(It will use placeholders and parameter binding if it thinks it’s appropriate.) If given our second example with two distinct values, will spot that there are two distinct values, 12, and will effect this with two UPDATE statements as described above.Optimising the number of UPDATEs by grouping the distinct SET values can be done in a way which is compatible with most common SQL databases. FROM approach requires knowledge of the specific SQL database being used.We can easily contrive for an “updates” table to exist by creating a temporary table and populating it.It is relatively straightforward to populate a table with multiple rows with just one query (or at least, far fewer queries than the number of rows desired).Similarly, let’s say we want to update two fields, salary and bonus.If we want to update more than one column, whereas previously we specified the new value using a scalar, when there is more than one column to update, we use an Array Ref.So is structured so that approaches which are generic across different SQL databases are expressed in a base class, and approaches which only work for specific SQL databases are expressed in a subclass.An object of the relevant class is instantiated when the call is made, and control then passed to the implementation relevant to the database in use.
The traditional advice for improving performance for multiple UPDATE statements is to “prepare” the required query once, and then “execute” the prepared query once for each row requiring an update.and we could persuade the database server to apply those updates to the target table?This is in fact entirely possible in many database systems.In the case of Postgre SQL, it can be done using a FROM clause with UPDATE, like this: This does an INNER JOIN between the tables “staff” and “updates” where the column “name” matches.The SET clause then takes the “salary” field from the “updates” table and uses it to update the “salary” field of the “staff” table.The dominant factor in the time taken to complete the overall operation tends to be the “admin” work in conveying the application’s intention to the database server rather than the actual updates to the database.A more effective solution to this problem is to attempt to reduce the number of UPDATE statements.In this case there are two distinct values, so we can do it in two UPDATE statements: So we can reduce the number of queries from five to two. But the extent to which this helps us reduces as the proportion of distinct SET values goes up.Eventually every SET value is different, for example: UPDATE staff SET salary = 1125 WHERE name = ' Bob'; UPDATE staff SET salary = 1200 WHERE name = ' Jane'; UPDATE staff SET salary = 1100 WHERE name = ' Frank'; UPDATE staff SET salary = 1175 WHERE name = ' Susan'; UPDATE staff SET salary = 1150 WHERE name = ' John'; Since every SET clause is now different, we can’t coalesce any queries using the approaches mentioned before, so we still have one UPDATE statement for every row requiring changes. What if we had a database table which contained a representation of the updates we wanted to make, e.g.The ‘where’ parameter can be used to specify a global condition, e.g. Another thing which we may want to do is update a column with the same value for all rows being updated. Rather than have to specify the same value over and over again, we can use the ‘set’ parameter.The ‘set’ parameter takes a Hash Ref whose keys are the columns to be updated.