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Findrow() is highly optimized and can do over 10 million searches per second. This makes findrow() ideal for tasks that require fast lookups. Given the cluster name, cluster field to search in, and data to searched for, findrow() returns the first row where the key was found or returns a 0 if the key was not found.
To handle duplicate keys, findrow() has an optional third parameter to find the Nth occurrence of a key.
- All fields of a cluster, regardless of data type, are searchable as a key
- All keys are changeable
- All keys can contain duplicates
- All key searches take O(1) constant time -- virtually instant lookups
Because all cluster fields are keys, bi-directional lookups are easy to do. In our example we will translate from English to German and German to English.
To define a cluster, use the cluster statement followed by the name of the cluster. In our example, we are calling our cluster trans. Our trans cluster has two fields: english$ and german$. To reference them we use trans->english$ and trans->german$.
Program Explanation:
1. Cluster Definition:
A cluster named trans is defined to store English words and their corresponding German translations. The cluster has two fields: english$ for English words and german$ for German words.
2. Adding Data:
The program adds entries to the trans cluster:
- The English word
'apple'is paired with the German word'der Apfel'. - The English word
'banana'is paired with the German word'die Banane'.
3. User Input Assignment:
The variable word$ is assigned the value of a$, which is assumed to be a word entered by the user that they want to translate.
4. Searching for English Word:
The program searches the trans cluster for a row where the english$ field matches word$ (the word entered by the user). The row number is stored in the variable row.
5. English to German Translation:
If the word is found (row > 0), the program prints the English word followed by its German translation, using ' >> ' as the separator. The loop then exits since the translation has been found.
6. Searching for German Word:
If the word wasn't found in the English field, the program then searches the trans cluster for a row where the german$ field matches word$.
7. German to English Translation:
If the word is found in the German field (row > 0), the program prints the German word followed by its English translation, again using ' >> ' as the separator. The loop then exits since the translation has been found.
8. No Translation Found:
If the word is not found in either the English or German fields, the program prints a message indicating that there is no translation available for the word entered by the user.
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