[SPARK-50814][DOCS] Remove unused SQL error pages

### What changes were proposed in this pull request?

Remove standalone SQL error pages that were made obsolete by the work completed in #44971.

Also fix the formatting of the error message for `QUERY_ONLY_CORRUPT_RECORD_COLUMN`, since it was incorrect and overflowing the table cell it belongs to.

### Why are the changes needed?

These error pages are either already captured completely in `common/utils/src/main/resources/error/error-conditions.json`, or are obsolete and not needed (and are not being rendered in the documentation output anyway).

The formatting of `QUERY_ONLY_CORRUPT_RECORD_COLUMN` before and after:

<img src="https://github.com/user-attachments/assets/476c57e0-dfa5-403e-8a7d-2d05301eb7a3" width=650 />
<img src="https://github.com/user-attachments/assets/106d5bca-6569-488c-9b9c-1a27345fc7a8" width=450 />

### Does this PR introduce _any_ user-facing change?

Yes, documentation formatting.

### How was this patch tested?

Built the docs locally and reviewed them in my browser.

### Was this patch authored or co-authored using generative AI tooling?

No.

Closes #49486 from nchammas/SPARK-50814-unused-error-docs.

Authored-by: Nicholas Chammas <nicholas.chammas@gmail.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>

Author: nchammas

common/utils/src/main/resources/error/error-conditions.json

@@ -5485,12 +5485,12 @@
         "message" : [
           "Queries from raw JSON/CSV/XML files are disallowed when the",
           "referenced columns only include the internal corrupt record column",
-          "(named _corrupt_record by default). For example:",
-          "spark.read.schema(schema).json(file).filter($\"_corrupt_record\".isNotNull).count()",
-          "and spark.read.schema(schema).json(file).select(\"_corrupt_record\").show().",
+          "(named `_corrupt_record` by default). For example:",
+          "`spark.read.schema(schema).json(file).filter($\"_corrupt_record\".isNotNull).count()`",
+          "and `spark.read.schema(schema).json(file).select(\"_corrupt_record\").show()`.",
           "Instead, you can cache or save the parsed results and then send the same query.",
-          "For example, val df = spark.read.schema(schema).json(file).cache() and then",
-          "df.filter($\"_corrupt_record\".isNotNull).count()."
+          "For example, `val df = spark.read.schema(schema).json(file).cache()` and then",
+          "`df.filter($\"_corrupt_record\".isNotNull).count()`."
         ]
       },
       "REMOVE_NAMESPACE_COMMENT" : {