Using wildcards (asterisks; *) in the skills/keywords field can quickly put a heavy load on our servers. Here are seven reasons why we have restricted this field to five wildcards.

Reasons for Limitation

1. Explosion of Terms: When multiple wildcards are used, Elastic Search generates an enormous number of terms to find matches. This results in a massive set of matches that the server must process.

2. Complexity of the Query: Using too many wildcards can unnecessarily complicate the query. This leads to longer processing times and increased server load.

3. Index Performance: Searching through indexes with many wildcards can be inefficient. Elastic Search must sift through numerous index postings to find matches, causing delayed response times.

4. Memory Usage: The explosion of terms can significantly increase memory usage on the server, especially if the query involves large indexes.

5. Network Load: If the Elastic Search server is hosted remotely, generating and transmitting a large volume of search results over the network can cause additional strain.

6. Cache Effectiveness: A high number of wildcards can reduce cache effectiveness, as each new query may generate a new set of terms that have not been cached before.

7. Resource Overload: The server can become overloaded when processing a large number of complex queries simultaneously, which can impact overall performance.

In summary, using more than five wildcards in a Boolean search can lead to a significant increase in the load on the Elastic Search server, resulting in longer processing times, higher memory usage, and reduced performance. Therefore, it is advisable to optimize queries and limit the use of wildcards to reduce server load.