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Apache-2.0

Bigflow

Bigflow 是什么?

Baidu Bigflow (以下简称 Bigflow)是百度的一套计算框架, 它致力于提供一套简单易用的接口来描述用户的计算任务,并使同一套代码可以运行在不同的执行引擎之上。

它的设计中有许多思想借鉴自 Google FlumeJava以及 Google Cloud Dataflow,另有部分接口设计借鉴自 Apache Spark

用户基本可以不去关心 Bigflow 的计算真正运行在哪里,可以像写一个单机的程序一样写出自己的逻辑, Bigflow 会将这些计算分发到相应的执行引擎之上执行。

Bigflow 的目标是: 使分布式程序写起来更简单,测起来更方便,跑起来更高效,维护起来更容易,迁移起来成本更小。

目前 Bigflow 在百度公司内部对接了公司内部的批量计算引擎 DCE(与社区 Tez 比较类似),迭代引擎 Spark,以及公司内部的流式计算引擎 Gemini。

在开源版本中,目前仅开放了Bigflow on Spark。

为什么要使用 Bigflow?

  • 高性能  Bigflow 的接口设计使得 Bigflow 可以感知更多的用户需求的细节属性,并且 Bigflow 会根据计算的属性进行作业的优化;另其执行层使用 C++ 实现,用户的一些代码逻辑会被翻译为 C++ 执行,有较大的性能提升。 在公司内部的实际业务测试来看,其性能远高于用户手写的作业。根据一些从现有业务改写过来的作业平均来看,其性能都比原用户代码提升了 100%+。开源版本的 benchmark 正在准备中。

  • 简单易用  Bigflow 的接口表面看起来很像 Spark,但实际实用之后会发现 Bigflow 使用一些独特的设计使得 Bigflow 的代码更像是单机程序,例如,屏蔽了 partitioner 的概念,支持嵌套的分布式数据集等,使得其接口更加易于理解,并且拥有更强的代码可复用性。 特别的,在许多需要优化的场景中,因为 Bigflow 可以进行自动的性能以及内存占用优化,所以用户可以避免许多因 OOM 或性能不足而必须进行的优化工作,降低用户的使用成本。

  • 在这里,Python 是一等公民  我们目前原生支持的语言是 Python。 使用 PySpark 时,有不少用户都困扰于 PySpark 的低效,或困扰于其不支持某些 CPython 库,或困扰于一些仅功能仅仅在 Scala 和 Java 中可用,在 PySpark 中暂时处于不可用状态。 而在 Bigflow 中,Python 是一等公民(毕竟当前我们仅仅支持 Python),以上问题在 Bigflow 中都不是问题,性能、功能、易用性都对 Python 用户比较友好。

在线试用

在线试用网页(passwd:bigflow) 包含了一些简单的例子介绍Bigflow的概念和API用法,同时也可以在线编写Python代码尝试Bigflow的功能,可智能提示。

注:该页面仅提供试用功能,并没有做安全防护,相关机器每隔一段时间会被清空一次,请不要做代码存储等操作。

Bigflow详细文档

Bigflow 主页

快速入门

编程指南

API 参考

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论文

http://jcst.ict.ac.cn/EN/10.1007/s11390-020-9702-3

联系我们

需要加入Bigflow微信技术讨论群的,请加微信号:iacmol 或 himddheart,然后备注一下:加入Bigflow技术讨论群

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简介

Baidu Bigflow是一个允许编写分布式计算程序的接口,它提供了许多简单、灵活、功能强大的api 展开 收起
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