Spark function to explain: cache

Use the MEMORY_ONLY storage level to cache the RDD, whose internal implementation calls the persist () function. Official document definition:
Persist this RDD with the default storage level (`MEMORY_ONLY`).

Function prototype

def cache() : this.type
 -----------------------------
scala> var data = sc.parallelize(List(1,2,3,4))
data: org.apache.spark.rdd.RDD[Int] =
　　ParallelCollectionRDD[44] at parallelize at <console>:12
 
scala> data.getStorageLevel
res65: org.apache.spark.storage.StorageLevel =
　　StorageLevel(false, false, false, false, 1)
 
scala> data.cache
res66: org.apache.spark.rdd.RDD[Int] =
　　ParallelCollectionRDD[44] at parallelize at <console>:12
 
scala> data.getStorageLevel
res67: org.apache.spark.storage.StorageLevel =
　　StorageLevel(false, true, false, true, 1)
 

Commentaires

  1. Tejuteju14 septembre 2018 à 06:46

    Really Good blog post.provided a helpful information.I hope that you will post more updates like this Big Data Hadoop Online Course Hyderabad

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