[
https://issues.apache.org/jira/browse/SPARK-21651?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
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
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
