RE: Flattening XML in a DataFrame

[srikanth.jella]

Hi Hyukjin,

I have created the below issue.
https://github.com/databricks/spark-xml/issues/155


Sent from Mail for Windows 10

From: Hyukjin Kwon

Re: Flattening XML in a DataFrame

[Hyukjin Kwon]

Sorry for late reply.

Currently, the library only supports to load XML documents just as they are.

Do you mind if I ask open an issue with some more explanations here,
https://github.com/databricks/spark-xml/issues?




2016-08-17 7:22 GMT+09:00 Sreekanth Jella <srikanth.je...@gmail.com>:

> Hi Experts,
>
>
>
> Please suggest. Thanks in advance.
>
>
>
> Thanks,
>
> Sreekanth
>
>
>
> *From:* Sreekanth Jella [mailto:srikanth.je...@gmail.com]
> *Sent:* Sunday, August 14, 2016 11:46 AM
> *To:* 'Hyukjin Kwon' <gurwls...@gmail.com>
> *Cc:* 'user @spark' <user@spark.apache.org>
> *Subject:* Re: Flattening XML in a DataFrame
>
>
>
> Hi Hyukjin Kwon,
>
> Thank you for reply.
>
> There are several types of XML documents with different schema which needs
> to be parsed and tag names do not know in hand. All we know is the XSD for
> the given XML.
>
> Is it possible to get the same results even when we do not know the xml
> tags like manager.id, manager.name or is it possible to read the tag
> names from XSD and use?
>
> Thanks,
> Sreekanth
>
>
>
> On Aug 12, 2016 9:58 PM, "Hyukjin Kwon" <gurwls...@gmail.com> wrote:
>
> Hi Sreekanth,
>
>
>
> Assuming you are using Spark 1.x,
>
>
>
> I believe this code below:
>
> sqlContext.read.format("com.databricks.spark.xml").option("rowTag", 
> "emp").load("/tmp/sample.xml")
>
>   .selectExpr("manager.id", "manager.name", 
> "explode(manager.subordinates.clerk) as clerk")
>
>   .selectExpr("id", "name", "clerk.cid", "clerk.cname")
>
>   .show()
>
> would print the results below as you want:
>
> +---++---+-+
>
> | id|name|cid|cname|
>
> +---++---+-+
>
> |  1| foo|  1|  foo|
>
> |  1| foo|  1|  foo|
>
> +---++---+-+
>
> ​
>
>
>
> I hope this is helpful.
>
>
>
> Thanks!
>
>
>
>
>
>
>
>
>
> 2016-08-13 9:33 GMT+09:00 Sreekanth Jella <srikanth.je...@gmail.com>:
>
> Hi Folks,
>
>
>
> I am trying flatten variety of XMLs using DataFrames. I’m using spark-xml
> package which is automatically inferring my schema and creating a
> DataFrame.
>
>
>
> I do not want to hard code any column names in DataFrame as I have lot of
> varieties of XML documents and each might be lot more depth of child nodes.
> I simply want to flatten any type of XML and then write output data to a
> hive table. Can you please give some expert advice for the same.
>
>
>
> Example XML and expected output is given below.
>
>
>
> Sample XML:
>
> 
>
> 
>
>
>
>1
>
>foo
>
> 
>
>   
>
> 1
>
> foo
>
>   
>
>   
>
> 1
>
> foo
>
>   
>
> 
>
>
>
> 
>
> 
>
>
>
> Expected output:
>
> id, name, clerk.cid, clerk.cname
>
> 1, foo, 2, cname2
>
> 1, foo, 3, cname3
>
>
>
> Thanks,
>
> Sreekanth Jella
>
>
>
>
>
>

RE: Flattening XML in a DataFrame

[Sreekanth Jella]

Hi Experts,

 

Please suggest. Thanks in advance.

 

Thanks,

Sreekanth

 

From: Sreekanth Jella [mailto:srikanth.je...@gmail.com] 
Sent: Sunday, August 14, 2016 11:46 AM
To: 'Hyukjin Kwon' <gurwls...@gmail.com>
Cc: 'user @spark' <user@spark.apache.org>
Subject: Re: Flattening XML in a DataFrame

 

Hi Hyukjin Kwon,

Thank you for reply.

There are several types of XML documents with different schema which needs to 
be parsed and tag names do not know in hand. All we know is the XSD for the 
given XML. 

Is it possible to get the same results even when we do not know the xml tags 
like manager.id, manager.name or is it possible to read the tag names from XSD 
and use?

Thanks, 
Sreekanth

 

On Aug 12, 2016 9:58 PM, "Hyukjin Kwon" <gurwls...@gmail.com 
<mailto:gurwls...@gmail.com> > wrote:

Hi Sreekanth,

 

Assuming you are using Spark 1.x,

 

I believe this code below:

sqlContext.read.format("com.databricks.spark.xml").option("rowTag", 
"emp").load("/tmp/sample.xml")
  .selectExpr("manager.id <http://manager.id> ", "manager.name 
<http://manager.name> ", "explode(manager.subordinates.clerk) as clerk")
  .selectExpr("id", "name", "clerk.cid", "clerk.cname")
  .show()

would print the results below as you want:

+---++---+-+
| id|name|cid|cname|
+---++---+-+
|  1| foo|  1|  foo|
|  1| foo|  1|  foo|
+---++---+-+

​

 

I hope this is helpful.

 

Thanks!

 

 

 

 

2016-08-13 9:33 GMT+09:00 Sreekanth Jella <srikanth.je...@gmail.com 
<mailto:srikanth.je...@gmail.com> >:

Hi Folks,

 

I am trying flatten variety of XMLs using DataFrames. I’m using spark-xml 
package which is automatically inferring my schema and creating a DataFrame. 

 

I do not want to hard code any column names in DataFrame as I have lot of 
varieties of XML documents and each might be lot more depth of child nodes. I 
simply want to flatten any type of XML and then write output data to a hive 
table. Can you please give some expert advice for the same.

 

Example XML and expected output is given below.

 

Sample XML:





   

   1

   foo



  

1

foo

  

  

1

foo

  



   





 

Expected output:

id, name, clerk.cid, clerk.cname

1, foo, 2, cname2

1, foo, 3, cname3

 

Thanks,

Sreekanth Jella

 

 

Re: Flattening XML in a DataFrame

[Sreekanth Jella]

Hi Hyukjin Kwon,

Thank you for reply.

There are several types of XML documents with different schema which needs to 
be parsed and tag names do not know in hand. All we know is the XSD for the 
given XML. 

Is it possible to get the same results even when we do not know the xml tags 
like manager.id, manager.name or is it possible to read the tag names from XSD 
and use?

Thanks, 
Sreekanth

 

On Aug 12, 2016 9:58 PM, "Hyukjin Kwon"  > wrote:

Hi Sreekanth,

 

Assuming you are using Spark 1.x,

 

I believe this code below:

sqlContext.read.format("com.databricks.spark.xml").option("rowTag", 
"emp").load("/tmp/sample.xml")
  .selectExpr("manager.id  ", "manager.name 
 ", "explode(manager.subordinates.clerk) as clerk")
  .selectExpr("id", "name", "clerk.cid", "clerk.cname")
  .show()

would print the results below as you want:

+---++---+-+
| id|name|cid|cname|
+---++---+-+
|  1| foo|  1|  foo|
|  1| foo|  1|  foo|
+---++---+-+

​

 

I hope this is helpful.

 

Thanks!

 

 

 

 

2016-08-13 9:33 GMT+09:00 Sreekanth Jella  >:

Hi Folks,

 

I am trying flatten variety of XMLs using DataFrames. I’m using spark-xml 
package which is automatically inferring my schema and creating a DataFrame. 

 

I do not want to hard code any column names in DataFrame as I have lot of 
varieties of XML documents and each might be lot more depth of child nodes. I 
simply want to flatten any type of XML and then write output data to a hive 
table. Can you please give some expert advice for the same.

 

Example XML and expected output is given below.

 

Sample XML:





   

   1

   foo



  

1

foo

  

  

1

foo

  



   





 

Expected output:

id, name, clerk.cid, clerk.cname

1, foo, 2, cname2

1, foo, 3, cname3

 

Thanks,

Sreekanth Jella

 

 

Re: Flattening XML in a DataFrame

[Hyukjin Kwon]

Hi Sreekanth,

Assuming you are using Spark 1.x,

I believe this code below:

sqlContext.read.format("com.databricks.spark.xml").option("rowTag",
"emp").load("/tmp/sample.xml")
  .selectExpr("manager.id", "manager.name",
"explode(manager.subordinates.clerk) as clerk")
  .selectExpr("id", "name", "clerk.cid", "clerk.cname")
  .show()

would print the results below as you want:

+---++---+-+
| id|name|cid|cname|
+---++---+-+
|  1| foo|  1|  foo|
|  1| foo|  1|  foo|
+---++---+-+

​

I hope this is helpful.

Thanks!




2016-08-13 9:33 GMT+09:00 Sreekanth Jella :

> Hi Folks,
>
>
>
> I am trying flatten variety of XMLs using DataFrames. I’m using spark-xml
> package which is automatically inferring my schema and creating a
> DataFrame.
>
>
>
> I do not want to hard code any column names in DataFrame as I have lot of
> varieties of XML documents and each might be lot more depth of child nodes.
> I simply want to flatten any type of XML and then write output data to a
> hive table. Can you please give some expert advice for the same.
>
>
>
> Example XML and expected output is given below.
>
>
>
> Sample XML:
>
> 
>
> 
>
>
>
>1
>
>foo
>
> 
>
>   
>
> 1
>
> foo
>
>   
>
>   
>
> 1
>
> foo
>
>   
>
> 
>
>
>
> 
>
> 
>
>
>
> Expected output:
>
> id, name, clerk.cid, clerk.cname
>
> 1, foo, 2, cname2
>
> 1, foo, 3, cname3
>
>
>
> Thanks,
>
> Sreekanth Jella
>
>
>

Flattening XML in a DataFrame

[Sreekanth Jella]

Hi Folks,

 

I am trying flatten variety of XMLs using DataFrames. I'm using spark-xml
package which is automatically inferring my schema and creating a DataFrame.


 

I do not want to hard code any column names in DataFrame as I have lot of
varieties of XML documents and each might be lot more depth of child nodes.
I simply want to flatten any type of XML and then write output data to a
hive table. Can you please give some expert advice for the same.

 

Example XML and expected output is given below.

 

Sample XML:





   

   1

   foo



  

1

foo

  

  

1

foo

  



   





 

Expected output:

id, name, clerk.cid, clerk.cname

1, foo, 2, cname2

1, foo, 3, cname3

 

Thanks,

Sreekanth Jella