findepi commented on a change in pull request #1611:
URL: https://github.com/apache/iceberg/pull/1611#discussion_r678201399
##########
File path: site/docs/spark.md
##########
@@ -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 | |
+| decimal | decimal | |
+| struct | struct | |
+| array | list | |
+| map | map | |
+
+The type conversion is asymmetric: this table doesn't represent the types of
Iceberg Spark can "read" from, or "write" to.
+The following sections describe the feasibility on read/write for Iceberg type
from Spark.
+
+### Iceberg to Spark on reading from Iceberg table
+
+| Iceberg | Spark | Note |
+|----------------------------|-------------------------|-------|
+| boolean | boolean | |
+| integer | integer | |
+| long | long | |
+| float | float | |
+| double | double | |
+| date | date | |
+| time | <N/A> | |
+| timestamp with timezone | timestamp | |
+| timestamp without timezone | <N/A> | |
+| string | string | |
+| uuid | string | |
Review comment:
Followed up at https://github.com/trinodb/trino/issues/6663 and on the
mailing list.
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