Json dataframe to CSV dataframe
Why do we need schema for a dataframe before converting json dataframe to CSV dataframe? In pyspark dataframe
As CSV format is flat and doesn’t support nested types hence you will need to flatten your DataFrame before writing it as CSV format.
person RAVULA access_time 11 months ago
Re: Json dataframe to CSV dataframe
For CSV :-
We can easily the data goes under easily ETL jobs.
But for json frames not
For json having complex levels like
Example : struct {
Array 1:[
Info_:{
Some values
},
Arry_inside:[
Some values
]
]
}
so we don't have choice to do like CSV so then we need to extract values the. We need to produce the output file as CSV from json.
For CSV :-
We can easily the data goes under easily ETL jobs.
But for json frames not
For json having complex levels like
Example : struct {
Array 1:[
Info_:{
Some values
},
Arry_inside:[
Some values
]
]
}
so we don't have choice to do like CSV so then we need to extract values the. We need to produce the output file as CSV from json.
person Raymond access_time 11 months ago
Re: Json dataframe to CSV dataframe
Can you please define what is a JSON or CSV DataFrame?
If a JSON document is loaded into memory as a DataFrame, it can then be saved as other format like CSV.
Before you load JSON document, you usually can define a schema or Spark can also infer schema.
For CSV :-
We can easily the data goes under easily ETL jobs.
But for json frames not
For json having complex levels like
Example : struct {
Array 1:[
Info_:{
Some values
},
Arry_inside:[
Some values
]
]
}
so we don't have choice to do like CSV so then we need to extract values the. We need to produce the output file as CSV from json.
person Raymond access_time 11 months ago
Re: Json dataframe to CSV dataframe
Can you please define what is a JSON or CSV DataFrame?
If a JSON document is loaded into memory as a DataFrame, it can then be saved as other format like CSV.
Before you load JSON document, you usually can define a schema or Spark can also infer schema.
For CSV :-
We can easily the data goes under easily ETL jobs.
But for json frames not
For json having complex levels like
Example : struct {
Array 1:[
Info_:{
Some values
},
Arry_inside:[
Some values
]
]
}
so we don't have choice to do like CSV so then we need to extract values the. We need to produce the output file as CSV from json.
person Raymond access_time 11 months ago
Re: Json dataframe to CSV dataframe
Can you please define what is a JSON or CSV DataFrame?
If a JSON document is loaded into memory as a DataFrame, it can then be saved as other format like CSV.
Before you load JSON document, you usually can define a schema or Spark can also infer schema.
Can you please define what is a JSON or CSV DataFrame?
If a JSON document is loaded into memory as a DataFrame, it can then be saved as other format like CSV.
Before you load JSON document, you usually can define a schema or Spark can also infer schema.
Consider this array:
{
Array 1:[
{
Info_:{
"a":1,
"b":4
},
Arry_inside:[
Item1,
Item2
]
},
{
Info_:{
"a":5,
"b":9
},
Arry_inside:[
Item1,
Item2,
Item3,
Item4
]},
]
}
Above json contains inside array is a growing array so how can we flat....i don't think that will work....can you please see these kind of json files
Some we can do it may be.....
I don't know that......
So basically the JSON in my case it is getting from RESTAPI response for a POST request to a server..
The response is a JSON...
Which look like above mentioned looks very simple now but it's not 😂,, but i can't share that one ..
In response Json file contains
Mainly one Array 1 inside that we are getting like 10k - 30k objects of struct type
Inside each object:
There 10 keys are struct type and 10 values arry type ...
All values are null is allowed
So here is the deal the one Array kind of key that is the Messege kind of stuff is there inside the complex types similar to the json i mentioned inside array if go inside items one key value pair message is there
We need to extract that each mesage in each row...