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* # Step 1 Throughout this interview, we'll pretend we're building a new
* analytical database. Don't worry about actually building a database though –
* these will all be toy problems.
*
* Here's how the database works: all records are represented as maps, with
* string keys and integer values. The records are contained in an array, in no
* particular order.
*
* To begin with, the database will support just one function: min_by_key. This
* function scans the array of records and returns the record that has the
* minimum value for a specified key. Records that do not contain the specified
* key are considered to have value 0 for the key. Note that keys may map to
* negative values!
*
* Here's an example use case: each of your records contains data about a school
* student. You can use min_by_key to answer questions such as "who is the
* youngest student?" and "who is the student with the lowest grade-point
* average?"
*
* Implementation notes: You should handle an empty array of records in an
* idiomatic way in your language of choice. If several records share the same
* minimum value for the chosen key, you may return any of them.
*
* ### Java function signature: ``` public static Map<String, Integer>
* minByKey(String key, List<Map<String, Integer>> records); ```
*
* ### Examples (in Python): ``` assert min_by_key("a", [{"a": 1, "b": 2}, {"a":
* 2}]) == {"a": 1, "b": 2} assert min_by_key("a", [{"a": 2}, {"a": 1, "b": 2}])
* == {"a": 1, "b": 2} assert min_by_key("b", [{"a": 1, "b": 2}, {"a": 2}]) ==
* {"a": 2} assert min_by_key("a", [{}]) == {} assert min_by_key("b", [{"a":
* -1}, {"b": -1}]) == {"b": -1} ```
*/