{ "data": { "question": { "questionId": "1000039", "questionFrontendId": "面试题 17.11", "categoryTitle": "LCCI", "boundTopicId": 94601, "title": "Find Closest LCCI", "titleSlug": "find-closest-lcci", "content": "
You have a large text file containing words. Given any two different words, find the shortest distance (in terms of number of words) between them in the file. If the operation will be repeated many times for the same file (but different pairs of words), can you optimize your solution?
\r\n\r\nExample:
\r\n\r\n\r\nInput: words = ["I","am","a","student","from","a","university","in","a","city"], word1 = "a", word2 = "student"\r\nOutput: 1\r\n\r\n
Note:
\r\n\r\nwords.length <= 100000
有个内含单词的超大文本文件,给定任意两个不同的
单词,找出在这个文件中这两个单词的最短距离(相隔单词数)。如果寻找过程在这个文件中会重复多次,而每次寻找的单词不同,你能对此优化吗?
示例:
\n\n\n输入:words = [\"I\",\"am\",\"a\",\"student\",\"from\",\"a\",\"university\",\"in\",\"a\",\"city\"], word1 = \"a\", word2 = \"student\"\n输出:1\n\n
提示:
\n\nwords.length <= 100000
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out-of-bounds<\\/code> \\u548c
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OpenJDK 21<\\/code>\\u3002\\u4f7f\\u7528\\u7f16\\u8bd1\\u53c2\\u6570
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Python 2.7.18<\\/code><\\/p>\\r\\n\\r\\n
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out-of-bounds<\\/code> \\u548c
use-after-free<\\/code> \\u9519\\u8bef\\u3002<\\/p>\\r\\n\\r\\n
\\r\\nstruct hash_entry {\\r\\n int id; \\/* we'll use this field as the key *\\/\\r\\n char name[10];\\r\\n UT_hash_handle hh; \\/* makes this structure hashable *\\/\\r\\n};\\r\\n\\r\\nstruct hash_entry *users = NULL;\\r\\n\\r\\nvoid add_user(struct hash_entry *s) {\\r\\n HASH_ADD_INT(users, id, s);\\r\\n}\\r\\n<\\/pre>\\r\\n<\\/p>\\r\\n\\r\\n
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