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https://issues.apache.org/jira/browse/SPARK-21651?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jochen Niebuhr updated SPARK-21651:
-----------------------------------
    Description: 
When loading Json Files which include a map with very variable keys, the 
current schema infer logic might create a very large schema. This will lead to 
long load times and possibly out of memory errors. 
I've already submitted a pull request to the mongo spark driver which had the 
same problem. Should I port this logic over to the json schema infer class?

The MongoDB Spark pull request mentioned is: 
https://github.com/mongodb/mongo-spark/pull/24

  was:
When loading Json Files which include a map with very variable keys, the 
current schema infer logic might create a very large schema. This will lead to 
long load times and possibly out of memory errors. 
I've already submitted a pull request to the mongo spark driver which had a 
similar problem. Should I port this logic over to the json schema infer class?

The MongoDB Spark pull request mentioned is: 
https://github.com/mongodb/mongo-spark/pull/24


> Detect MapType in Json InferSchema
> ----------------------------------
>
>                 Key: SPARK-21651
>                 URL: https://issues.apache.org/jira/browse/SPARK-21651
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.1.0, 2.1.1, 2.2.0
>            Reporter: Jochen Niebuhr
>            Priority: Minor
>
> When loading Json Files which include a map with very variable keys, the 
> current schema infer logic might create a very large schema. This will lead 
> to long load times and possibly out of memory errors. 
> I've already submitted a pull request to the mongo spark driver which had the 
> same problem. Should I port this logic over to the json schema infer class?
> The MongoDB Spark pull request mentioned is: 
> https://github.com/mongodb/mongo-spark/pull/24



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