It is a bit easier to follow this means

which displays per-product sales totals in only the top sales regions. Having clause defines two auxiliary statements named regional_conversion process and top_nations, where the output of regional_conversion process is used in top_nations and the output of top_countries is used in the priple could have been written without That have, but we’d have needed two levels of nested sub-Look fors.

Yet not, have a tendency to a pattern does not involve returns rows that are entirely duplicate: it can be had a need to take a look at just one or a number of industries to find out if a comparable part might have been achieved just before

optional RECURSIVE modifier changes With from a mere syntactic convenience into a feature that accomplishes things not otherwise possible in standard SQL. Using RECURSIVE, a With query can refer to its own output. A very simple example is this query to sum the integers from 1 through 100:

general form of a recursive Which have query is always a non-recursive term, then Union (or Partnership All), then a recursive term, where only the recursive term can contain a reference to the query’s own output. Such a query is executed as follows:

Evaluate the non-recursive term. For Partnership (but not Connection The), discard duplicate rows. Include all remaining rows in the result of the recursive query, and also place them in a temporary working table.

Evaluate the recursive term, substituting the current contents of the working table for the recursive self-reference. For Union (but not Union All), discard duplicate rows and rows that duplicate any previous result row. Include all remaining rows in the result of the recursive query, and also place them in a temporary intermediate table

Note: Strictly speaking, this process is iteration not recursion, but RECURSIVE is the terminology chosen by the SQL standards committee.

In the example above, the working table has just a single row in each step, and it takes on the values from 1 through 100 in successive steps. In the 100th step, there is no output because of the Where clause, and so the query terminates.

Recursive concerns are generally regularly deal with hierarchical otherwise tree-prepared analysis. A helpful example so is this query locate most of the lead and indirect sub-components of a product or service, offered just a table that presents instant inclusions:

When working with recursive queries it is important to be sure that the recursive part of the query will eventually return no tuples, or else the query will loop indefinitely. Sometimes, using Union instead of Commitment Every can accomplish this by discarding rows that duplicate previous output rows. standard method for handling such situations is to compute an array of the already-visited values. For example, consider the following query that searches a table chart using a hook field:

This query will loop if the link relationships contain cycles. Because we require a “depth” output, just changing Connection Most of the to Connection would not eliminate the looping. Instead we need to recognize whether we have reached the same row again while following a particular road of links. We add two columns path and cycle to the loop-prone query:

Aside from blocking schedules, the selection worth is sometimes helpful in a unique best as the symbolizing the latest “path” brought to arrived at any kind of line.

In the general case where more than one field needs to be checked to recognize a cycle, use an array of rows. For example, if we needed to compare fields f1 and f2:


Tip: Omit the ROW() syntax in the common case where only one field needs to be checked to recognize a cycle. This allows a simple array rather than a composite-type array to be used, gaining efficiency.