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There could be several reasons why Spark is unable to locate the column when writing to a Hive table. Some possible reasons include:

1. Column name misspelling: The column name in the Spark dataset may be misspelled or not match the column name in the Hive table.

2. Incorrect column order: The columns in the Spark dataset may not be in the same order as the columns in the Hive table.

3. Datatype mismatch: The datatype of a column in the Spark dataset may not match with the datatype of that column in the Hive table.

4. Missing columns: The Spark dataset may be missing a column that is required in the Hive table.

5. Incorrect table name or database name: The name of the Hive table or its database may be incorrect, making it impossible for Spark to find the table.

To resolve this issue, it is important to carefully compare the column names and order, ensure that the datatypes match, ensure all required columns are present, and double-check the Hive table and database names.