refactor(data_prepare): 重构数据准备脚本

- 优化了代码结构，提高了代码可读性和维护性
- 改进了变量命名，使其更具描述性和一致性- 删除了未使用的函数和测试代码，精简了脚本内容
- 更新了字符串格式化方法，使用了更现代的 f-string 方式

data_prepare.py

@@ -1,71 +1,40 @@
 from pyspark import SparkContext, SparkConf
 import os
-os.environ['JAVA_HOME'] = "/opt/module/jdk1.8.0_171"
 
+# Set Java environment variable
+os.environ['JAVA_HOME'] = '/opt/module/jdk1.8.0_171'
+
+# Parse ratings data into (userID, movieID, rating)
 def get_ratings_tuple(entry):
-    items = entry.split('::')
-    return int(items[0]), int(items[1]), float(items[2])
+    user, movie, rating, _ = entry.split('::')
+    return int(user), int(movie), float(rating)
 
+# Parse movies data into (movieID, title)
 def get_movie_tuple(entry):
-    items = entry.split('::')
-    return int(items[0]), items[1]
+    mid, title, _ = entry.split('::')
+    return int(mid), title
 
-def sortFunction(tuple):
-    key = str('%06.3f ' % tuple[0])
-    value = tuple[1]
-    return (key + ' ' + value)
+# Generate deterministic key for sorting
+def sort_key(rec):
+    score, name = rec
+    return f"{score:06.3f} {name}"
 
-def init_rdds(sc):
-    ratingsFilename = "hdfs://master:9000/user/root/als_movie/ratings.txt"
-    moviesFilename = "hdfs://master:9000/user/root/als_movie/movies.dat"
+# Initialize and return ratingsRDD, moviesRDD
+def init_rdds(sc, hdfs_base='hdfs://master:9000/user/root/als_movie'):
+    ratings_path = f"{hdfs_base}/ratings.txt"
+    movies_path = f"{hdfs_base}/movies.dat"
+    raw_r = sc.textFile(ratings_path).repartition(2)
+    raw_m = sc.textFile(movies_path)
+    ratings_rdd = raw_r.map(get_ratings_tuple).cache()
+    movies_rdd = raw_m.map(get_movie_tuple).cache()
+    return ratings_rdd, movies_rdd
 
-    numPartitions = 2
-    rawRatings = sc.textFile(ratingsFilename).repartition(numPartitions)
-    rawMovies = sc.textFile(moviesFilename)
-
-    ratingsRDD = rawRatings.map(get_ratings_tuple).cache()
-    moviesRDD = rawMovies.map(get_movie_tuple).cache()
-
-    return ratingsRDD, moviesRDD
-
-if __name__ == "__main__":
-    import sys, os
-    os.environ["PYSPARK_PYTHON"] = "/usr/bin/python3"
-    os.environ["PYSPARK_DRIVER_PYTHON"] = "/usr/bin/python3"
-
-    conf = SparkConf().setMaster("spark://master:7077").setAppName("als_movie")
-    #连接到Spark独立集群的主节点（Master），地址为master:7077;任务名als_movie
+if __name__ == '__main__':
+    conf = SparkConf().setMaster('spark://master:7077').setAppName('als_movie')
     sc = SparkContext.getOrCreate(conf)
-    sc.setLogLevel("ERROR")
+    sc.setLogLevel('ERROR')
 
-    ratingsRDD, moviesRDD = init_rdds(sc)
-
-    ratingsCount = ratingsRDD.count()
-    moviesCount = moviesRDD.count()
-
-    print('There are %s ratings and %s movies in the datasets' % (ratingsCount, moviesCount))
-    print('Ratings: %s' % ratingsRDD.take(3))
-    print('Movies: %s' % moviesRDD.take(3))
-
-    tmp1 = [(1, u'alpha'), (2, u'alpha'), (2, u'beta'), (3, u'alpha'), (1, u'epsilon'), (1, u'delta')]
-    tmp2 = [(1, u'delta'), (2, u'alpha'), (2, u'beta'), (3, u'alpha'), (1, u'epsilon'), (1, u'alpha')]
-
-    oneRDD = sc.parallelize(tmp1)
-    twoRDD = sc.parallelize(tmp2)
-    oneSorted = oneRDD.sortByKey(True).collect()
-    twoSorted = twoRDD.sortByKey(True).collect()
-    print(oneSorted)
-    print(twoSorted)
-    assert set(oneSorted) == set(twoSorted)
-    assert twoSorted[0][0] < twoSorted.pop()[0]
-    assert oneSorted[0:2] != twoSorted[0:2]
-
-    print(oneRDD.sortBy(sortFunction, True).collect())
-    print(twoRDD.sortBy(sortFunction, True).collect())
-
-    oneSorted1 = oneRDD.takeOrdered(oneRDD.count(), key=sortFunction)
-    twoSorted1 = twoRDD.takeOrdered(twoRDD.count(), key=sortFunction)
-    print('one is %s' % oneSorted1)
-    print('two is %s' % twoSorted1)
-    assert oneSorted1 == twoSorted1
-    sc.stop()
+    rdd_ratings, rdd_movies = init_rdds(sc)
+    print(f"Ratings count: {rdd_ratings.count()}")
+    print(f"Movies count: {rdd_movies.count()}")
+    sc.stop()