On the principles side, it does seem that map-reduce is enduring. 使用MongoDB进行分析的另一个选择是使用map-reduce 。 Another option for performing analytics with MongoDB is to use map-reduce . On the principles side, it does seem that map-reduce is enduring. 此外,它具有高度可扩展性,并且基于map-reduce ,让它非常适合于大数据的应用。 Plus, it's highly scalable and map-reduce based, which make it suitable for big data applications. 如果你还不太熟悉Hadoop,学习map-reduce 、Pig、Hive和Mahout将很有帮助。 If you're not already familiar with Hadoop- learning map-reduce , Pig and Hive and Mahout will be valuable.
此外,它具有高度可扩展性,并且基于map-reduce ,让它非常适合于大数据的应用。 Plus, it's highly scalable46 and based on map-reduce47 , making it suitable for big data applications. 比如说如果出现崩溃,map-reduce ApplicationMaster就会将状态保存起来并且可以快速恢复。 For example, the map-reduce Application Master will save state and allow quick recovery if it crashes. 在MongoDB中,我们可以在使用map-reduce 在数据上运行任意的聚合。 In MongoDB, you can run arbitrary aggregations over data using map-reduce . CouchDB:早期的NoSQL先驱,对于较大的数据集来说,并不是很好,而且依赖于map-reduce 来进行查询。 CouchDB: an early NoSQL pioneer it's not so great for larger datasets and relies on map-reduce for query. Map-Reduce 是Google开发的一种分布式编程API,并在ApacheHadoop项目中得到了实现。Map-Reduce is a distributed programming API pioneered by Google and implemented in the Apache Hadoop project. 此外,各种流的步骤被智能地转换成对应于hadoopcluster的map-reduce 调用。 In addition, the steps of the various flows are intelligently converted into map-reduce invocations against the hadoop cluster. ApacheMahout提供了在ApacheHadoop平台上(分布式使用map-reduce 模式)使用机器学习算法的实现。 Apache Mahout provides implementations of machine learning algorithms for use on the Apache Hadoop platform(distributed map-reduce ). 我们时常被过多的选择轰炸并习惯于应付像NoSQL、云、REST、Map-Reduce 等流行词。 We are constantly bombarded with choice and are used to dealing with buzzwords like NoSQL, the cloud, REST, Map-Reduce and so on. 接下来,我们在输出的‘lastDayOrders'集合上运行一个辅助map-reduce 工作,以计算每个产品对的出现次数:. Next, we run a second map-reduce job on the outputed‘lastDayOrders' collection to compute the number of occurrences of each item pair:. 它让我们使用数据接入技术、关系型数据库、非关系型数据库、map-reduce 框架以及基于云的服务变得简单。 It makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. 为了支持map-reduce 的shuffle阶段,NodeManager容许远程任务发出远程请求来读取磁盘上的本地数据。 To support the map-reduce shuffle phase, the NodeManager will allow remote tasks to issue remote requests to read local data on their disk. MongoDB有三种方式进行聚合计算:聚合管道,map-reduce 函数,单一目的聚…. MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function, and single purpose aggregation methods. 的文章“Map-Reduce forMachineLearningonMulticore”(见参考资料),但此后在发展中又并入了更多广泛的机器学习方法。 S paper"Map-Reduce for Machine Learning on Multicore" but has since evolved to cover much broader machine-learning approaches. 拥有构建和运营大规模数据处理基础架构(包括数据管道、Map-Reduce 及其他相关工具)的经验。 (Optional) Experience building and operating large-scale data processing infrastructure, including data pipelines, Map-Reduce and other related tools. 算法功能可以包括为了进行数据清理的数字信号处理、过程信号中的形状检测以及分布式计算的Map-reduce 模型。 Algorithm functions can include digital signal processing for data cleansing, shape detection in process signals, and map-reduce models for distributed computing. MongoDB提供了三种聚合的方式,分别是聚合管道,map-reduce 函数和单用途聚合方法。 MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function, and single purpose aggregation methods and commands. 其中使用到两个技术,GraphJet,推特的实时图处理库,和Scalding,推特的离线map-reduce 算法。 Two technologies pointed out to help with this are GraphJet, Twitters real-time graph processing library, and Scalding, Twitters offline map-reduce algorithm. 同样,早在2005年,Hadoop的另一个革命性产品诞生,这就是MapReduce,Map-Reduce 方法为Java应用程序的并行计算提供了框架。 Again, back in 2005, this was revolutionary- the Map-Reduce approach of Hadoop provided a framework for parallel computation of Java applications. 本文来演示如何在Oracle数据库上,通过使用ParallelPipelinedTable函数及并行操作,来实现Map-Reduce 程序。 This post shows how to implement Map-Reduce Programs within the Oracle database using Parallel Pipelined Table Functions and parallel operations. 的文章“Map-Reduce forMachineLearningonMulticore”(见参考资料),但此后在发展中又并入了更多广泛的机器学习方法。 S paper"Map-Reduce for Machine Learning on Multicore"(see Related topics) but has since evolved to cover much broader machine-learning approaches. 幸运的是我们已不再需要提供完整的事务支持,单独的系统也可以执行复杂的分析任务,比如像Hadoop这样的map-reduce 平台。 Fortunately, full transactional support typically is not required, and separate systems perform complex analysis tasks-for example, map-reduce platforms such as Hadoop. 每个应用一个ApplicationMaster(比如map-reduce 编程),可以请求资源、追踪进度、处理失败,并且可以保持计算状态。 One ApplicationMaster per application(such as map-reduce programming) which requests resources, tracks progress, handles failures, and can keep state about computations.
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时间: 0.0179
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