Transferring Data Between Tables in SQLite: Mastering the `SELECT INTO` Approach

2. Construct the Query:

   INSERT INTO target_table (column1, column2, ..., columnN)
   SELECT source_column1, source_column2, ..., source_columnN
   FROM source_table;
   

   • Replace target_table with the name of the table where you want to copy the data.
   • List the specific columns (comma-separated) from the source table (source_table) that you want to copy. These should correspond to existing columns (with compatible data types) in the target table.
   • In the SELECT clause, list the corresponding column names from the source table that match the selected columns in the INSERT clause.

Example:

Assuming you have tables customers and orders, with customers having columns customer_id, name, email, and orders having columns order_id, customer_id, and product:

INSERT INTO orders (customer_id, product)
SELECT customer_id, "placeholder_product"  -- Assuming product is required in orders table
FROM customers;

This will copy the customer_id from customers to orders and insert a placeholder value ("placeholder_product") for the product column (assuming it's required).

Method 2: Creating a New Table with All Columns

CREATE TABLE combined_data (
  customer_id INTEGER,
  name TEXT,
  email TEXT,
  order_id INTEGER,
  product TEXT
);

INSERT INTO combined_data
SELECT *
FROM customers;

INSERT INTO combined_data (customer_id, product)
SELECT customer_id, "placeholder_product"
FROM orders;

This creates a new table combined_data with all columns from both customers and orders, then populates it with data from each table.

Choosing the Right Method:

• Selective Copy: Use Method 1 if you only need to copy specific columns and potentially modify values during the copy process.
• Complete Copy with New Table: Use Method 2 if you want a new table that holds all data from both source and target tables, even if some columns might be redundant.

Additional Considerations:

• Data Type Compatibility: Ensure that the data types of the columns you're copying are compatible between the source and target tables. SQLite may perform implicit conversions if possible, but it's best to avoid potential errors.
• Default Values: If the target table has columns with default values that aren't explicitly included in the INSERT statement, those default values will be used.
• Constraints: Be mindful of constraints (like primary keys) on the target table. You might need to adjust the query to handle them appropriately.

-- Assuming tables: customers (customer_id INTEGER PRIMARY KEY, name TEXT, email TEXT)
--                  orders (order_id INTEGER PRIMARY KEY, customer_id INTEGER REFERENCES customers(customer_id), product TEXT)

-- Check data type compatibility (assuming product in orders is TEXT)
PRAGMA table_info(orders); -- View table structure to verify data types

-- Copy customer_id and handle potential missing product values
INSERT INTO orders (customer_id, product)
SELECT c.customer_id,
       CASE WHEN o.product IS NULL THEN "No product specified" ELSE o.product END  -- Handle NULL values
FROM customers c
LEFT JOIN orders o ON c.customer_id = o.customer_id;  -- Include rows from customers even if no order exists

This example:

• Checks data type compatibility using PRAGMA table_info.
• Selectively copies customer_id and handles potential NULL values in the product column of the orders table.
• Uses a LEFT JOIN to include rows from customers even if there's no corresponding order.

Method 2: Complete Copy with New Table

-- Assuming tables: customers (customer_id INTEGER PRIMARY KEY, name TEXT, email TEXT)
--                  orders (order_id INTEGER PRIMARY KEY, customer_id INTEGER REFERENCES customers(customer_id), product TEXT)

CREATE TABLE combined_data (
  customer_id INTEGER PRIMARY KEY REFERENCES customers(customer_id),  -- Set primary key constraint
  name TEXT,
  email TEXT,
  order_id INTEGER REFERENCES orders(order_id),  -- Set foreign key constraint (optional)
  product TEXT
);

INSERT INTO combined_data
SELECT *
FROM customers;

INSERT INTO combined_data (customer_id, name, email, order_id, product)
SELECT o.customer_id, c.name, c.email, o.order_id, o.product
FROM orders o
INNER JOIN customers c ON o.customer_id = c.customer_id;  -- Ensure matching rows

• Creates a new table combined_data with all columns from both tables, including primary and foreign key constraints (optional).
• Copies data from customers using SELECT *.
• Copies data from orders with explicit column selection and an INNER JOIN to ensure matching rows.

• This method can be useful if you need to perform intermediate data manipulation before inserting it into the target table.
• Create a temporary table with the desired structure.
• Populate the temporary table using a SELECT query from the source table, potentially with transformations.
• Insert the data from the temporary table into the target table using INSERT INTO.

CREATE TEMPORARY TABLE temp_data (
  customer_id INTEGER,
  name TEXT UPPERCASE  -- Example transformation
);

INSERT INTO temp_data
SELECT customer_id, name
FROM customers;

INSERT INTO target_table (customer_id, some_other_column)
SELECT customer_id, "default_value"  -- Assuming some_other_column has a default value
FROM temp_data;

DROP TABLE temp_data;

Considerations:

• Temporary tables are not persisted across database connections.
• This approach might have performance implications for large datasets.

Using Triggers (for ongoing data synchronization):

• Triggers are database objects that execute automatically in response to specific events (like INSERT, UPDATE, or DELETE) on a table.
• You can create a trigger on the source table that fires an INSERT statement whenever a new row is inserted, effectively replicating the data to the target table.

Example (simplified, for illustration):

CREATE TRIGGER copy_data
AFTER INSERT ON source_table
FOR EACH ROW
BEGIN
  INSERT INTO target_table (column1, column2, ...)
  VALUES (NEW.column1, NEW.column2, ...);
END;

• Triggers can add complexity to your database schema.
• They can impact performance, especially for high-volume inserts.
• Ensure your triggers are designed to handle potential conflicts or race conditions.

• For simple, one-time data copies, the SELECT INTO methods (explained earlier) are generally efficient.
• If you need to transform data before copying, consider temporary tables.
• For ongoing data synchronization, triggers can be an option, but use them with caution and proper design.