MapReduce for complex aggregation.
针对复杂聚合的mapreduce。
MapReduce is inspired by these concepts.
MapReduce是受到这些概念的启发而产生的一个模型。
Next, request the MapReduce job for grep.
接下来，请求用于执行 grep的MapReduce作业。
The MapReduce programming mode was developed at Google.
MapReduce编程模式是在Google开发出来的。
Main function configures the MapReduce job and runs it.
main函数配置并运行MapReduce作业。
Check out this list of Mapreduce and Hadoop algorithms in academic papers.
检查学术文章中的Mapreduce和Hadoop算法的列表。
Processing in Elastic MapReduce is centered around the concept of a Job Flow.
ElasticMapReduce的处理是围绕着任务流这一概念为中心来开展的。
The primary way data is retrieved is through MapReduce-style code called views.
检索数据的主要方法是通过称为视图的mapreduce式代码。
The combination of cloud computing and MapReduce seems tailored for big data jobs.
云计算和MapReduce的组合看起来非常适合处理BigData作业。
The third parameter is the name of the object that holds the results of MapReduce.
第三个参数是持有MapReduce结果的对象的名称。
MapReduce is about the simplest way you can break down a big job into little pieces.
MapReduce是把大任务分解为小任务的最简单的方法。
So, what are the functional elements that inspired the MapReduce programming paradigm?
是什么功能性元素激发了MapReduce编程范例的创立？
MapReduce programs are designed to compute large volumes of data in a parallel fashion.
MapReduce程序用于以并行方式计算大量数据。
A simple MapReduce job that does a word frequency count, written in our mrjob Python framework.
我们在mrjobPython框架中编写了这个简单的MapReduce作业，它执行单词频率统计。
Next in the MapReduce life cycle: All of the intermediate results get boiled down and summarized.
在MapReduce生命周期中，下一步是浓缩和汇总所有中间结果。
The scenario is one where a startup company wishes to offer a MapReduce service to their clients.
这个情景是关于一个新起步的公司，他们希望为他们的客户提供MapReduce服务。
The record-breaking MapReduce approach, he said, is useful in physics, cryptography and data mining.
他还介绍说，破记录的MapReduce方法在物理学，密码学和数据挖掘领域也是很有用的。
Now you have set up the Hadoop Cluster on the cloud, and it's ready to run the MapReduce applications.
现在，已经在云中设置了Hadoop集群，该运行MapReduce应用程序了。
In a cloud environment, the MapReduce structure increases the efficiency of throughput for large data sets.
在云环境中，MapReduce结构提高了大型数据集的吞吐效率。
As a result of this paper, many open source implementations of MapReduce emerged between 2004 to the present.
这篇文章导致的结果是，从2004年到现在出现了许多开放源码的MapReduce实现。
There is no shortage of cloud-based MapReduce options available both as open source and commercial offerings.
基于云的MapReduce 系统既有开放源码的，也有商用产品。
Here are a few simple examples of interesting programs that can be easily expressed as MapReduce computations.
下面是一些mapreduce应用中有趣的例子。
When working with MapReduce, the map function's job is to pick some value to work off of, along with some key.
当使用MapReduce 进行处理时，map函数的任务是选择一些要处理的值，以及一些键。
Google introduced the idea of MapReduce as a programming model for processing or generating large sets of data.
Google引用MapReduce的概念作为处理或生成大型数据集的编程模型。
The advantage of MapReduce is that it allows for the distributed processing of the map and reduction operations.
MapReduce的优点是它允许对映射和缩减操作进行分布式处理。
MapReduce doesn't depend on a traditional structured database, where information is categorized as it's collected.
MapReduce不需要传统结构的数据库，信息在收集的时候就已经分类了。
The MapReduce reliability was severely tested once during a maintenance operation on one cluster with 1,800 servers.
MapReduce的可靠性曾经在一个由1800台服务器组成的集群进行维护时经受住了严格考验。
Is there any additional work being done to simplify the management of a cluster, the HDFS, MapReduce processes, etc.?
那么管理这样一个集群、HDFS以及MapReduce的处理还有什么额外的工作需要做吗？
Map, written by a user of the MapReduce library, takes an input pair and produces a set of intermediate key/value pairs.
MapReduce库的用户指定一个Map函数，通过这个函数接收key/value对，然后产生一系列的中间key/value对。
Map, written by a user of the MapReduce library, takes an input pair and produces a set of intermediate key/value pairs.
MapReduce库的用户指定一个Map函数，通过这个函数接收key/value对，然后产生一系列的中间key/value对。
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