『 Spark 』1. spark 简介

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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 :

  • Spark SQL for SQL and structured data processing, extends to DataFrames and DataSets
  • MLlib for machine learning
  • GraphX for graph processing
  • Spark Streaming for stream data processing

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 :

  • generalize MapReduce to support new apps within same engine

    • 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.
  • speed up iteration computing over hadoop.

    • use memory + disk instead of disk as data storage medium

    • design a new programming modal, RDD, which make the data processing more graceful.
      [RDD transformation, action, distributed jobs, stages and tasks]



为何选用 spark

  • designed, implemented and used as libs, instead of specialized systems;
    • much more useful and maintainable


  • from history, it is designed and improved upon hadoop and storm, it has perfect genes;
  • documents, community, products and trends;
  • 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;
  • it provides ad-hoc exploring, which boost your data exploring and pre-processing and help you build your data ETL, processing job;


Intro to Apache Spark

introducing spark

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