我想更准确地了解pyspark中数据帧的方法缓存的使用
I want to know more precisely about the use of the method cache for dataframe in pyspark
当我运行 df.cache()时，它将返回一个数据帧.因此，如果我执行 df2 = df.cache()，哪个数据帧在缓存中?是 df ， df2 还是两者?
When I run df.cache() it returns a dataframe. Therefore, if I do df2 = df.cache(), which dataframe is in cache ? Is it df, df2, or both ?
I found the source code DataFrame.cache
def cache(self): """Persists the :class:`DataFrame` with the default storage level (`MEMORY_AND_DISK`). .. note:: The default storage level has changed to `MEMORY_AND_DISK` to match Scala in 2.0. """ self.is_cached = True self._jdf.cache() return self 因此，答案是:两者
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