Spark中持久化和序列化学习

一、cache和persisit的对比

-rw-r--r--@ 1 hadoop staff 68M 5 17 07:04 access.log







cache/persitence是 lazy的,延迟加载
unpersitence是立即执行的

@DeveloperApi
class StorageLevel private(
    private var _useDisk: Boolean,
    private var _useMemory: Boolean,
    private var _useOffHeap: Boolean,
    private var _deserialized: Boolean,
    private var _replication: Int = 1)
  extends Externalizable {  }

  /**
 * Various [[org.apache.spark.storage.StorageLevel]] defined and utility functions for creating
 * new storage levels.
 */
object StorageLevel {
  val NONE = new StorageLevel(false, false, false, false)
  val DISK_ONLY = new StorageLevel(true, false, false, false)
  val DISK_ONLY_2 = new StorageLevel(true, false, false, false, 2)
  val MEMORY_ONLY = new StorageLevel(false, true, false, true)
  val MEMORY_ONLY_2 = new StorageLevel(false, true, false, true, 2)
  val MEMORY_ONLY_SER = new StorageLevel(false, true, false, false)
  val MEMORY_ONLY_SER_2 = new StorageLevel(false, true, false, false, 2)
  val MEMORY_AND_DISK = new StorageLevel(true, true, false, true)
  val MEMORY_AND_DISK_2 = new StorageLevel(true, true, false, true, 2)
  val MEMORY_AND_DISK_SER = new StorageLevel(true, true, false, false)
  val MEMORY_AND_DISK_SER_2 = new StorageLevel(true, true, false, false, 2)
  val OFF_HEAP = new StorageLevel(true, true, true, false, 1)

  /**
   * Persist this RDD with the default storage level (`MEMORY_ONLY`).
   */
  def persist(): this.type = persist(StorageLevel.MEMORY_ONLY)

  /**
   * Persist this RDD with the default storage level (`MEMORY_ONLY`).
   */
  def cache(): this.type = persist()

  /**
   * Mark the RDD as non-persistent, and remove all blocks for it from memory and disk.
   *
   * @param blocking Whether to block until all blocks are deleted.
   * @return This RDD.
   */
  def unpersist(blocking: Boolean = true): this.type = {
    logInfo("Removing RDD " + id + " from persistence list")
    sc.unpersistRDD(id, blocking)
    storageLevel = StorageLevel.NONE
    this
  }

  /** Get the RDD's current storage level, or StorageLevel.NONE if none is set. */
  def getStorageLevel: StorageLevel = storageLevel

二、序列化测试Java和kyro

序列化:
默认java序列化类User
使用kyro序列化没有未注册类User
使用kryo序列化并注册类User

---

---

默认java序列化类User

import scala.collection.mutable.ListBuffer
class User(id:Int,username:String,age:String) extends Serializable
val users = new ListBuffer[User]
for(i <- 1 to 1000000){
users.+=(new User(i,"name"+i,i.toString))
}
val usersRDD=sc.parallelize(users)
import org.apache.spark.storage.StorageLevel
usersRDD.persist(StorageLevel.MEMORY_ONLY_SER)
usersRDD.foreach(println(_))

使用kyro序列化没有未注册类User

import org.apache.spark.SparkConf
val sparkConf= new SparkConf()
sparkConf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")

import org.apache.spark.SparkContext

使用kryo序列化并注册类User

sparkConf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    sparkConf.registerKryoClasses(Array(classOf[User]))