Hi Mathieu,
metadata is very usefull if you need to save some data about a column
(e.g. count of null values, cardinality, domain, min/max/std, etc.).
It's currently used in ml package in attributes:
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/attribute/attributes.scala
Take a look how i'm using metadata to get summary statistics from h2o:
https://github.com/h2oai/sparkling-water/pull/17/files
Let me know if you'll have questions.
Thanks,
Peter Rudenko
On 2015-07-15 12:48, matd wrote:
I see in StructField that we can provide metadata.
What is it meant for ? How is it used by Spark later on ?
Are there any rules on what we can/cannot do with it ?
I'm building some DataFrame processing, and I need to maintain a set of
(meta)data along with the DF. I was wondering if I can use
StructField.metadata for this use, or if I should build my own structure.
Mathieu
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