原文链接:『 Spark 』1. spark 简介
写在前面
本系列是综合了自己在学习spark过程中的理解记录 + 对参考文章中的一些理解 + 个人实践spark过程中的一些心得而来。写这样一个系列仅仅是为了梳理个人学习spark的笔记记录,并非为了做什么教程,所以一切以个人理解梳理为主,没有必要的细节就不会记录了。若想深入了解,最好阅读参考文章和官方文档。
其次,本系列是基于目前最新的 spark 1.6.0 系列开始的,spark 目前的更新速度很快,记录一下版本好还是必要的。
最后,如果各位觉得内容有误,欢迎留言备注,所有留言 24 小时内必定回复,非常感谢。
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1. 如何向别人介绍 spark
Apache Spark™ is a fast and general engine for large-scale data processing.
Apache Spark is a fast and general-purpose cluster computing system.
It provides high-level APIs in Java, Scala, Python and R
, and an optimized engine that supports general execution graphs.
It also supports a rich set of higher-level tools including :
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Spark SQL for SQL and structured data processing, extends to DataFrames and DataSets
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MLlib for machine learning
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GraphX for graph processing
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Spark Streaming for stream data processing
2. spark 诞生的一些背景
Spark started in 2009, open sourced 2010, unlike the various specialized systems[hadoop, storm], Spark’s goal was to :
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generalize MapReduce to support new apps within same engine
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it\’s perfectly compatible with hadoop, can run on Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, and S3.
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speed up iteration computing over hadoop.
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use memory + disk instead of disk as data storage medium
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design a new programming modal, RDD, which make the data processing more graceful [RDD transformation, action, distributed jobs, stages and tasks]
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3. 为何选用 spark
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designed, implemented and used as libs, instead of specialized systems;
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much more useful and maintainable
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from history, it is designed and improved upon hadoop and storm, it has perfect genes;
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documents, community, products and trends;
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it provides sql, dataframes, datasets, machine learning lib, graph computing lib and activitily growth 3-party lib, easy to use, cover lots of use cases in lots field;
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it provides ad-hoc exploring, which boost your data exploring and pre-processing and help you build your data ETL, processing job;
4. Next
下一篇,简单介绍 spark 里必须深刻理解的基本概念。
参考文章
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Intro to Apache Spark
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introducing spark
本系列文章链接
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『 Spark 』1. spark 简介
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『 Spark 』2. spark 基本概念解析
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『 Spark 』3. spark 编程模式
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『 Spark 』4. spark 之 RDD
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『 Spark 』5. 这些年,你不能错过的 spark 学习资源
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『 Spark 』6. 深入研究 spark 运行原理之 job, stage, task
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『 Spark 』7. 使用 Spark DataFrame 进行大数据分析