From 1ebf2a45fecc8dd90732a8f5fa53079be087ab7f Mon Sep 17 00:00:00 2001
From: pbr4nzfkh <18879212807@163.com>
Date: Sun, 17 Mar 2024 10:22:05 +0800
Subject: [PATCH] =?UTF-8?q?tf-91=E5=A4=9A=E7=BA=BF=E7=A8=8B=E6=A8=A1?=
 =?UTF-8?q?=E5=BC=8F?=
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---
 计算设备/map-reduce/tf-91.py | 56 ++++++++++++++++++++++++++++++++
 1 file changed, 56 insertions(+)
 create mode 100644 计算设备/map-reduce/tf-91.py

diff --git a/计算设备/map-reduce/tf-91.py b/计算设备/map-reduce/tf-91.py
new file mode 100644
index 0000000..4c50a18
--- /dev/null
+++ b/计算设备/map-reduce/tf-91.py
@@ -0,0 +1,56 @@
+# -*- coding: utf-8 -*-
+from collections import Counter
+from cppy.cp_util import *
+from multiprocessing.pool import ThreadPool
+
+
+#
+# 多线程
+#
+def process_chunk(chunk):
+    # 过滤停用词
+    stop_words = get_stopwords()
+    words = [ w for w in chunk if ( not w in stop_words ) and len(w) >= 3 ]
+    return Counter(words)
+
+
+def merge_counts(counts_list):
+    # 合并多个Counter对象
+    total_counts = Counter()
+    for counts in counts_list:
+        total_counts += counts
+    return total_counts
+
+
+def thread_function(chunk, counts_list):
+    word_count = process_chunk(chunk)
+    counts_list.append(word_count)
+
+
+@timing_decorator
+def main():
+    # 读取文件内容
+    content = re_split(read_file(testfilepath))
+    chunk_size = 1000 # 可以根据实际情况调整块大小
+    chunks = [content[i:i + chunk_size] for i in range(0, len(content), chunk_size)]
+
+    # 使用多线程池，每个线程处理一个块
+    pool = ThreadPool(len(content)//chunk_size+1)
+    counts_list = pool.map(process_chunk, chunks)
+    pool.close()
+    pool.join()
+
+    # 合并计数
+    total_counts = merge_counts(counts_list)
+
+    # 输出最高频的n个词
+    print_word_freqs(total_counts.most_common(10))
+
+
+if __name__ == '__main__':
+    main()
+
+
+
+
+