[Spark][Python]DataFrame中取出有限个记录的例子

的 继续

In [4]: peopleDF.select("age")
Out[4]: DataFrame[age: bigint]

In [5]: myDF=people.select("age")
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-5-b5b723b62a49> in <module>()
----> 1 myDF=people.select("age")

NameError: name 'people' is not defined

In [6]: myDF=peopleDF.select("age")

In [7]: myDF.take(3)
17/10/05 05:13:02 INFO storage.MemoryStore: Block broadcast_5 stored as values in memory (estimated size 230.1 KB, free 871.7 KB)
17/10/05 05:13:02 INFO storage.MemoryStore: Block broadcast_5_piece0 stored as bytes in memory (estimated size 21.4 KB, free 893.1 KB)
17/10/05 05:13:02 INFO storage.BlockManagerInfo: Added broadcast_5_piece0 in memory on localhost:55073 (size: 21.4 KB, free: 208.7 MB)
17/10/05 05:13:02 INFO spark.SparkContext: Created broadcast 5 from take at <ipython-input-7-745486715568>:1
17/10/05 05:13:02 INFO storage.MemoryStore: Block broadcast_6 stored as values in memory (estimated size 251.1 KB, free 1144.2 KB)
17/10/05 05:13:02 INFO storage.MemoryStore: Block broadcast_6_piece0 stored as bytes in memory (estimated size 21.6 KB, free 1165.8 KB)
17/10/05 05:13:02 INFO storage.BlockManagerInfo: Added broadcast_6_piece0 in memory on localhost:55073 (size: 21.6 KB, free: 208.7 MB)
17/10/05 05:13:02 INFO spark.SparkContext: Created broadcast 6 from take at <ipython-input-7-745486715568>:1
17/10/05 05:13:03 INFO mapred.FileInputFormat: Total input paths to process : 1
17/10/05 05:13:03 INFO spark.SparkContext: Starting job: take at <ipython-input-7-745486715568>:1
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Got job 2 (take at <ipython-input-7-745486715568>:1) with 1 output partitions
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Final stage: ResultStage 2 (take at <ipython-input-7-745486715568>:1)
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Parents of final stage: List()
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Missing parents: List()
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Submitting ResultStage 2 (MapPartitionsRDD[14] at take at <ipython-input-7-745486715568>:1), which has no missing parents
17/10/05 05:13:03 INFO storage.MemoryStore: Block broadcast_7 stored as values in memory (estimated size 4.3 KB, free 1170.2 KB)
17/10/05 05:13:03 INFO storage.MemoryStore: Block broadcast_7_piece0 stored as bytes in memory (estimated size 2.5 KB, free 1172.6 KB)
17/10/05 05:13:03 INFO storage.BlockManagerInfo: Added broadcast_7_piece0 in memory on localhost:55073 (size: 2.5 KB, free: 208.7 MB)
17/10/05 05:13:03 INFO spark.SparkContext: Created broadcast 7 from broadcast at DAGScheduler.scala:1006
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Submitting 1 missing tasks from ResultStage 2 (MapPartitionsRDD[14] at take at <ipython-input-7-745486715568>:1)
17/10/05 05:13:03 INFO scheduler.TaskSchedulerImpl: Adding task set 2.0 with 1 tasks
17/10/05 05:13:03 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 2.0 (TID 2, localhost, partition 0,PROCESS_LOCAL, 2149 bytes)
17/10/05 05:13:03 INFO executor.Executor: Running task 0.0 in stage 2.0 (TID 2)
17/10/05 05:13:03 INFO rdd.HadoopRDD: Input split: hdfs://localhost:8020/user/training/people.json:0+179
17/10/05 05:13:03 INFO codegen.GenerateUnsafeProjection: Code generated in 113.719806 ms
17/10/05 05:13:03 INFO executor.Executor: Finished task 0.0 in stage 2.0 (TID 2). 2235 bytes result sent to driver
17/10/05 05:13:03 INFO scheduler.DAGScheduler: ResultStage 2 (take at <ipython-input-7-745486715568>:1) finished in 0.493 s
17/10/05 05:13:03 INFO scheduler.TaskSetManager: Finished task 0.0 in stage 2.0 (TID 2) in 487 ms on localhost (1/1)
17/10/05 05:13:03 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 2.0, whose tasks have all completed, from pool
17/10/05 05:13:03 INFO scheduler.DAGScheduler: Job 2 finished: take at <ipython-input-7-745486715568>:1, took 0.737231 s
Out[7]: [Row(age=None), Row(age=30), Row(age=19)]

In [8]:

[Spark][Python]DataFrame select 操作例子的更多相关文章

  1. [Spark][Python]DataFrame select 操作例子II

    [Spark][Python]DataFrame中取出有限个记录的   继续 In [4]: peopleDF.select("age","name") In ...

  2. [Spark][Python]DataFrame where 操作例子

    [Spark][Python]DataFrame中取出有限个记录的例子 的 继续 [15]: myDF=peopleDF.where("age>21") In [16]: m ...

  3. [Spark][Python]RDD flatMap 操作例子

    RDD flatMap 操作例子: flatMap,对原RDD的每个元素(行)执行函数操作,然后把每行都“拍扁” [training@localhost ~]$ hdfs dfs -put cats. ...

  4. [Spark][Python][DataFrame][SQL]Spark对DataFrame直接执行SQL处理的例子

    [Spark][Python][DataFrame][SQL]Spark对DataFrame直接执行SQL处理的例子 $cat people.json {"name":" ...

  5. [Spark][Python][DataFrame][RDD]DataFrame中抽取RDD例子

    [Spark][Python][DataFrame][RDD]DataFrame中抽取RDD例子 sqlContext = HiveContext(sc) peopleDF = sqlContext. ...

  6. [Spark][Python][DataFrame][RDD]从DataFrame得到RDD的例子

    [Spark][Python][DataFrame][RDD]从DataFrame得到RDD的例子 $ hdfs dfs -cat people.json {"name":&quo ...

  7. [Spark][Python][DataFrame][Write]DataFrame写入的例子

    [Spark][Python][DataFrame][Write]DataFrame写入的例子 $ hdfs dfs -cat people.json {"name":" ...

  8. [Spark][Python]DataFrame的左右连接例子

    [Spark][Python]DataFrame的左右连接例子 $ hdfs dfs -cat people.json {"name":"Alice",&quo ...

  9. [Spark][Python]DataFrame中取出有限个记录的例子

    [Spark][Python]DataFrame中取出有限个记录的例子: sqlContext = HiveContext(sc) peopleDF = sqlContext.read.json(&q ...

随机推荐

  1. Django--数据库查询操作

    MySQL是几乎每一个项目都会使用的一个关系数据库,又因为它是开源免费的,所以很多企业都用它来作为自家后台的数据库. BAT这类大公司除外,它们的业务数据是以亿级别来讨论的,而MySQL的单表6000 ...

  2. 数组中的逆序对(Java实现)

    来源:剑指offer 逆序对定义:a[i]>a[j],其中i<j 思路:利用归并排序的思想,先求前面一半数组的逆序数,再求后面一半数组的逆序数,然后求前面一半数组比后面一半数组中大的数的个 ...

  3. python第九十天----jquery

    jQuery http://jquery.cuishifeng.cn/ 相当于js的模块,类库 DOM/BOM/JavaScript的类库 一.查找元素 jQuery 选择器 直接找到某个或者某个标签 ...

  4. tkinter学习系列(四)之Button 控件

    目录 目录 前言 (一)基本用法和可选属性 ==1.基本用法== ==2.可选属性== (二)属性的具体实现和案例 ==1.常用属性== ==案例一== ==2.按钮里的图片== ==案例二== == ...

  5. ELK-logstash-6.3.2部署

    Logstash 是一款强大的数据处理工具,它可以实现数据传输,格式处理,格式化输出,还有强大的插件功能,常用于日志处理. 1. logstash部署 [yun@mini04 software]$ p ...

  6. 一个CSS值转REM的Sublime Text插件

    CSSREM 一个CSS的px值转rem值的Sublime Text 3自动完成插件. 插件效果如下: 安装 下载本项目,比如:git clone https://github.com/flashli ...

  7. sql 查询重复行数据

    1.查找表中多余的重复记录,重复记录是根据单个字段(peopleId)来判断select * from peoplewhere peopleId in (select  peopleId  from  ...

  8. SpringMVC---applicationContext.xml

    <?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.sp ...

  9. Ceph的BlueStore总体介绍

    整体架构 bluestore的诞生是为了解决filestore自身维护一套journal并同时还需要基于系统文件系统的写放大问题,并且filestore本身没有对SSD进行优化,因此bluestore ...

  10. ActiveMQ安装配置及使用

    ActiveMQ介绍 ActiveMQ 是Apache出品,最流行的,能力强劲的开源消息总线.ActiveMQ 是一个完全支持JMS1.1和J2EE 1.4规范的 JMS Provider实现,尽管J ...