[jira] [Created] (SPARK-30334) Add metadata around semi-structured columns to Spark

["Burak Yavuz (Jira)" <ji...@apache.org>]

Burak Yavuz created SPARK-30334:
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             Summary: Add metadata around semi-structured columns to Spark
                 Key: SPARK-30334
                 URL: https://issues.apache.org/jira/browse/SPARK-30334
             Project: Spark
          Issue Type: New Feature
          Components: SQL
    Affects Versions: 2.4.4
            Reporter: Burak Yavuz


Semi-structured data is used widely in the data industry for reporting events in a wide variety of formats. Click events in product analytics can be stored as json. Some application logs can be in the form of delimited key=value text. Some data may be in xml.

The goal of this project is to be able to signal Spark that such a column exists. This will then enable Spark to "auto-parse" these columns on the fly. The proposal is to store this information as part of the column metadata, in the fields:

 - format: The format of the semi-structured column, e.g. json, xml, avro

 - options: Options for parsing these columns

Then imagine having the following data:
{code:java}
+------------+-------+--------------------+
|     ts     | event |        raw         |
+------------+-------+--------------------+
| 2019-10-12 | click | {"field":"value"}  |
+------------+-------+--------------------+ {code}
SELECT raw.field FROM data

will return "value"

or the following data
{code:java}
+------------+-------+----------------------+
|     ts     | event |         raw          |
+------------+-------+----------------------+
| 2019-10-12 | click | field1=v1|field2=v2  |
+------------+-------+----------------------+ {code}
SELECT raw.field1 FROM data

will return v1.



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