@@ -66,8 +66,8 @@ Specify Known Fields with Schema Hints
6666~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
6767
6868You can specify a schema containing known field values to use during
69- schema inference by specifying the ``schemaHint `` configuration option. You can
70- specify the ``schemaHint `` option in any of the following Spark formats:
69+ schema inference by specifying the ``schemaHints `` configuration option. You can
70+ specify the ``schemaHints `` option in any of the following Spark formats:
7171
7272.. list-table::
7373 :header-rows: 1
@@ -90,7 +90,7 @@ specify the ``schemaHint`` option in any of the following Spark formats:
9090 { "name": "<field name>", "type": "<field type>", "nullable": <true/false> },
9191 { "name": "<field name>", "type": "<field type>", "nullable": <true/false> }]}
9292
93- The following example shows how to specify the ``schemaHint `` option in each
93+ The following example shows how to specify the ``schemaHints `` option in each
9494format by using the Spark shell. The example specifies a string-valued field named
9595``"value"`` and an integer-valued field named ``"count"``.
9696
@@ -114,7 +114,7 @@ format by using the Spark shell. The example specifies a string-valued field nam
114114 // Generate JSON format
115115 mySchema.json
116116
117- You can also specify the ``schemaHint `` option in the Simple String DDL format,
117+ You can also specify the ``schemaHints `` option in the Simple String DDL format,
118118or in JSON format by using PySpark, as shown in the following example:
119119
120120.. code-block:: python
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