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  • Language
    Java
  • License
    Apache License 2.0
  • Created about 6 years ago
  • Updated 7 months ago

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Repository Details

Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.

English| 简体中文

Alink

Alink是基于Flink的通用算法平台,由阿里巴巴计算平台PAI团队研发,欢迎大家加入Alink开源用户钉钉群进行交流。

Alink教程

开源算法列表

PyAlink 使用截图

快速开始

PyAlink 使用介绍

使用前准备:


包名和版本说明:

  • PyAlink 根据 Alink 所支持的 Flink 版本提供不同的 Python 包: 其中,pyalink 包对应为 Alink 所支持的最新 Flink 版本,当前为 1.13,而 pyalink-flink-*** 为旧版本的 Flink 版本,当前提供 pyalink-flink-1.12, pyalink-flink-1.11, pyalink-flink-1.10pyalink-flink-1.9
  • Python 包的版本号与 Alink 的版本号一致,例如1.6.1

####安装步骤:

  1. 确保使用环境中有Python3,版本限于 3.6,3.7 和 3.8。
  2. 确保使用环境中安装有 Java 8。
  3. 使用 pip 命令进行安装: pip install pyalinkpip install pyalink-flink-1.12pip install pyalink-flink-1.11pip install pyalink-flink-1.10 或者 pip install pyalink-flink-1.9

安装注意事项:

  1. pyalinkpyalink-flink-*** 不能同时安装,也不能与旧版本同时安装。 如果之前安装过 pyalink 或者 pyalink-flink-***,请使用pip uninstall pyalink 或者 pip uninstall pyalink-flink-*** 卸载之前的版本。
  2. 出现pip安装缓慢或不成功的情况,可以参考这篇文章修改pip源,或者直接使用下面的链接下载 whl 包,然后使用 pip 安装:
    • Flink 1.13:链接 (MD5: a10d57a19c53d206d324273f377a1b13)
    • Flink 1.12:链接 (MD5: 82b2395740fbd960895d16350266ab4d)
    • Flink 1.11:链接 (MD5: 5bf901c084b51ebfa13a62489fafc2f2)
    • Flink 1.10:链接 (MD5: e18c620a3a3423407973b8c3d23a02e0)
    • Flink 1.9: 链接 (MD5: 2feaed5f159bb8970400eb3f6eafc7e5)
  3. 如果有多个版本的 Python,可能需要使用特定版本的 pip,比如 pip3;如果使用 Anaconda,则需要在 Anaconda 命令行中进行安装。

开始使用:


可以通过 Jupyter Notebook 来开始使用 PyAlink,能获得更好的使用体验。

使用步骤:

  1. 在命令行中启动Jupyter:jupyter notebook,并新建 Python 3 的 Notebook 。
  2. 导入 pyalink 包:from pyalink.alink import *
  3. 使用方法创建本地运行环境: useLocalEnv(parallism, flinkHome=None, config=None)。 其中,参数 parallism 表示执行所使用的并行度;flinkHome 为 flink 的完整路径,一般情况不需要设置;config为Flink所接受的配置参数。运行后出现如下所示的输出,表示初始化运行环境成功:
JVM listening on ***
  1. 开始编写 PyAlink 代码,例如:
source = CsvSourceBatchOp()\
    .setSchemaStr("sepal_length double, sepal_width double, petal_length double, petal_width double, category string")\
    .setFilePath("https://alink-release.oss-cn-beijing.aliyuncs.com/data-files/iris.csv")
res = source.select(["sepal_length", "sepal_width"])
df = res.collectToDataframe()
print(df)

编写代码:


在 PyAlink 中,算法组件提供的接口基本与 Java API 一致,即通过默认构造方法创建一个算法组件,然后通过 setXXX 设置参数,通过 link/linkTo/linkFrom 与其他组件相连。 这里利用 Jupyter Notebook 的自动补全机制可以提供书写便利。

对于批式作业,可以通过批式组件的 print/collectToDataframe/collectToDataframes 等方法或者 BatchOperator.execute() 来触发执行;对于流式作业,则通过 StreamOperator.execute() 来启动作业。

更多用法:


Java 接口使用介绍


示例代码

String URL = "https://alink-release.oss-cn-beijing.aliyuncs.com/data-files/iris.csv";
String SCHEMA_STR = "sepal_length double, sepal_width double, petal_length double, petal_width double, category string";

BatchOperator data = new CsvSourceBatchOp()
        .setFilePath(URL)
        .setSchemaStr(SCHEMA_STR);

VectorAssembler va = new VectorAssembler()
        .setSelectedCols(new String[]{"sepal_length", "sepal_width", "petal_length", "petal_width"})
        .setOutputCol("features");

KMeans kMeans = new KMeans().setVectorCol("features").setK(3)
        .setPredictionCol("prediction_result")
        .setPredictionDetailCol("prediction_detail")
        .setReservedCols("category")
        .setMaxIter(100);

Pipeline pipeline = new Pipeline().add(va).add(kMeans);
pipeline.fit(data).transform(data).print();

Flink-1.13 的 Maven 依赖

<dependency>
    <groupId>com.alibaba.alink</groupId>
    <artifactId>alink_core_flink-1.13_2.11</artifactId>
    <version>1.6.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-scala_2.11</artifactId>
    <version>1.13.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-planner_2.11</artifactId>
    <version>1.13.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-clients_2.11</artifactId>
    <version>1.13.0</version>
</dependency>

Flink-1.12 的 Maven 依赖

<dependency>
    <groupId>com.alibaba.alink</groupId>
    <artifactId>alink_core_flink-1.12_2.11</artifactId>
    <version>1.6.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-scala_2.11</artifactId>
    <version>1.12.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-planner_2.11</artifactId>
    <version>1.12.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-clients_2.11</artifactId>
    <version>1.12.1</version>
</dependency>

Flink-1.11 的 Maven 依赖

<dependency>
    <groupId>com.alibaba.alink</groupId>
    <artifactId>alink_core_flink-1.11_2.11</artifactId>
    <version>1.6.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-scala_2.11</artifactId>
    <version>1.11.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-planner_2.11</artifactId>
    <version>1.11.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-clients_2.11</artifactId>
    <version>1.11.0</version>
</dependency>

Flink-1.10 的 Maven 依赖

<dependency>
    <groupId>com.alibaba.alink</groupId>
    <artifactId>alink_core_flink-1.10_2.11</artifactId>
    <version>1.6.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-scala_2.11</artifactId>
    <version>1.10.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-planner_2.11</artifactId>
    <version>1.10.0</version>
</dependency>

Flink-1.9 的 Maven 依赖

<dependency>
    <groupId>com.alibaba.alink</groupId>
    <artifactId>alink_core_flink-1.9_2.11</artifactId>
    <version>1.6.1</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-streaming-scala_2.11</artifactId>
    <version>1.9.0</version>
</dependency>
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-table-planner_2.11</artifactId>
    <version>1.9.0</version>
</dependency>

快速开始在集群上运行Alink算法


  1. 准备Flink集群
  wget https://archive.apache.org/dist/flink/flink-1.13.0/flink-1.13.0-bin-scala_2.11.tgz
  tar -xf flink-1.13.0-bin-scala_2.11.tgz && cd flink-1.13.0
  ./bin/start-cluster.sh
  1. 准备Alink算法包
  git clone https://github.com/alibaba/Alink.git
  # add <scope>provided</scope> in pom.xml of alink_examples.
  cd Alink && mvn -Dmaven.test.skip=true clean package shade:shade
  1. 运行Java示例
  ./bin/flink run -p 1 -c com.alibaba.alink.ALSExample [path_to_Alink]/examples/target/alink_examples-1.5-SNAPSHOT.jar
  # ./bin/flink run -p 1 -c com.alibaba.alink.GBDTExample [path_to_Alink]/examples/target/alink_examples-1.5-SNAPSHOT.jar
  # ./bin/flink run -p 1 -c com.alibaba.alink.KMeansExample [path_to_Alink]/examples/target/alink_examples-1.5-SNAPSHOT.jar

部署


集群部署

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A one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大语言模型提供更高质量、更丰富、更易”消化“的数据!
Python
1,292
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