rdd | 易学教程

How to JOIN 3 RDD's using Spark Scala

阅读更多关于 How to JOIN 3 RDD's using Spark Scala

问题 I want to join 3 tables using spark rdd . I achieved my objective using spark sql but when I tried to join it using Rdd I am not getting the desired results. Below is my query using spark SQL and the output : scala> actorDF.as("df1").join(movieCastDF.as("df2"),$"df1.act_id"===$"df2.act_id").join(movieDF.as("df3"),$"df2.mov_id"===$"df3.mov_id"). filter(col("df3.mov_title")==="Annie Hall").select($"df1.act_fname",$"df1.act_lname",$"df2.role").show(false) +---------+---------+-----------+ |act

Convert lines of JSON in RDD to dataframe in Apache Spark

阅读更多关于 Convert lines of JSON in RDD to dataframe in Apache Spark

问题 I have some 17,000 files in S3 that look like this: {"hour": "00", "month": "07", "second": "00", "year": "1970", "timezone": "-00:00", "day": "12", "minute": "00"} {"hour": "00", "month": "07", "second": "01", "year": "1970", "timezone": "-00:00", "day": "12", "minute": "00"} {"hour": "00", "month": "07", "second": "02", "year": "1970", "timezone": "-00:00", "day": "12", "minute": "00"} {"hour": "00", "month": "07", "second": "03", "year": "1970", "timezone": "-00:00", "day": "12", "minute":

pyspark program for nested loop

阅读更多关于 pyspark program for nested loop

问题 I am new to PySpark and I am trying to understand how can we write multiple nested for loop in PySpark, rough high level example below. Any help will be appreciated. for ( i=0;i<10;i++) for ( j=0;j<10;j++) for ( k=0;k<10;k++) { print "i"."j"."k" } 回答1: In non distributed setting for-loops are rewritten using foreach combinator, but due to Spark nature map and flatMap are a better choice: from __future__ import print_function a_loop = lambda x: ((x, y) for y in xrange(10)) print_me = lambda (

Formatting data for Spark ML

阅读更多关于 Formatting data for Spark ML

问题 I'm new to spark and Spark ML. I'm generated some data with the function KMeansDataGenerator.generateKMeansRDD but I fail when formatting those so that it can then be used by an ML algorithm (here it's K-Means). The error is Exception in thread "main" java.lang.IllegalArgumentException: Data type ArrayType(DoubleType,false) is not supported. It happens when using VectorAssembler. val generatedData = KMeansDataGenerator.generateKMeansRDD(sc, numPoints = 1000, k = 5, d = 3, r = 5, numPartitions

Cannot deserialize RDD with different number of items in pair

阅读更多关于 Cannot deserialize RDD with different number of items in pair

问题 I have two RDD's which have key-value pairs. I want to join them by key (and according to the key, get cartesian product of all values), which I assume can be done with zip() function of pyspark. However, when I apply this, elemPairs = elems1.zip(elems2).reduceByKey(add) It gives me the error: Cannot deserialize RDD with different number of items in pair: (40, 10) And here are the 2 RDD's which I try to zip: elems1 => [((0, 0), ('A', 0, 90)), ((0, 1), ('A', 0, 90)), ((0, 2), ('A', 0, 90)), (

BroadCast Variable publish in Spark Program

阅读更多关于 BroadCast Variable publish in Spark Program

问题 In the spark - java program I need to read a config file and populate a HashMap , which I need to publish as broadcast variable so that it will be available across all the datanodes . I need to get the value of this broadcast variable in the CustomInputFormat class which is going to run in the datanodes . How can i specify in my CustomInputFormat class to get value from the specific broadcast variable since the broadcast variable is declared in my driver program ? I am adding some code to

How to groupby and aggregate multiple fields using RDD?

阅读更多关于 How to groupby and aggregate multiple fields using RDD?

问题 I am new to Apache Spark as well as Scala, currently learning this framework and programming language for big data. I have a sample file I am trying to find out for a given field total number of another field and its count and list of values from another field. I tried on my own and seems that i am not writing in better approach in spark rdd (as starting). Please find the below sample data (Customerid: Int, Orderid: Int, Amount: Float) : 44,8602,37.19 35,5368,65.89 2,3391,40.64 47,6694,14.98

SparkStreaming窗口操作经典案例

阅读更多关于 SparkStreaming窗口操作经典案例

1.背景描述在社交网络（微博），电子商务（京东）、搜索引擎（百度）、股票交易中人们关心的内容之一是我所关注的内容中，大家正在关注什么在实际企业中非常有价值例如：我们关注过去30分钟大家都在热搜什么？并且每5分钟更新一次。要求列出来搜索前三名的话题内容 2.原理图如图所示，每当窗口滑过DStream时，落在窗口内的源RDD被组合并被执行操作以产生windowed DStream的RDD。在上面的例子中，操作应用于最近3个时间单位的数据，并以2个时间单位滑动。这表明任何窗口操作都需要指定两个参数。  窗口长度（windowlength） - 窗口的时间长度（上图的示例中为：15）。  滑动间隔（slidinginterval） - 两次相邻的窗口操作的间隔（即每次滑动的时间长度）（上图示例中为：10）。这两个参数必须是源DStream的批间隔的倍数（上图示例中为：5）。 3.代码问题： * 下述代码每隔20秒回重新计算之前60秒内的所有数据，如果窗口滑动时间间隔太短，那么需要重新计算的数据就比较大，非常耗时 * 怎么理解呢？窗口滑动时间间隔短的话，与窗口长度的交集每次都必须重新计算，浪费资源，避免交集太大的话就应该设置滑动间隔长一点 * //第一个Seconds是窗口大小（3个RDD一共需要的时间）,第二个Seconds是窗口间隔时间 * searchPair

How to create RDD from within Task?

阅读更多关于 How to create RDD from within Task?

问题 Normally when creating an RDD from a List you can just use the SparkContext.parallelize method, but you can not use the spark context from within a Task as it's not serializeable. I have a need to create an RDD from a list of Strings from within a task. Is there a way to do this? I've tried creating a new SparkContext in the task, but it gives me an error about not supporting multiple spark contexts in the same JVM and that I need to set spark.driver.allowMultipleContexts = true . According

save each element of rdd in text file hdfs

阅读更多关于 save each element of rdd in text file hdfs

问题 I am using spark application. In each element of rdd contains good amount of data. I want to save each element of rdd into multiple hdfs files respectively. I tried rdd.saveAsTextFile("foo.txt") But I will create a single file for whole rdd . rdd size is 10. I want 10 files in hdfs . How can I achieve this?? 回答1: If I understand your question, you can create a custom output format like this class RDDMultipleTextOutputFormat extends MultipleTextOutputFormat[Any, Any] { override def