在 英语 中使用 Streaming data 的示例及其翻译为 中文
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Coinbase created a streaming data insight pipeline in AWS, with real-time exchange analytics processed by an Amazon Kinesis managed big-data processing service.
That connectivity and streaming data also creates a sense of urgency to respond, but that response must be accurate to make IoT profitable.
连通性和流数据还带来了响应的紧迫感，但这种响应必须是准确的，才能使物联网有益。It integrates very well with Apache Storm and Spark for real-time streaming data analysis.
它与apachestorm和spark非常好地集成，用于实时流式数据分析。In the age of GDPR and other regulatory compliance laws, it's important to track data lineage, even for streaming data.
在遵从GDPR及其他法规合规性的时代，跟踪数据沿袭很重要，即使对于流数据也是如此。While Structured Streaming provides high-level improvements to Spark Streaming, it currently relies on the same microbatching scheme of handling streaming data.
尽管结构化流式传输为SparkStreaming提供了高级改进，但它目前依赖于处理流式数据的相同的微处理方案。You may also want to visit the InfoSphere Streams Web site for details on how IBM's platform supports streaming data.
您也可以访问InfoSphereStreams网站，获得IBM如何支持流数据的详细信息。Apache Kafka has become a standard messaging system for large-scale, streaming data.
ApacheKafka已经成为了用于大规模流式数据的标准消息系统。In addition to Map and Reduce operations, it supports SQL queries, streaming data, machine learning and graph data processing.
除了Map和Reduce操作之外，它还支持SQL查询，流数据，机器学习和图表数据处理。Our platforms for global data management extends from the edge to the enterprise, capturing and analysing streaming data and bringing it to rest.
我们的全球数据管理平台从边缘扩展到企业，捕获和分析流数据并使其成为静态数据。Narkhede: When Confluent was formed, the first two areas we looked into were stream processing and streaming data pipelines.
Narkhede:当Confluent初创时，我们研究的前两个领域是流处理和流数据管道。They were developed for batch or micro-batch data, which does not work well with high velocity/volume of streaming data from sensors, etc.
它们是针对批或微批数据而开发的，对于来自传感器等较高速度/较大数量的流数据不能很好地发挥作用。Level 4: Increased heterogeneity of enterprise systems requires cross-platform model deployment, with a growing need to incorporate models into streaming data applications.
第4级：企业系统的异构性增加需要跨平台模型部署，并且越来越需要将模型合并到流数据应用程序中。Our global data platform extends from the edge to the enterprise, capturing and analyzing streaming data and bringing it to rest.
我们的全球数据管理平台从边缘扩展到企业，捕获和分析流数据并使其成为静态数据。The rise of interest in Apache Spark has demonstrated just how important streaming data has become in the big data ecosystem.
ApacheSpark日益受到关注，表明了数据流在大数据生态系统中变得到底有多重要。Ultra efficient for streaming data, taking full advantage of carrier aggregation(CA) and massive multiple input/multiple output(MIMO).
异常高效处理数据流，充分利用载波聚合(CA)和大规模多路输入/多路输出(MIMO).Industry terminology for such fast-moving data tends to be either“streaming data,” or“complex event processing.”.
对于这种快速传输的数据，其行业术语就是“数据流”或“复杂事务处理”。Both HTTP queries and responses are perceived as isolated events but, in fact, they are actually streaming data.
虽然HTTP请求和响应被认为是两个孤立的事件，但实际上它们是数据流。All data- including smart cities' sensor-generated streaming data- are classified according to standardized models.
所有数据，包括智慧城市传感器生成的流数据，都按照标准化模型进行分类。Windowing in processing time affects the streaming data analytics and results in some errors in data processing.
处理时间的窗口会对流数据的分析产生影响，并会导致数据处理过程中出现某些错误。The evolution of data-centric platforms, including Hadoop services, streaming data services, and in-memory databases, also is gaining visibility.
而以数据为中心的发展平台，包括Hadoop服务、流媒体数据服务，和内存数据库，也是获得显著变化。
