HyukjinKwon commented on a change in pull request #32658:
URL: https://github.com/apache/spark/pull/32658#discussion_r640506244
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File path: docs/sql-data-sources-csv.md
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@@ -38,3 +36,223 @@ Spark SQL provides `spark.read().csv("file_name")` to read
a file or directory o
</div>
</div>
+
+## Data Source Option
+
+Data source options of CSV can be set via:
+* the `.option`/`.options` methods of
+ * `DataFrameReader`
+ * `DataFrameWriter`
+ * `DataStreamReader`
+ * `DataStreamWriter`
+* the built-in functions below
+ * `from_csv`
+ * `to_csv`
+ * `schema_of_csv`
+* `OPTIONS` clause at [CREATE TABLE USING
DATA_SOURCE](sql-ref-syntax-ddl-create-table-datasource.html)
+
+
+<table class="table">
+ <tr><th><b>Property
Name</b></th><th><b>Default</b></th><th><b>Meaning</b></th><th><b>Scope</b></th></tr>
+ <tr>
+ <td><code>sep</code></td>
+ <td>,</td>
+ <td>Sets a separator (one or more characters) for each field and
value.</td>
+ <td>read/write</td>
+ </tr>
+ <tr>
+ <td><code>encoding</code></td>
+ <td><code>UTF-8</code> for reading, not set for writing</td>
+ <td>For reading, decodes the CSV files by the given encoding type.</td>
Review comment:
what about writing?
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