RDD创建操作

Spark算子系列文章

从集合创建RDD

parallelize

def parallelize[T](seq: Seq[T], numSlices: Int = defaultParallelism)(implicit arg0: ClassTag[T]): RDD[T]

从一个Seq集合创建RDD。

参数1：Seq集合，必须。

参数2：分区数，默认为该Application分配到的资源的CPU核数

scala> var rdd = sc.parallelize(1 to 10)rdd: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[2] at parallelize at :21 scala> rdd.collectres3: Array[Int] = Array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10) scala> rdd.partitions.sizeres4: Int = 15 //设置RDD为3个分区scala> var rdd2 = sc.parallelize(1 to 10,3)rdd2: org.apache.spark.rdd.RDD[Int] = ParallelCollectionRDD[3] at parallelize at :21 scala> rdd2.collectres5: Array[Int] = Array(1, 2, 3, 4, 5, 6, 7, 8, 9, 10) scala> rdd2.partitions.sizeres6: Int = 3  makeRDD

def makeRDD[T](seq: Seq[T], numSlices: Int = defaultParallelism)(implicit arg0: ClassTag[T]): RDD[T]

这种用法和parallelize完全相同

def makeRDD[T](seq: Seq[(T, Seq[String])])(implicit arg0: ClassTag[T]): RDD[T]

该用法可以指定每一个分区的preferredLocations。

scala> var collect = Seq((1 to 10,Seq("slave007.lxw1234.com","slave002.lxw1234.com")),(11 to 15,Seq("slave013.lxw1234.com","slave015.lxw1234.com")))collect: Seq[(scala.collection.immutable.Range.Inclusive, Seq[String])] = List((Range(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),List(slave007.lxw1234.com, slave002.lxw1234.com)), (Range(11, 12, 13, 14, 15),List(slave013.lxw1234.com, slave015.lxw1234.com))) scala> var rdd = sc.makeRDD(collect)rdd: org.apache.spark.rdd.RDD[scala.collection.immutable.Range.Inclusive] = ParallelCollectionRDD[6] at makeRDD at :23 scala> rdd.partitions.sizeres33: Int = 2 scala> rdd.preferredLocations(rdd.partitions(0))res34: Seq[String] = List(slave007.lxw1234.com, slave002.lxw1234.com) scala> rdd.preferredLocations(rdd.partitions(1))res35: Seq[String] = List(slave013.lxw1234.com, slave015.lxw1234.com)  

指定分区的优先位置，对后续的调度优化有帮助。

从外部存储创建RDD

textFile

//从hdfs文件创建.

//从hdfs文件创建scala> var rdd = sc.textFile("hdfs:///tmp/lxw1234/1.txt")rdd: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[26] at textFile at :21 scala> rdd.countres48: Long = 4 //从本地文件创建scala> var rdd = sc.textFile("file:///etc/hadoop/conf/core-site.xml")rdd: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[28] at textFile at :21 scala> rdd.countres49: Long = 97  

注意这里的本地文件路径需要在Driver和Executor端存在。

从其他HDFS文件格式创建

hadoopFile

sequenceFile

objectFile

newAPIHadoopFile

从Hadoop接口API创建

hadoopRDD

newAPIHadoopRDD

比如：从HBase创建RDD

scala> import org.apache.hadoop.hbase.{HBaseConfiguration, HTableDescriptor, TableName}import org.apache.hadoop.hbase.{HBaseConfiguration, HTableDescriptor, TableName} scala> import org.apache.hadoop.hbase.mapreduce.TableInputFormatimport org.apache.hadoop.hbase.mapreduce.TableInputFormat scala> import org.apache.hadoop.hbase.client.HBaseAdminimport org.apache.hadoop.hbase.client.HBaseAdmin scala> val conf = HBaseConfiguration.create()scala> conf.set(TableInputFormat.INPUT_TABLE,"lxw1234")scala> var hbaseRDD = sc.newAPIHadoopRDD(conf,classOf[org.apache.hadoop.hbase.mapreduce.TableInputFormat],classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],classOf[org.apache.hadoop.hbase.client.Result]) scala> hbaseRDD.countres52: Long = 1