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You need defining conditions to define how the rows of the table can be mapped to pattern components A , B , C and D : As you can see, the conditions can refer to other pattern components ( C depends on A ), or the sequential match number ( D ). After finding a match, you can step one row forward and search for another one. Time to get more technical # In the preceding examples, the pattern consisted of components A , B , C and D . They were chosen this way to capture the analogy between pattern matching in a string and pattern matching in a set of rows. According to the SQL specification, row pattern components can be named with arbitrary identifiers, as long as they are compliant with the SQL identifier semantics, so you don’t need to limit yourself to single-letter names, and instead you can use more verbose labels. PATTERN( START DOWN+ UP+ ) DEFINE DOWN AS price PREV(price) The preceding example shows the two key clauses of row pattern recognition: PATTERN and DEFINE . Let’s see what other keywords there are in the MATCH_RECOHNIZE clause. The MATCH_RECOGNIZE syntax is long and rich enough to capture everything that a pattern matching tool needs, and all the options which let you easily toggle your matching strategies.
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