.. _auto_sql_create_table:

*CREATES A SQL TABLE*
=====================

Accepts a dataset, sanitizes its column names (lowercasing, removing reserved SQL words, enforcing uniqueness up to 63 characters), creates a new SQL table with a SHA1-hashed name prefixed by `d3view_table_`, and inserts all rows. Use this worker to persist an in-memory or pipeline dataset into a queryable SQL table for downstream SQL-based workers.

When to use
-----------

Tagged: ``column_sanitization``, ``create_table``, ``dataset``, ``db``, ``sql``, ``workflows``.

Inputs
------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20 20 20

   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Dataset
     - dataset
     - dataset
     - —
     - ✓
     - Tabular dataset (array of associative rows) to be materialized as a SQL table; must be non-empty — each row's keys become sanitized SQL column names.

Outputs
-------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20

   * - Label
     - ID
     - Type
     - Description
   * - New Table Name
     - new_table_name
     - string
     - Fully-qualified name of the newly created SQL table (format: `d3view_table_<sha1_hash>`); pass this to downstream SQL workers to query the data.
   * - Column Map (original to cleaned)
     - column_map
     - string
     - JSON-serializable map of original dataset column names to their sanitized SQL equivalents (e.g., `{"My Column!": "my_column"}`); use this to translate results back to original field names.

Disciplines
-----------

- data.dataset.transform
- data.io.sql

.. raw:: html

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   Auto-generated from <code>platform</code> schema. Worker id: <code>sql_create_table</code>. Schema hash: <code>ce1b6208987c</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
   </p>