Titlebook: Pro Spark Streaming; The Zen of Real-Time Zubair Nabi Book 2016 Zubair Nabi 2016 Spark.Spark Streaming.Spark Streaming Application.Spark St

GERD847

書目名稱Pro Spark Streaming影響因子(影響力)




書目名稱Pro Spark Streaming影響因子(影響力)學科排名




書目名稱Pro Spark Streaming網(wǎng)絡公開度




書目名稱Pro Spark Streaming網(wǎng)絡公開度學科排名




書目名稱Pro Spark Streaming被引頻次




書目名稱Pro Spark Streaming被引頻次學科排名




書目名稱Pro Spark Streaming年度引用




書目名稱Pro Spark Streaming年度引用學科排名




書目名稱Pro Spark Streaming讀者反饋




書目名稱Pro Spark Streaming讀者反饋學科排名

以煙熏消毒

Zubair NabiHighlights the differences between traditional stream processing and the Spark Streaming micro-batch model.Targets real-world applications from multiple industry verticals.Provides an introduction to

情感

Herpetologist

DStreams: Real-Time RDDs,ng will define the future of real-time analytics. There is also a growing need to analyze both data at rest and data in motion to drive applications, which makes systems like Spark—which can do both—all the more attractive and powerful. It’s a system for all Big Data seasons.

Neuropeptides

AIL

Real-Time ETL and Analytics Magic,solution such as Hive, but this is a marriage of convenience rather than a natural fit: data must be copied back and forth, not to mention the burden of maintaining two different APIs. A better solution is Spark SQL.

別名

Of Clouds, Lambdas, and Pythons,c), Databricks, and IBM (Bluemix). No book about Spark would be complete without a discussion of running it in the cloud. Other topics covered in this chapter include the Spark Python API, the lambda architecture, and graph processing.

思考

beta-carotene

limber

Real-Time Route 66: Linking External Data Sources,cation—can substantially affect performance. With this in mind, this chapter is dedicated to ingesting data from solutions such as Kafka, Flume, and MQTT. In the process, you also write your own connector for HTTP to learn the ropes of connecting to external data sources.