Updating fields in sql dating site by contact membership of charges

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.

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.

Also, let’s say we want to make updates only for people in the company “Widget Co”.

“Bob Jones” appears in both companies, so we need to be careful to identify the company, but we don’t want to have to specify it repeatedly for each row.

So, given a list of updates to apply we could effect them using the following steps: So in the example above we can reduce five statements to four. But now the number of statements is no longer directly dependent on the number of rows requiring updates.

The columns that are not on the list retain their original values.

OK, that’s great, we have some theoretical approaches for reducing the number of queries, now what?

The code required to implement the above logic is sufficiently fiddly that we would probably not want to have to repeat it.

(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.

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But if there are a large number of rows that require an update, then the overhead of issuing large numbers of UPDATE statements can result in the operation as a whole taking a long time to complete.

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