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Dropping the first and last row of an RDD with Spark

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问题 I'm reading in a text file using spark with sc.textFile(fileLocation) and need to be able to quickly drop the first and last row (they could be a header or trailer). I've found good ways of returning the first and last row, but no good one for removing them. Is this possible? 回答1: One way of doing this would be to zipWithIndex , and then filter out the records with indices 0 and count - 1 : // We're going to perform multiple actions on this RDD, // so it's usually better to cache it so we don

How to avoid using of collect in Spark RDD in Scala?

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问题 I have a List and has to create Map from this for further use, I am using RDD, but with use of collect(), job is failing in cluster. Any help is appreciated. Please help. Below is the sample code from List to rdd.collect. I have to use this Map data further but how to use without collect? This code creates a Map from RDD (List) Data. List Format->(asdfg/1234/wert,asdf) //List Data to create Map val listData = methodToGetListData(ListData).toList //Creating RDD from above List val rdd =

How to match an RDD[ParentClass] with RDD[Subclass] in apache spark?

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问题 I have to match an rdd with its types. trait Fruit case class Apple(price:Int) extends Fruit case class Mango(price:Int) extends Fruit Now a dstream of type DStream[Fruit] is coming. It is either Apple or Mango . How to perform operation based on the subclass? Something like the below (which doesn't work): dStream.foreachRDD{rdd:RDD[Fruit] => rdd match { case rdd: RDD[Apple] => //do something case rdd: RDD[Mango] => //do something case _ => println(rdd.count() + "<<<< not matched anything") }

spark how to remove last line in a csv file

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问题 I am new to spark I want to remove header and last line from a csv file Notes xyz "id","member_id" "60045257","63989975", "60981766","65023535", Total amount:4444228900 Total amount: 133826689 I want to remove line Notes xyz , Total amount:4444228900 and Total amount: 133826689 from the file .I have removed the first line from the file val dfRetail = sc.textFile("file:////home/cloudera/Projects/Project3/test/test_3.csv"); var header=dfRetail.first(); var final_data=dfRetail.filter(row => row!

spark how to remove last line in a csv file

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spark RDD算子详解3

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Actions算子本质上在Actions算子中通过SparkContext执行提交作业的runJob操作，触发了RDD DAG的执行。 1．无输出（1）foreach(f) 对RDD中的每个元素都应用f函数操作，不返回RDD和Array，而是返回Uint。图3-25表示foreach算子通过用户自定义函数对每个数据项进行操作。本例中自定义函数为println()，控制台打印所有数据项。 2．HDFS saveAsTextFile (path, compressionCodecClass=None) 函数将数据输出，存储到HDFS的指定目录。将RDD中的每个元素映射转变为(Null, x.toString)，然后再将其写入HDFS。图3-26中左侧的方框代表RDD分区，右侧方框代表HDFS的Block。通过函数将RDD的每个分区存储为HDFS中的一个Block。 3．Scala集合和数据类型（1）collect() collect将分布式的RDD返回为一个单机的scala Array数组。在这个数组上运用scala的函数式操作。图3-28中的左侧方框代表RDD分区，右侧方框代表单机内存中的数组。通过函数操作，将结果返回到Driver程序所在的节点，以数组形式存储。（2）collectAsMap() collectAsMap对(K, V

Spark RDD method “saveAsTextFile” throwing exception Even after deleting the output directory. org.apache.hadoop.mapred.FileAlreadyExistsException

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问题 I am calling this method on an RDD[String] with destination in the arguments. (Scala) Even after deleting the directory before starting, the process gives this error. I am running this process on EMR cluster with output location at aws S3. Below is the command used: spark-submit --deploy-mode cluster --class com.hotwire.hda.spark.prd.pricingengine.PRDPricingEngine --conf spark.yarn.submit.waitAppCompletion=true --num-executors 21 --executor-cores 4 --executor-memory 20g --driver-memory 8g -

Spark RDD method “saveAsTextFile” throwing exception Even after deleting the output directory. org.apache.hadoop.mapred.FileAlreadyExistsException

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Spark RDD method “saveAsTextFile” throwing exception Even after deleting the output directory. org.apache.hadoop.mapred.FileAlreadyExistsException

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spark训练模型

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训练模型一、前述经过之前的训练数据的构建可以得到所有特征值为1的模型文件，本文将继续构建训练数据特征并构建模型。二、详细流程将处理完成后的训练数据导出用做线下训练的源数据（可以用Spark_Sql对数据进行处理） insert overwrite local directory '/opt/data/traindata' row format delimited fields terminated by '\t' select * from dw_rcm_hitop_prepare2train_dm; 注：这里是将数据导出到本地，方便后面再本地模式跑数据，导出模型数据。这里是方便演示真正的生产环境是直接用脚本提交spark任务，从hdfs取数据结果仍然在hdfs，再用ETL工具将训练的模型结果文件输出到 web项目的文件目录下，用来做新的模型，web项目设置了定时更新模型文件，每天按时读取新模型文件三、代码详解 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64

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