当前有一个数据集包含两个句子，如下： “Apache Spark has its architectural foundation in the resilient distributed dataset” “Inside Apache Spark dataset is managed as a resilient distributed dataset” 请基于Spark写出针对该数据集的词频统计算法，以及每一步执行之后，collect函数的返回值。

以下是基于Spark的针对该数据集的词频统计算法的代码：

from pyspark import SparkContext, SparkConf

# 创建SparkConf和SparkContext
conf = SparkConf().setAppName("wordcount").setMaster("local")
sc = SparkContext(conf=conf)

# 读取文本数据，并将其转化为一个RDD
text_rdd = sc.textFile("path/to/text/file")

# 对RDD中的每一行数据进行切分，得到单词列表
words_rdd = text_rdd.flatMap(lambda line: line.split(" "))

# 将单词列表转化为一个包含单词与出现次数的元组列表
word_count_rdd = words_rdd.map(lambda word: (word, 1))

# 对元组列表中每一个元素的计数值进行求和，得到每个单词的总出现次数
word_count_rdd = word_count_rdd.reduceByKey(lambda x, y: x + y)

# 将单词与总出现次数的元组列表按照总出现次数降序排序
word_count_rdd = word_count_rdd.sortBy(lambda x: x[1], ascending=False)

# 输出排序结果
print(word_count_rdd.collect())

每个步骤执行之后，collect函数的返回值如下：

1. 读取文本数据：返回一个包含两个句子的RDD，即`["Apache Spark has its architectural foundation in the resilient distributed dataset", "Inside Apache Spark dataset is managed as a resilient distributed dataset"]`。
2. 对RDD中的每一行数据进行切分：返回一个包含所有单词的RDD，即`["Apache", "Spark", "has", "its", "architectural", "foundation", "in", "the", "resilient", "distributed", "dataset", "Inside", "Apache", "Spark", "dataset", "is", "managed", "as", "a", "resilient", "distributed", "dataset"]`。
3. 将单词列表转化为一个包含单词与出现次数的元组列表：返回一个包含所有单词及其出现次数的元组列表，即`[("Apache", 1), ("Spark", 1), ("has", 1), ("its", 1), ("architectural", 1), ("foundation", 1), ("in", 1), ("the", 1), ("resilient", 1), ("distributed", 1), ("dataset", 1), ("Inside", 1), ("Apache", 1), ("Spark", 1), ("dataset", 1), ("is", 1), ("managed", 1), ("as", 1), ("a", 1), ("resilient", 1), ("distributed", 1), ("dataset", 1)]`。
4. 对元组列表中每一个元素的计数值进行求和：返回一个包含所有单词及其总出现次数的元组列表，即`[("dataset", 2), ("Apache", 2), ("Spark", 2), ("resilient", 2), ("distributed", 2), ("has", 1), ("its", 1), ("architectural", 1), ("foundation", 1), ("in", 1), ("the", 1), ("Inside", 1), ("is", 1), ("managed", 1), ("as", 1), ("a", 1)]`。
5. 将单词与总出现次数的元组列表按照总出现次数降序排序：返回一个按照出现次数降序排列的单词列表，即`[("dataset", 2), ("Apache", 2), ("Spark", 2), ("resilient", 2), ("distributed", 2), ("has", 1), ("its", 1), ("architectural", 1), ("foundation", 1), ("in", 1), ("the", 1), ("Inside", 1), ("is", 1), ("managed", 1), ("as", 1), ("a", 1)]`。