MapReduce

Difference between fold and reduce revisted

由 こ雲淡風輕ζ 提交于 2019-12-22 11:45:15
问题 I've been reading a nice answer to Difference between reduce and foldLeft/fold in functional programming (particularly Scala and Scala APIs)? provided by samthebest and I am not sure if I understand all the details: According to the answer ( reduce vs foldLeft ): A big big difference (...) is that reduce should be given a commutative monoid, (...) This distinction is very important for Big Data / MPP / distributed computing, and the entire reason why reduce even exists. and Reduce is defined

Pig数据模型及Order，Limit关系操作

由 笑着哭i 提交于 2019-12-22 11:34:08
【推荐】2019 Java 开发者跳槽指南.pdf(吐血整理) >>> 上一篇博客主要讲解了Pig的安装和一个试手的例子，下面说一下Pig的数据模型。 Pig的数据模型基本分为2大类，基本类型，和复杂类型。基本类型只能包含一个简单的数值，复杂类型可以包含其他所有类型。 基本类型，和其他大多数主流语言提供的简单类型一样，Pig也提供int， long， float， double，chararray（Sring），bytearray（字节类型） Pig是用Java开发的，因此Java程序员应该能想象的到，上面的基本类型都是java.lang包中对应类型的实现的。 需要注意的是，Pig的基本类型中没有Boolean值，但是在Pig的运行期却是有Boolean值的，因为关系Filter需要一个Boolean关系为true时数据才能流过去。这点上需要注意。 复杂类型包括Map， Tuple和Bag Map相当于Java的Map<String, Object>类型的。Key必须是一个chararray，而值可以是任何基本和复杂类型。表示为[key#value] Tuple可以理解为Java中的List，其实如果懂得Python，它更像Python中的Tuple[元组]，表示为：（1, “abc”， 1.5）等 Bag的数据类型按我的理解为Java的Set<Tuple>，它内部的数据是无序的

Exception while executing hadoop job remotely

由 拥有回忆 提交于 2019-12-22 11:12:23
问题 I am trying to execute a Hadoop job on a remote hadoop cluster. Below is my code. Configuration conf = new Configuration(); conf.set("fs.default.name", "hdfs://server:9000/"); conf.set("hadoop.job.ugi", "username"); Job job = new Job(conf, "Percentil Ranking"); job.setJarByClass(PercentileDriver.class); job.setMapperClass(PercentileMapper.class); job.setReducerClass(PercentileReducer.class); job.setMapOutputKeyClass(TestKey.class); job.setMapOutputValueClass(TestData.class); job

Where to see the mapreduce code generated from hadoop pig statements

由 自古美人都是妖i 提交于 2019-12-22 09:30:10
问题 We all know that the hadoop pig statements are converted into java mapreduce code. I want to know there is any way i can see the mapreduce code generated from pig statements ? 回答1: We all know that hadoop pig statements are converted into java mapreduce code This is not the case. Hadoop Pig statements are not translated into Java MapReduce code. A better way of thinking about it is Pig code is "interpreted" in an Pig interpreter that runs in Java MapReduce. Think about it this way: Python and

Is it possible to execute Hive queries parallelly by writing seperate mapreduce program?

由 六眼飞鱼酱① 提交于 2019-12-22 09:11:20
问题 I have asked some of the questions on increasing the performance of Hive queries. Some of the answers were pertaining to number of mappers and reducers. I tried with multiple mappers and reducers but I didn't see any difference in the execution. Don't know why, may be I did not do it in the right way or I missed something else. I would like to know is it possible to execute Hive queries in parallell? What exactly I mean is, normally the queries get executed in a queue. For instance: query1

Writing to HBase in MapReduce using MultipleOutputs

由 限于喜欢 提交于 2019-12-22 09:01:05
问题 I currently have a MapReduce job that uses MultipleOutputs to send data to several HDFS locations. After that completes, I am using HBase client calls (outside of MR) to add some of the same elements to a few HBase tables. It would be nice to add the HBase outputs as just additional MultipleOutputs, using TableOutputFormat. In that way, I would distribute my HBase processing. Problem is, I cannot get this to work. Has anyone ever used TableOutputFormat in MultipleOutputs...? With multiple

Record Reader and Record Boundaries

由 会有一股神秘感。 提交于 2019-12-22 08:21:31
问题 Suppose I have one input file and there are three blocks created in HDFS for this file. Assuming I have three data nodes and each data node is storing one block. If I have 3 input splits, 3 mappers will be running in parallel to process the data local to the respective data nodes. Each mapper gets input in terms of key value pairs using Input Format and Record Reader. This scenario with TextInputFormat where the record is complete line of text from file. Question here is what happens if there

Hadoop ChainMapper, ChainReducer [duplicate]

由 混江龙づ霸主 提交于 2019-12-22 08:16:14
问题 This question already has answers here : Hadoop mapreduce : Driver for chaining mappers within a MapReduce job (4 answers) Closed 5 months ago . I'm relatively new to Hadoop and trying to figure out how to programmatically chain jobs (multiple mappers, reducers) with ChainMapper, ChainReducer. I've found a few partial examples, but not a single complete and working one. My current test code is public class ChainJobs extends Configured implements Tool { public static class Map extends

Processing JSON using java Mapreduce

由 邮差的信 提交于 2019-12-22 07:16:08
问题 I am new to hadoop mapreduce I have input text file where data has been stored as follow. Here are only a few tuples (data.txt) {"author":"Sharīf Qāsim","book":"al- Rabīʻ al-manshūd"} {"author":"Nāṣir Nimrī","book":"Adīb ʻAbbāsī"} {"author":"Muẓaffar ʻAbd al-Majīd Kammūnah","book":"Asmāʼ Allāh al-ḥusná al-wāridah fī muḥkam kitābih"} {"author":"Ḥasan Muṣṭafá Aḥmad","book":"al- Jabhah al-sharqīyah wa-maʻārikuhā fī ḥarb Ramaḍān"} {"author":"Rafīqah Salīm

Under MongoDB java driver Mapreduce command scope; add functions to Scope

由 邮差的信 提交于 2019-12-22 06:47:48
问题 Is their a way to Execute a MongoDB map reduce job through the java driver in which you create a scope DBObject that contains functions. I can execute my map reduce configuration in javascript where the passed in scope contains utility functions, but I can't figure out how to do this with the java driver. I setup the scope using mapReduceCommand's c.addExtraOption("scope",new BasicDBObject().append('average',function(){ return false;})); However I can't get the mappers/reducers to recognize
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