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Inserting All Columns
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As a convenience, SQL allows you to omit the column list from the INSERT statement. When the column list is omitted, SQL automatically generates a column list consisting of all columns of the table, in left-to-right sequence. This is the same column sequence generated by SQL when you use a SELECT * query. Using this shortcut, the previous INSERT statement could be rewritten equivalently as: INSERT INTO SALESREPS VALUES (111, 'Henry Jacobsen', 36, 13, 'Sales Mgr', '25-JUL-90', NULL, NULL, 0.00) When you omit the column list, the NULL keyword must be used in the values list to explicitly assign NULL values to columns, as shown in the example. In addition, the sequence of data values must correspond exactly to the sequence of columns in the table. Omitting the column list is convenient in interactive SQL because it reduces the length of the INSERT statement you must type. For programmatic SQL, the column list should always be specified because it makes the program easier to read and understand.
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The Multi-Row INSERT Statement
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The second form of the INSERT statement, shown in Figure 10-3, adds multiple rows of data to its target table. In this form of the INSERT statement, the data values for the new rows are not explicitly specified within the statement text. Instead, the source of new rows is a database query, specified in the statement.
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Figure 10-3: Multi-row INSERT statement syntax diagram
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Adding rows whose values come from within the database itself may seem strange at first, but it's very useful in some special situations. For example, suppose that you want to copy the order number, date, and amount of all orders placed before January 1, 1990, from the ORDERS table into another table, called OLDORDERS. The multi-row INSERT statement provides a compact, efficient way to copy the data: Copy old orders into the OLDORDERS table. INSERT INTO OLDORDERS (ORDER_NUM, ORDER_DATE, AMOUNT) SELECT ORDER_NUM, ORDER_DATE, AMOUNT
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FROM ORDERS WHERE ORDER_DATE < '01-JAN-90' 9 rows inserted. This INSERT statement looks complicated, but it's really very simple. The statement identifies the table to receive the new rows (OLDORDERS) and the columns to receive the data, just like the single-row INSERT statement. The remainder of the statement is a query that retrieves data from the ORDERS table. Figure 10-4 graphically illustrates the operation of this INSERT statement. Conceptually, SQL first performs the query against the ORDERS table and then inserts the query results, row by row, into the OLDORDERS table.
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Figure 10-4: Inserting multiple rows
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Here's another situation where you could use the multi-row INSERT statement. Suppose you want to analyze customer-buying patterns by looking at which customers and salespeople are responsible for big orders those over $15,000. The queries that you will be running will combine data from the CUSTOMERS, SALESREPS, and ORDERS tables. These three-table queries will execute fairly quickly on the small sample database, but in a real corporate database with many thousands of rows, they would take a long time. Rather than running many long, three-table queries, you could create a new table named BIGORDERS to contain the required data, defined as follows: Column AMOUNT COMPANY NAME PERF MFR PRODUCT QTY Information Order amount (from ORDERS) Customer name (from CUSTOMERS) Salesperson name (from SALESREPS) Amount over/under quota (calculated from SALESREPS) Manufacturer id (from ORDERS) Product id (from ORDERS) Quantity ordered (from ORDERS)
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Once you have created the BIGORDERS table, this multi-row INSERT statement can be
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6 rows inserted. In a large database, this INSERT statement may take a while to execute because it involves a three-table query. When the statement is complete, the data in the BIGORDERS table will duplicate information in other tables. In addition, the BIGORDERS table won't be automatically kept up to date when new orders are added to the database, so its data may quickly become outdated. Each of these factors seems like a disadvantage. However, the subsequent data analysis queries against the BIGORDERS table can be expressed very simply they become single-table queries. Furthermore, each of those queries will run much faster than if it were a three-table join. Consequently, this is probably a good strategy for performing the analysis, especially if the three original tables are large. The SQL1 standard specified several logical restrictions on the query that appears within the multi-row INSERT statement: The query cannot contain an ORDER BY clause. It's useless to sort the query results anyway, because they're being inserted into a table that is, like all tables, unordered. The query results must contain the same number of columns as the column list in the INSERT statement (or the entire target table, if the column list is omitted), and the data types must be compatible, column by column. The query cannot be the UNION of several different SELECT statements. Only a single SELECT statement may be specified. The target table of the INSERT statement cannot appear in the FROM clause of the query or any subqueries that it contains. This prohibits inserting part of a table into itself. The first two restrictions are structural, but the latter two were included in the standard simply to avoid complexity. As a result, these restrictions were relaxed in the SQL2 standard. The standard now allows UNION and join operations and expressions in the query, basically allowing the results of a general database query to be retrieved and then inserted into a table with the INSERT statement. It also allows various forms of "selfinsertion," where the source table for the data to be inserted and destination table are the same.
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