Company: IBM

In an e-commerce product search system, users input queries to search for items. You are given an array products of length n representing the product names and an array queries of length q containing search query strings.
Implement a function that, for each query string, returns all products that are anagrams of the query string. An anagram is any string that can be formed by rearranging the le tters of another string.

The function getProductMatches takes the following inputs:
string products[n]: the list of all available product names
string queries[q]: the list of search query strings

The function should return a list of products for each query that are anagrams of the query string, sorted alphabetically.
Example
Input:
n = 4
products = ["duel", "speed", "dule", "cars"]
q = 2
queries = ["spede", "deul"]
Output:
["speed"]
["duel", "dule"]

Explanation:
For queries[0] = "spede", the only anagram of "spede" is "speed", so the answer for this query is ["speed"].
For queries[1] = "deul", the anagrams in the product list are "duel" and "dule", so the answer for this query is ["duel", "dule"].
The function getProductMatches should return a list of lists, where each inner list contains the matching anagram products for a given query, sorted alphabetically. Show More

getQueryAnswers
In a machine learning model, there are n data entries stored in the model's output cache cacheEntries. Each entry contains three values:
1. timestamp – when the prediction was made.
2. modelId – the identifier of the machine learning model.
3. predictionValue – the model's output, represented as a string containing an integer.

A query handler receives q queries in th e form of queries[q][2], where each query consists of:
- modelId – identifying the machine learning model.
- timestamp – specifying the time at which the prediction was made.

Implement a function getQueryAnswers that:
- Takes two inputs:
- cacheEntries[n][3]: A list of cached predictions.
- queries[q][2]: A list of queries.
- Returns an array of integers, where each value corresponds to the predictionValue for the given modelId and timestamp. Show More