[GitHub] srowen commented on a change in pull request #23742: [SPARK-26835][DOCS] Documentationof Spark SQL Generic Load/Save Functions options extended

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srowen commented on a change in pull request #23742: [SPARK-26835][DOCS] Documentationof Spark SQL Generic Load/Save Functions options extended
URL: https://github.com/apache/spark/pull/23742#discussion_r255691164
 
 

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 File path: docs/sql-data-sources-load-save-functions.md
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 @@ -41,6 +41,11 @@ name (i.e., `org.apache.spark.sql.parquet`), but for built-in sources you can al
 names (`json`, `parquet`, `jdbc`, `orc`, `libsvm`, `csv`, `text`). DataFrames loaded from any data
 source type can be converted into other types using this syntax.
 
+The available extra options are documented in the API documentation. For basic formats
+(like `json`, `parquet`, `jdbc`, `orc`, `csv`, `text`) you want to check the API documentation of
+`org.apache.spark.sql.DataFrameReader` and `org.apache.spark.sql.DataFrameWriter`. For other
 
 Review comment:
   You can link to, for example, http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.DataFrameWriter and http://spark.apache.org/docs/latest/api/python/pyspark.sql.html?highlight=dataframewriter#pyspark.sql.DataFrameWriter I think the Scala docs are probably most comprehensive though, and would be relevant to Pyspark users too.

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