Spark列出所有缓存的RDD名称，并且不持久 [英] Spark list all cached RDD names and unpersist

问题描述

我是Apache Spark的新手，我创建了几个RDD和DataFrame，并对其进行了缓存，现在我想使用下面的命令来取消持久化其中一些

I am new to Apache Spark, I created several RDD's and DataFrames, cached them, now I want to unpersist some of them by using the command below

rddName.unpersist()

但是我不记得他们的名字了.我使用了sc.getPersistentRDDs，但是输出不包含名称.我还使用浏览器查看了缓存的rdds，但再次没有名称信息.我想念什么吗?

but I can't remember their names. I used sc.getPersistentRDDs but the output does not include the names. I also used the browser to view the cached rdds but again no name information. Am I missing something?

推荐答案

@Dikei的答案实际上是正确的，但我相信您正在寻找的是sc.getPersistentRDDs:

@Dikei's answer is actually correct but I believe what you are looking for is sc.getPersistentRDDs :

scala> val rdd1 = sc.makeRDD(1 to 100)
# rdd1: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[0] at makeRDD at <console>:27

scala> val rdd2 = sc.makeRDD(10 to 1000)
# rdd2: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[1] at makeRDD at <console>:27

scala> rdd2.cache.setName("rdd_2")
# res0: rdd2.type = rdd_2 ParallelCollectionRDD[1] at makeRDD at <console>:27

scala> sc.getPersistentRDDs
# res1: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(1 -> rdd_2 ParallelCollectionRDD[1] at makeRDD at <console>:27)

scala> rdd1.cache.setName("foo")
# res2: rdd1.type = foo ParallelCollectionRDD[0] at makeRDD at <console>:27

scala> sc.getPersistentRDDs
# res3: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(1 -> rdd_2 ParallelCollectionRDD[1] at makeRDD at <console>:27, 0 -> foo ParallelCollectionRDD[0] at makeRDD at <console>:27)

现在让我们添加另一个RDD并为其命名:

Now let's add another RDD and name it as well :

scala> rdd3.setName("bar")
# res4: rdd3.type = bar ParallelCollectionRDD[2] at makeRDD at <console>:27

scala> sc.getPersistentRDDs
# res5: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(1 -> rdd_2 ParallelCollectionRDD[1] at makeRDD at <console>:27, 0 -> foo ParallelCollectionRDD[0] at makeRDD at <console>:27)

我们注意到它实际上并没有持久存在.

We noticed that actually it isn't persisted.

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