Mapping Single Rows to Multiple Pairs目的: 把如下的这种数据, Input Data 00001 sku010:sku933:sku02200002 sku912:sku33100003 sku888:sku022:sku010:sku59400004 sku411 转换为这样:一个Key值,带的这几个键值,分别罗列: (00001,sk010)(00001,sku933)(00001,sku022) ...(00002,sku912)(00002,sku3…

周末的任务是更新Learning Spark系列第三篇,以为自己写不完了,但为了改正拖延症,还是得完成给自己定的任务啊 = =.这三章主要讲Spark的运行过程(本地+集群),性能调优以及Spark SQL相关的知识,如果对Spark不熟的同学可以先看看之前总结的两篇文章: [原]Learning Spark (Python版) 学习笔记(一)----RDD 基本概念与命令 [原]Learning Spark (Python版) 学习笔记(二)----键值对.数据读取与保存.共享特性 #####…

[Spark][Python][DataFrame][Write]DataFrame写入的例子 $ hdfs dfs -cat people.json {"name":"Alice","pcode":"94304"}{"name":"Brayden","age":30,"pcode":"94304"}{"name&qu…

http://dev.mysql.com/doc/refman/5.7/en/prepare.html Statement names are not case sensitive. preparable_stmt is either a string literal or a user variable that contains the text of the SQL statement. The text must represent a single statement, not mul…

摘要:pandas是一个强大的Python数据分析工具包,pandas的两个主要数据结构Series(一维)和DataFrame(二维)处理了金融,统计,社会中的绝大多数典型用例科学,以及许多工程领域.在Spark中,python程序可以方便修改,省去java和scala等的打包环节,如果需要导出文件,可以将数据转为pandas再保存到csv,excel等. 1.Pandas是什么? pandas是一个强大的Python数据分析工具包,是一个提供快速,灵活和表达性数据结构的python包,旨在使…

[Spark][Python][RDD][DataFrame]从 RDD 构造 DataFrame 例子 from pyspark.sql.types import * schema = StructType( [ StructField("age",IntegerType(),True), StructField("name",StringType(),True), StructField("pcode",StringType(),True)…

[Spark][Python][DataFrame][RDD]DataFrame中抽取RDD例子 sqlContext = HiveContext(sc) peopleDF = sqlContext.read.json("people.json") peopleRDD = peopleDF.map(lambda row: (row.pcode,row.name)) peopleRDD.take(5) Out[5]: [(u'94304', u'Alice'),(u'94304', u'…

[Spark][Python][DataFrame][RDD]从DataFrame得到RDD的例子 $ hdfs dfs -cat people.json {"name":"Alice","pcode":"94304"}{"name":"Brayden","age":30,"pcode":"94304"}{"name&…

[Spark][Python][DataFrame][SQL]Spark对DataFrame直接执行SQL处理的例子 $cat people.json {"name":"Alice","pcode":"94304"}{"name":"Brayden","age":30,"pcode":"94304"}{"name&qu…

[Spark][Python]DataFrame的左右连接例子 $ hdfs dfs -cat people.json {"name":"Alice","pcode":"94304"}{"name":"Brayden","age":30,"pcode":"94304"}{"name":"Carla&…