[GitHub] [iceberg] rdblue commented on a change in pull request #1611: DOCS: describe type compatibility between Spark and Iceberg

[GitBox <gi...@apache.org>]

rdblue commented on a change in pull request #1611:
URL: https://github.com/apache/iceberg/pull/1611#discussion_r504793706



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File path: site/docs/spark.md
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@@ -728,3 +730,82 @@ spark.read.format("iceberg").load("db.table.files").show(truncate = false)
 // Hadoop path table
 spark.read.format("iceberg").load("hdfs://nn:8020/path/to/table#files").show(truncate = false)
 ```
+
+## Type compatibility
+
+Spark and Iceberg support different set of types. Iceberg does the type conversion automatically, but not for all combinations,
+so you may want to understand the type conversion in Iceberg in prior to design the types of columns in your tables.
+
+### Spark type to Iceberg type on creating table
+
+This type conversion table describes how Spark types are converted to the Iceberg types. The conversion applies on creating Iceberg table via Spark without using Iceberg core API.
+
+| Spark           | Iceberg                 | Notes |
+|-----------------|-------------------------|-------|
+| boolean         | boolean                 |       |
+| integer         | integer                 |       |
+| short           | integer                 |       |
+| byte            | integer                 |       |
+| long            | long                    |       |
+| float           | float                   |       |
+| double          | double                  |       |
+| date            | date                    |       |
+| timestamp       | timestamp with timezone |       |
+| string          | string                  |       |
+| char            | string                  |       |
+| varchar         | string                  |       |
+| binary          | binary                  |       |

Review comment:
       Binary can be written to a fixed column. It will be validated at write time.




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