Examples of using Graphx in English and their translations into Chinese
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Political
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Ecclesiastic
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Now we can use GraphX algorithms in all three languages.
Let's look at the details of each of the sample GraphX programs.
现在我们来仔细看看每一个GraphX程序例子。GraphX allows users to view the same data as graphs and as collections.
GraphX让用户可以查看与图形和集合同样的数据。In this article, we will focus on Spark GraphX for analyzing the graph data.
在该文中，我们将聚焦于用SparkGraphX来分析图数据。GraphX provides two implementations of PageRank: Static and Dynamic.
GraphX提供了两种Pageank的实现方法：静态的和动态的。Spark: Spark comes with a graph computation library called GraphX to make things simple.
Spark：Spark带有一个名为GraphX的图形计算库，使事情变得简单。GraphX: A powerful graph database engine useful outside of streaming applications.
GraphX：强大的图形数据库引擎，可用于流式应用程序之外。Let's look at some of the Spark GraphX API like triplets, indegrees, and outdegrees.
GraphX has a static and dynamic version of the PageRank implementation.
GraphX附带了PageRank的静态和动态实现方法作PageRank对象上的方法。As we learned in this article, Spark GraphX is a very good choice for graph data processing requirements.
这篇文章表明，SparkGraphX是满足图数据处理需求的很好的选择。GraphX also includes a visual preview function for all controls as well as rich usability documentation and user support.
GraphX还包括对所有控件的可视化预览功能以及丰富的易用性文档及用户支持。It has built-in modules for machine learning, SQL, streaming analytics(Spark Streaming),and graph processing(GraphX).
它内置可用于机器学习、SQL、流分析(SparkStreaming)和图形处理(GraphX)的模块。Furthermore, GraphX includes an increasing collection of algorithms to simplify the graphs analysis tasks.
此外，GraphX包含越来越多的图算法和构建器，以简化图形分析任务。This article describes atest application about how to use Spark GraphX for fraud detection using PageRank algorithm on metadata about phone communication.
这里有一篇文章描述了一个如何用SparkGraphX进行欺诈分析的测试应用，它将PageRank算法应用在电话通信的元数据上。Furthermore, GraphX includes an increasing collection of algorithms to simplify the graphs analysis tasks.
此外，GraphX还包括越来越多的图形算法和构建器，以简化图形分析任务。The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming,and machine learning and graphX.
该课程涵盖Sparkshell，用于交互式数据分析，Spark内部，SparkAPI，SparkSQL，Spark流，机器学习和graphX。In our code examples on Spark GraphX, we will use few different data sets for running Spark GraphX programs.
在我们的代码例子中，我们将用到四种不同的数据集来运行SparkGraphX程序。These libraries currently include SparkSQL, Spark Streaming,MLlib(for machine learning), and GraphX, each of which is further detailed in this article.
目前这些库包括SparkSQL、SparkStreaming、MLlib（用于机器学习）以及GraphX，我们会在稍后针对每一个库进行进一步描述。In addition, GraphX includes a growing collection of graph algorithms and builders to simplify graph analytics tasks.
此外，GraphX包含越来越多的图算法和构建器，以简化图形分析任务。GraphX supports analysis of and computation over graphs of data, and supports a version of graph processing's Pregel API.
GraphX：这个模块主要支持数据图的分析和计算，并支持图形处理的PregelAPI版本。In addition, GraphX includes a growing collection of graph algorithms and builders to simplify graph analytics tasks.
此外，GraphX还包括了越来越多的图形算法和构造者，以简化图形分析任务。GraphX is a library for manipulating graphs(e.g., a social network's friend graph) and performing graph-parallel computations.
GraphXGraphX是一个操作图(如社交网络的好友图)和执行基于图的并行计算的库。To support graph computation, GraphX exposes a set of fundamental operators(such as subgraph, joinVertices, and aggregateMessages) and an optimized variant of the Pregel API.
为了支持图计算，GraphX暴露了一个基础操作符集合（如subgraph，joinVertices和aggregateMessages）和一个经过优化的PregelAPI变体。GraphX is an advanced graph visualization software, it is an open-source project and is a part of the Apache Spark engine.
GraphX是一种高级的图形可视化软件，它是一个开源项目，还是ApacheSpark引擎的一部分。Spark GraphX has both: the flexibility of multiple algorithms, and the speed to transform and join the data in a number of different ways.
SparkGraphX结合了二者的优势：多个算法的灵活性，以及以各种不同方式转换和合并数据的速度。Spark GraphX comes with a selection of distributed algorithms for processing graph structures including an implementation of Google's PageRank.
SparkGraphX提供了一系列用于处理图形结构的分布式算法，包括Google的PageRank的实现。
