guykhazma commented on code in PR #12931:
URL: https://github.com/apache/iceberg/pull/12931#discussion_r2067399268
##########
docs/docs/spark-configuration.md:
##########
@@ -145,6 +145,59 @@ Using those SQL commands requires adding Iceberg
extensions to your Spark enviro
## Runtime configuration
+### Precedence of Configuration Settings
+Iceberg allows configurations to be specified at different levels. The
effective configuration for a read or write operation is determined based on
the following order of precedence:
+
+1. Read/Write Options – Explicitly passed to `.option(...)` in a read/write
operation.
+
+2. Table Properties – Defined on the Iceberg table via `ALTER TABLE SET
TBLPROPERTIES`.
+
+3. Spark SQL Configurations – Set globally in Spark via `spark.conf.set(...)`,
`spark-defaults.conf`, or `--conf` in spark-submit.
+
+If a setting is not defined at a higher level, the next level is used as
fallback. This allows flexibility while enabling global defaults when needed.
+
+### Spark SQL Options
+
+Iceberg supports setting various global behaviors using Spark SQL
configuration options. These can be set via `spark.conf`, `SparkSession
settings`, or Spark submit arguments.
+For example:
+
+```scala
+// disabling vectorization
+val spark = SparkSession.builder()
+ .appName("IcebergExample")
+ .master("local[*]")
+ .config("spark.sql.catalog.my_catalog",
"org.apache.iceberg.spark.SparkCatalog")
+ .config("spark.sql.extensions",
"org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions")
+ .config("spark.sql.iceberg.vectorization.enabled", "false")
+ .getOrCreate()
+```
+
+| Spark option | Default
| Description |
Review Comment:
Some of the properties have different naming. For example, the vectorization
is set using `vectorization-enabled` when using an option or the session conf.
While using it as a table property requires to specify the format:
`read.parquet.vectorization.enabled`.
So my thinking was that this would represent a comprehensive enumeration of
the properties to avoid confusion.
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