What is the approach for universal search on Idea?

There are several main methods for global search:

1. Linear search: searching through each item one by one until the desired result is found. This is the simplest search method, but it is not very efficient in large-scale data.

2. Binary search: searching ordered data by narrowing down the search range by half each time until the target is found. This method is more efficient and suitable for ordered data.

3. Hash table: mapping data to a unique index value using a hash function, and then quickly searching for the target using the index value. Hash tables are suitable for large-scale data and have the advantage of fast searches.

4. Tree search: using tree structures such as binary search trees, balanced search trees, and B-trees for searching. Tree structures can quickly locate targets by comparing sizes.

5. Graph search: suitable for searching directed or undirected graphs, with common algorithms including breadth-first search (BFS) and depth-first search (DFS).

6. Text search: suitable for searching for targets in text, with common algorithms including KMP algorithm, Boyer-Moore algorithm, and regular expressions.

These are common methods of global search, and the specific choice of method depends on the type of data, the scale of data, and the search requirements.