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| author | Andrew Or <andrew@databricks.com> | 2016-05-19 23:43:01 -0700 |
|---|---|---|
| committer | Andrew Or <andrew@databricks.com> | 2016-05-19 23:43:01 -0700 |
| commit | 257375019266ab9e3c320e33026318cc31f58ada (patch) | |
| tree | ce885e91c56fd8d6133ee9a3c512d80cd826c6c2 /python/pyspark/shell.py | |
| parent | 39fd469078271aa12f3163606000e06e382d35dc (diff) | |
| download | spark-257375019266ab9e3c320e33026318cc31f58ada.tar.gz spark-257375019266ab9e3c320e33026318cc31f58ada.tar.bz2 spark-257375019266ab9e3c320e33026318cc31f58ada.zip | |
[SPARK-15421][SQL] Validate DDL property values
## What changes were proposed in this pull request?
When we parse DDLs involving table or database properties, we need to validate the values.
E.g. if we alter a database's property without providing a value:
```
ALTER DATABASE my_db SET DBPROPERTIES('some_key')
```
Then we'll ignore it with Hive, but override the property with the in-memory catalog. Inconsistencies like these arise because we don't validate the property values.
In such cases, we should throw exceptions instead.
## How was this patch tested?
`DDLCommandSuite`
Author: Andrew Or <andrew@databricks.com>
Closes #13205 from andrewor14/ddl-prop-values.
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