MapReduce

HBase与MapReduce的集成

由 折月煮酒 提交于 2019-12-21 10:04:59
HBase当中的数据最终都是存储在HDFS上面的，HBase天生的支持MR的操作，我们可以通过MR直接处理HBase当中的数据，并且MR可以将处理后的结果直接存储到HBase当中去 一、读取myuser这张表当中的数据写入到HBase的另外一张表当中去 读取HBase当中一张表的数据，然后将数据写入到HBase当中的另外一张表当中去。注意：我们可以使用TableMapper与TableReducer来实现从HBase当中读取与写入数据 将myuser这张表当中f1列族的name和age字段写入到myuser2这张表的f1列族当中去 1、创建myuser2这张表 hbase(main):010:0> create 'myuser2','f1' 2、创建maven工程，导入jar包 <repositories> <repository> <id>cloudera</id> <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url> </repository> </repositories> <dependencies> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-client</artifactId>

CouchDB Views: How much processing is acceptable in map reduce?

由 痴心易碎 提交于 2019-12-21 09:37:04
问题 I've been toying around with Map Reduce with CouchDB. Some of the examples show some possibly heavy logic within the map reduce functions. In one particular case, they were performing for loops within map. Is map reduce run on every single possible document before it emits your selected documents? If so, I would think that means that running any kind of iterative processing within the map reduce functions would increase processing burden by an order of magnitude, at least. Basically it boils

CouchDB Views: How much processing is acceptable in map reduce?

由 南楼画角 提交于 2019-12-21 09:36:45
问题 I've been toying around with Map Reduce with CouchDB. Some of the examples show some possibly heavy logic within the map reduce functions. In one particular case, they were performing for loops within map. Is map reduce run on every single possible document before it emits your selected documents? If so, I would think that means that running any kind of iterative processing within the map reduce functions would increase processing burden by an order of magnitude, at least. Basically it boils

Hadoop: How can i merge reducer outputs to a single file? [duplicate]

由 喜你入骨 提交于 2019-12-21 07:03:03
问题 This question already has answers here : merge output files after reduce phase (10 answers) Closed 6 years ago . I know that "getmerge" command in shell can do this work. But what should I do if I want to merge these outputs after the job by HDFS API for java？ What i actually want is a single merged file on HDFS. The only thing i can think of is to start an additional job after that. thanks! 回答1: But what should I do if I want to merge these outputs after the job by HDFS API for java?

How can we automate incremental import in SQOOP?

由 早过忘川 提交于 2019-12-21 05:41:00
问题 How can we automate the incremental import in SQoop ? In incremental import, we need to give the --last-value to start the import from the last value onwards, but my job is to frequently import from RDBMS, I don't want to give last value manually, is there any way we can automate this process? 回答1: An alternate approach to @Durga Viswanath Gadiraju answer. In case you are importing the data to a hive table , you could query the last updated value from the hive table and pass the value to the

Error handling in hadoop map reduce

由 狂风中的少年 提交于 2019-12-21 05:34:10
问题 Based on the documentation, there are a few ways, how the error handling is performed in map reduce. Below are the few: a. Custom counters using enum - increment for every failed record. b. Log error and analyze later. Counters give the number of failed records. However to get the identifier of the failed record(may be its unique key), and details of the exception occurred, node on which the error occurred - we need to perform centralized log analysis and there are many nodes running.

Hadoop Streaming Job Failed (Not Successful) in Python

由 我的未来我决定 提交于 2019-12-21 05:03:13
问题 I'm trying to run a Map-Reduce job on Hadoop Streaming with Python scripts and getting the same errors as Hadoop Streaming Job failed error in python but those solutions didn't work for me. My scripts work fine when I run "cat sample.txt | ./p1mapper.py | sort | ./p1reducer.py" But when I run the following: ./bin/hadoop jar contrib/streaming/hadoop-0.20.2-streaming.jar \ -input "p1input/*" \ -output p1output \ -mapper "python p1mapper.py" \ -reducer "python p1reducer.py" \ -file /Users/Tish

How to use Cassandra's Map Reduce with or w/o Pig?

由 拥有回忆 提交于 2019-12-21 03:29:08
问题 Can someone explain how MapReduce works with Cassandra .6? I've read through the word count example, but I don't quite follow what's happening on the Cassandra end vs. the "client" end. https://svn.apache.org/repos/asf/cassandra/trunk/contrib/word_count/ For instance, let's say I'm using Python and Pycassa, how would I load in a new map reduce function, and then call it? Does my map reduce function have to be java that's installed on the cassandra server? If so, how do I call it from Pycassa?

Out of memory error in Mapreduce shuffle phase

由 亡梦爱人 提交于 2019-12-21 03:25:34
问题 I am getting strange errors while running a wordcount-like mapreduce program. I have a hadoop cluster with 20 slaves, each having 4 GB RAM. I configured my map tasks to have a heap of 300MB and my reduce task slots get 1GB. I have 2 map slots and 1 reduce slot per node. Everything goes well until the first round of map tasks finishes. Then there progress remains at 100%. I suppose then the copy phase is taking place. Each map task generates something like: Map output bytes 4,164,335,564 Map

MapReduce算法（将数据按照 /OutputData/城市名称/日期（YYYY-MM-dd）/类型（固定Gn）/imsi.txt ）

由 老子叫甜甜 提交于 2019-12-21 03:04:50
需求： 现有部分GN数据，数据为全省数据，解析GN数据，将数据按照 /OutputData/城市名称/日期（YYYY-MM-dd）/类型（固定Gn）/imsi.txt (有很多imsi)的结构，将相同城市，相同日期，相同imsi（国际移动用户标识），类型为Gn的数据汇总到一起，。 解析出新的IMSI, VULUME、CELLID、TAC、city、time 数据： 1|460002452699237|8655890276520178|8613786401241|21.176.70.136|29588|255|56042|221.177.173.83|221.177.173.64|221.177.173.35|221.177.173.35|2|cmnet|101|a788057f91cf3a89|1480752079784|1480752079788|18|26|0|33931|8.8.8.8|53|460|0|73|366|1|1|0|0|0|0|0|0|183.232.72.164|0|1|4|6|6|2260069379||||||||||||||| 数据说明：数据列的分隔符为“|”，截取出数据的第六个和第八个字段，两个字段使用“_”拼接，构成城市名称编号。 日期字段为第十七个数据。 Imsi数据为第二个数据 GnMapper package GN.demo01; import
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