Re: How to maintain order of key-value in DataFrame same as JSON?

[Afshin, Bardia]

Is there a API available to do this via SparkSession?

Sent from my iPhone

On Apr 24, 2017, at 6:20 AM, Devender Yadav 
> wrote:


Thanks Hemanth for a quick reply.


From: Hemanth Gudela 
>
Sent: Monday, April 24, 2017 6:37:48 PM
To: Devender Yadav; user@spark.apache.org
Subject: Re: How to maintain order of key-value in DataFrame same as JSON?

Hi,

One option to use if you can is to force df to use the schema order you prefer 
like this.

DataFrame df = 
sqlContext.read().json(jsonPath).select("name","salary","occupation","address")

-Hemanth

From: Devender Yadav 
>
Date: Monday, 24 April 2017 at 15.45
To: "user@spark.apache.org" 
>
Subject: How to maintain order of key-value in DataFrame same as JSON?


{"name": "dev","salary": 100,"occupation": "engg","address": "noida"}

{"name": "karthik","salary": 200,"occupation": "engg","address": "blore"}








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Re: How to maintain order of key-value in DataFrame same as JSON?

[Devender Yadav]

Thanks Hemanth for a quick reply.


From: Hemanth Gudela 
Sent: Monday, April 24, 2017 6:37:48 PM
To: Devender Yadav; user@spark.apache.org
Subject: Re: How to maintain order of key-value in DataFrame same as JSON?

Hi,

One option to use if you can is to force df to use the schema order you prefer 
like this.

DataFrame df = 
sqlContext.read().json(jsonPath).select("name","salary","occupation","address")

-Hemanth

From: Devender Yadav 
Date: Monday, 24 April 2017 at 15.45
To: "user@spark.apache.org" 
Subject: How to maintain order of key-value in DataFrame same as JSON?


{"name": "dev","salary": 100,"occupation": "engg","address": "noida"}

{"name": "karthik","salary": 200,"occupation": "engg","address": "blore"}








NOTE: This message may contain information that is confidential, proprietary, 
privileged or otherwise protected by law. The message is intended solely for 
the named addressee. If received in error, please destroy and notify the 
sender. Any use of this email is prohibited when received in error. Impetus 
does not represent, warrant and/or guarantee, that the integrity of this 
communication has been maintained nor that the communication is free of errors, 
virus, interception or interference.

Re: How to maintain order of key-value in DataFrame same as JSON?

[Hemanth Gudela]

Hi,

One option to use if you can is to force df to use the schema order you prefer 
like this.

DataFrame df = 
sqlContext.read().json(jsonPath).select("name","salary","occupation","address")

-Hemanth

From: Devender Yadav 
Date: Monday, 24 April 2017 at 15.45
To: "user@spark.apache.org" 
Subject: How to maintain order of key-value in DataFrame same as JSON?


{"name": "dev","salary": 100,"occupation": "engg","address": "noida"}

{"name": "karthik","salary": 200,"occupation": "engg","address": "blore"}

How to maintain order of key-value in DataFrame same as JSON?

[Devender Yadav]

Hi All,


Sample JSON data:

{"name": "dev","salary": 100,"occupation": "engg","address": "noida"}

{"name": "karthik","salary": 200,"occupation": "engg","address": "blore"}

Spark Java code:

DataFrame df = sqlContext.read().json(jsonPath);
df.printSchema();
df.show(false);


Output:

root
 |-- address: string (nullable = true)
 |-- name: string (nullable = true)
 |-- occupation: string (nullable = true)
 |-- salary: long (nullable = true)


+---+---+--+--+
|address|name   |occupation|salary|
+---+---+--+--+
|noida  |dev|engg  |1 |
|blore  |karthik|engg  |2 |
+---+---+--+--+


Columns are arranged in the alphabetical order.


Is there any way to maintain natural order?



Regards,
Devender








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