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Titlebook: Big Data Analytics with Spark; A Practitioner‘s Gui Mohammed Guller Book 2015 Mohammed Guller 2015 Big Data.Spark.Hive.Avro.Kafka.databases

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31#
發(fā)表于 2025-3-26 22:22:01 | 只看該作者
32#
發(fā)表于 2025-3-27 02:52:30 | 只看該作者
https://doi.org/10.1007/978-94-009-1179-6Armbrust, Michael, Reynold S. Xin, Cheng Lian, Yin Huai, Davies Liu, Joseph K. Bradley, Xiangrui Meng, Tomer Kaftan, Michael J. Franklin, Ali Ghodsi, Matei Zaharia. .. ..
33#
發(fā)表于 2025-3-27 07:17:45 | 只看該作者
34#
發(fā)表于 2025-3-27 11:34:49 | 只看該作者
35#
發(fā)表于 2025-3-27 15:12:58 | 只看該作者
Writing a Spark Application,This chapter discusses how to write a data processing application in Scala using Spark. . covered the basics of Scala, which you need to know to get started.
36#
發(fā)表于 2025-3-27 20:38:48 | 只看該作者
Spark SQL,Ease of use is one of the reasons Spark became popular. It provides a simpler programming model than Hadoop MapReduce for processing big data. However, the number of people who are fluent in the languages supported by the Spark core API is a lot smaller than the number of people who know the venerable SQL.
37#
發(fā)表于 2025-3-28 00:20:09 | 只看該作者
Graph Processing with Spark,Data is generally stored and processed as a collection of records or rows. It is represented as a two-dimensional table with data divided into rows and columns. However, collections or tables are not the only way to represent data. Sometimes, a graph provides a better representation of data than a collection.
38#
發(fā)表于 2025-3-28 03:05:18 | 只看該作者
39#
發(fā)表于 2025-3-28 06:25:13 | 只看該作者
40#
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