Big data is a collection of large data sets that cannot be processed w的简体中文翻译

Big data is a collection of large d

Big data is a collection of large data sets that cannot be processed with traditional computing techniques. It is not a single technology or tool, but involves many areas of business and technology.Currently, the three major mainstream distributed computing systems are :Hadoop, Spark and Strom:Hadoop is one of the current big data management standards used in many commercial applications. You can easily integrate structured, semi-structured, and even unstructured data sets.Spark USES memory computing. Starting from multi-iteration batch processing, it allows the data to be loaded into memory for repeated queries. In addition, it integrates various computing paradigms such as data warehouse, stream processing and graph computing. Spark is built on HDFS and works well with Hadoop. Its RDD is a big feature.Storm is used for distributed real-time computing systems that handle high-speed, large data streams. Add reliable real-time data processing capabilities to HadoopHadoop is Apache's open source framework, written in Java, that allows the processing of large datasets of computers distributed in clusters, using a simple programming model. The Hadoop framework application project provides a distributed storage and computing environment across computer clusters. Hadoop is designed to scale from a single server to thousands of machines, each of which can provide local computing and storage.
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大数据是不能用传统的计算技术来处理大型数据集的集合。它不是一个单一的技术或工具,但涉及商业和技术的许多领域。<br>目前,三大主流的分布式计算系统:Hadoop的,Spark和斯特罗姆:<br>Hadoop是在许多商业应用中使用当前的大数据管理的标准之一。您可以轻松地将结构化,半结构化,甚至非结构化数据集。<br>火花使用内存计算。从多迭代批处理开始,它允许数据被加载到内存中以便重复查询。此外,它集成了各种计算范例,例如数据仓库,流处理和图表计算。火花是建立在HDFS和用Hadoop效果很好。它RDD是一大特色。<br>风暴用于分布式实时计算系统的是手柄的高速,大数据流。添加可靠的实时数据处理能力的Hadoop<br>Hadoop是Apache的开源框架,用Java编写的,它允许分布式集群计算机的大型数据集的处理,使用简单的编程模型。Hadoop框架的应用项目提供了跨计算机集群的分布式存储和计算环境。Hadoop是从一个单一的服务器到上千台机器,其中的每一个可以提供当地的计算和存储设计成比例。
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结果 (简体中文) 2:[复制]
复制成功!
Big data is a collection of large data sets that cannot be processed with traditional computing techniques. It is not a single technology or tool, but involves many areas of business and technology.<br>Currently, the three major mainstream distributed computing systems are :Hadoop, Spark and Strom:<br>Hadoop is one of the current big data management standards used in many commercial applications. You can easily integrate structured, semi-structured, and even unstructured data sets.<br>Spark USES memory computing. Starting from multi-iteration batch processing, it allows the data to be loaded into memory for repeated queries. In addition, it integrates various computing paradigms such as data warehouse, stream processing and graph computing. Spark is built on HDFS and works well with Hadoop. Its RDD is a big feature.<br>Storm is used for distributed real-time computing systems that handle high-speed, large data streams. Add reliable real-time data processing capabilities to Hadoop<br>Hadoop is Apache's open source framework, written in Java, that allows the processing of large datasets of computers distributed in clusters, using a simple programming model. The Hadoop framework application project provides a distributed storage and computing environment across computer clusters. Hadoop is designed to scale from a single server to thousands of machines, each of which can provide local computing and storage.
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结果 (简体中文) 3:[复制]
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大数据是用传统计算技术无法处理的大数据集的集合。它不是单一的技术或工具,而是涉及许多业务和技术领域。<br>目前,主流的三大分布式计算系统是:Hadoop、Spark和Strom:<br>Hadoop是当前许多商业应用中使用的大数据管理标准之一。您可以轻松集成结构化、半结构化甚至非结构化数据集。<br>Spark使用内存计算。从多迭代批处理开始,它允许将数据加载到内存中进行重复查询。此外,它还集成了数据仓库、流处理和图形计算等多种计算模式。Spark是在HDFS上构建的,与Hadoop配合得很好。它的RDD是一个很大的特性。<br>Storm用于处理高速、大数据流的分布式实时计算系统。向Hadoop添加可靠的实时数据处理功能<br>Hadoop是Apache的开源框架,用Java编写,它允许使用一个简单的编程模型处理集群中分布的大型计算机数据集。Hadoop框架应用程序项目提供了一个跨计算机集群的分布式存储和计算环境。Hadoop被设计成从一台服务器扩展到数千台机器,每台机器都可以提供本地计算和存储。
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