"use strict"; const {Fragment: _Fragment, jsx: _jsx, jsxs: _jsxs} = arguments[0]; const {useMDXComponents: _provideComponents} = arguments[0]; function _createMdxContent(props) { const _components = { a: "a", annotation: "annotation", code: "code", figure: "figure", h2: "h2", img: "img", li: "li", math: "math", mi: "mi", mo: "mo", mrow: "mrow", p: "p", pre: "pre", semantics: "semantics", span: "span", ul: "ul", ..._provideComponents(), ...props.components }; return _jsxs(_Fragment, { children: [_jsx(_components.p, { children: _jsx(_components.a, { href: "https://www.acmicpc.net/problem/7662", children: "문제 링크" }) }), "\n", _jsx(_components.h2, { children: "문제" }), "\n", _jsx(_components.p, { children: "이중 우선순위 큐(dual priority queue)는 전형적인 우선순위 큐처럼 데이터를 삽입, 삭제할 수 있는 자료 구조이다. 전형적인 큐와의 차이점은 데이터를 삭제할 때 연산(operation) 명령에 따라 우선순위가 가장 높은 데이터 또는 가장 낮은 데이터 중 하나를 삭제하는 점이다. 이중 우선순위 큐를 위해선 두 가지 연산이 사용되는데, 하나는 데이터를 삽입하는 연산이고 다른 하나는 데이터를 삭제하는 연산이다. 데이터를 삭제하는 연산은 또 두 가지로 구분되는데 하나는 우선순위가 가장 높은 것을 삭제하기 위한 것이고 다른 하나는 우선순위가 가장 낮은 것을 삭제하기 위한 것이다." }), "\n", _jsx(_components.p, { children: "정수만 저장하는 이중 우선순위 큐 Q가 있다고 가정하자. Q에 저장된 각 정수의 값 자체를 우선순위라고 간주하자." }), "\n", _jsx(_components.p, { children: "Q에 적용될 일련의 연산이 주어질 때 이를 처리한 후 최종적으로 Q에 저장된 데이터 중 최댓값과 최솟값을 출력하는 프로그램을 작성하라." }), "\n", _jsx(_components.h2, { children: "입력" }), "\n", _jsx(_components.p, { children: "입력 데이터는 표준입력을 사용한다. 입력은 T개의 테스트 데이터로 구성된다. 입력의 첫 번째 줄에는 입력 데이터의 수를 나타내는 정수 T가 주어진다. 각 테스트 데이터의 첫째 줄에는 Q에 적용할 연산의 개수를 나타내는 정수 k (k ≤ 1,000,000)가 주어진다. 이어지는 k 줄 각각엔 연산을 나타내는 문자(‘D’ 또는 ‘I’)와 정수 n이 주어진다. ‘I n’은 정수 n을 Q에 삽입하는 연산을 의미한다. 동일한 정수가 삽입될 수 있음을 참고하기 바란다. ‘D 1’는 Q에서 최댓값을 삭제하는 연산을 의미하며, ‘D -1’는 Q 에서 최솟값을 삭제하는 연산을 의미한다. 최댓값(최솟값)을 삭제하는 연산에서 최댓값(최솟값)이 둘 이상인 경우, 하나만 삭제됨을 유념하기 바란다." }), "\n", _jsx(_components.p, { children: "만약 Q가 비어있는데 적용할 연산이 ‘D’라면 이 연산은 무시해도 좋다. Q에 저장될 모든 정수는 -2^31 이상 2^31 미만인 정수이다." }), "\n", _jsx(_components.h2, { children: "출력" }), "\n", _jsx(_components.p, { children: "출력은 표준출력을 사용한다. 각 테스트 데이터에 대해, 모든 연산을 처리한 후 Q에 남아 있는 값 중 최댓값과 최솟값을 출력하라. 두 값은 한 줄에 출력하되 하나의 공백으로 구분하라. 만약 Q가 비어있다면 ‘EMPTY’를 출력하라." }), "\n", _jsx(_components.h2, { children: "풀이" }), "\n", _jsx(_components.p, { children: "최댓값과 최솟값을 둘 다 빠르게 꺼내야 하므로 힙을 하나만 써서는 부족하다. 최소 힙과 최대 힙을 함께 두고, 삭제 여부는 별도로 관리하는 lazy deletion 방식이 잘 맞는다." }), "\n", _jsxs(_components.p, { children: ["코드에서는 삽입할 때 두 힙에 모두 넣고, 삭제 연산 후에는 각 힙에서 유효하지 않은 값이 top에 남아 있는 동안 정리한다. ", _jsx(_components.code, { children: "map" }), "가 현재 남아 있는 값의 개수를 관리하므로, 두 힙이 서로 다른 시점에 삭제되더라도 최댓값과 최솟값을 맞춰 출력할 수 있다."] }), "\n", _jsx(_components.p, { children: "즉 한 자료구조가 아니라 두 힙과 삭제 동기화가 핵심이다." }), "\n", _jsx(_components.h2, { children: "코드" }), "\n", _jsx(_components.figure, { "data-rehype-pretty-code-figure": "", children: _jsx(_components.pre, { style: { backgroundColor: "#2e3440ff", color: "#d8dee9ff" }, tabIndex: "0", "data-language": "cpp", "data-theme": "nord", children: _jsxs(_components.code, { "data-language": "cpp", "data-theme": "nord", style: { display: "grid" }, children: [_jsxs(_components.span, { "data-line": "", children: [_jsx(_components.span, { style: { color: "#5E81AC", fontWeight: "bold" }, children: "#" }), _jsx(_components.span, { style: { color: "#81A1C1" }, children: "include" }), _jsx(_components.span, { style: { color: "#ECEFF4" }, children: " <" }), _jsx(_components.span, { style: { color: "#A3BE8C" }, children: "iostream" }), _jsx(_components.span, { 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BOJ 7662 - 이중 우선순위 큐