does not contain the metadata after 
> saving and loading the dataframe. Was working fine with 1.6.1.
> {code}
> case class TestRow(a: String, b: Int)
> val rows = TestRow("a", 0) :: TestRow("b", 1) :: TestRow("c", 2) :: Nil
> val df = spark.createDataFrame(rows)
> import org.apache.spark.sql.types.MetadataBuilder
> val md = new MetadataBuilder().putString("key", "value").build()
> val dfWithMeta = df.select(col("a"), col("b").as("b", md))
> println(dfWithMeta.schema.json)
> dfWithMeta.write.parquet("dfWithMeta")
> val dfWithMeta2 = spark.read.parquet("dfWithMeta")
> println(dfWithMeta2.schema.json)
> {code}



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[jira] [Commented] (SPARK-15804) Manually added metadata not saving with parquet

2016-06-07 Thread Takeshi Yamamuro (JIRA)

[ 
https://issues.apache.org/jira/browse/SPARK-15804?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15318897#comment-15318897
 ] 

Takeshi Yamamuro commented on SPARK-15804:
--

`MetadataBuilder` is one of developer apis, so is this functionality useful for 
developers?
Any useful scenario to use this?
Anyway, this is related to not only `parquet but also other formats such as 
orc, csv, json...

> Manually added metadata not saving with parquet
> ---
>
> Key: SPARK-15804
> URL: https://issues.apache.org/jira/browse/SPARK-15804
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.0
>Reporter: Charlie Evans
>
> Adding metadata with col().as(_, metadata) then saving the resultant 
> dataframe does not save the metadata. No error is thrown. Only see the schema 
> contains the metadata before saving and does not contain the metadata after 
> saving and loading the dataframe.
> {code}
> case class TestRow(a: String, b: Int)
> val rows = TestRow("a", 0) :: TestRow("b", 1) :: TestRow("c", 2) :: Nil
> val df = spark.createDataFrame(rows)
> import org.apache.spark.sql.types.MetadataBuilder
> val md = new MetadataBuilder().putString("key", "value").build()
> val dfWithMeta = df.select(col("a"), col("b").as("b", md))
> println(dfWithMeta.schema.json)
> dfWithMeta.write.parquet("dfWithMeta")
> val dfWithMeta2 = spark.read.parquet("dfWithMeta")
> println(dfWithMeta2.schema.json)
> {code}



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