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