Re: spark partitionBy with partitioned column in json output
Had the same issue my self. I was surprised at first as well, but I found
it useful - the amount of data saved for each partition has decreased.
When I load the data from each partition, I add the partitioned columns
with lit function before I merge the frames from the
different partitions.
On Tue, Jun 5, 2018 at 5:44 AM, Jay wrote:
> The partitionBy clause is used to create hive folders so that you can
> point a hive partitioned table on the data .
>
> What are you using the partitionBy for ? What is the use case ?
>
>
> On Mon 4 Jun, 2018, 4:59 PM purna pradeep,
> wrote:
>
>> im reading below json in spark
>>
>> {"bucket": "B01", "actionType": "A1", "preaction": "NULL",
>> "postaction": "NULL"}
>> {"bucket": "B02", "actionType": "A2", "preaction": "NULL",
>> "postaction": "NULL"}
>> {"bucket": "B03", "actionType": "A3", "preaction": "NULL",
>> "postaction": "NULL"}
>>
>> val df=spark.read.json("actions.json").toDF()
>>
>> Now im writing the same to a json output as below
>>
>> df.write. format("json"). mode("append").
>> partitionBy("bucket","actionType").
>> save("output.json")
>>
>>
>> and the output.json is as below
>>
>> {"preaction":"NULL","postaction":"NULL"}
>>
>> bucket,actionType columns are missing in the json output, i need
>> partitionby columns as well in the output
>>
>>
Re: spark partitionBy with partitioned column in json output
The partitionBy clause is used to create hive folders so that you can point
a hive partitioned table on the data .
What are you using the partitionBy for ? What is the use case ?
On Mon 4 Jun, 2018, 4:59 PM purna pradeep, wrote:
> im reading below json in spark
>
> {"bucket": "B01", "actionType": "A1", "preaction": "NULL",
> "postaction": "NULL"}
> {"bucket": "B02", "actionType": "A2", "preaction": "NULL",
> "postaction": "NULL"}
> {"bucket": "B03", "actionType": "A3", "preaction": "NULL",
> "postaction": "NULL"}
>
> val df=spark.read.json("actions.json").toDF()
>
> Now im writing the same to a json output as below
>
> df.write. format("json"). mode("append").
> partitionBy("bucket","actionType"). save("output.json")
>
>
> and the output.json is as below
>
> {"preaction":"NULL","postaction":"NULL"}
>
> bucket,actionType columns are missing in the json output, i need
> partitionby columns as well in the output
>
>
Re: spark partitionBy with partitioned column in json output
Purna,
This behavior is by design. If you provide partitionBy, Spark removes the
columns from the data
From: purna pradeep
Date: Monday, June 4, 2018 at 8:00 PM
To: "user@spark.apache.org"
Subject: spark partitionBy with partitioned column in json output
im reading below json in spark
{"bucket": "B01", "actionType": "A1", "preaction": "NULL", "postaction":
"NULL"}
{"bucket": "B02", "actionType": "A2", "preaction": "NULL", "postaction":
"NULL"}
{"bucket": "B03", "actionType": "A3", "preaction": "NULL", "postaction":
"NULL"}
val df=spark.read.json("actions.json").toDF()
Now im writing the same to a json output as below
df.write. format("json"). mode("append").
partitionBy("bucket","actionType"). save("output.json")
and the output.json is as below
{"preaction":"NULL","postaction":"NULL"}
bucket,actionType columns are missing in the json output, i need partitionby
columns as well in the output
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spark partitionBy with partitioned column in json output
im reading below json in spark
{"bucket": "B01", "actionType": "A1", "preaction": "NULL",
"postaction": "NULL"}
{"bucket": "B02", "actionType": "A2", "preaction": "NULL",
"postaction": "NULL"}
{"bucket": "B03", "actionType": "A3", "preaction": "NULL",
"postaction": "NULL"}
val df=spark.read.json("actions.json").toDF()
Now im writing the same to a json output as below
df.write. format("json"). mode("append").
partitionBy("bucket","actionType"). save("output.json")
and the output.json is as below
{"preaction":"NULL","postaction":"NULL"}
bucket,actionType columns are missing in the json output, i need
partitionby columns as well in the output
