Flink 1.7 文档翻译活动期待大家的参与 | ApacheCN

news/2024/7/3 9:02:15 标签: scala, 大数据, java

参与方式:https://github.com/apachecn/f...

整体进度:https://github.com/apachecn/f...

项目仓库:https://github.com/apachecn/f...


贡献指南

请您勇敢地去翻译和改进翻译。虽然我们追求卓越,但我们并不要求您做到十全十美,因此请不要担心因为翻译上犯错——在大部分情况下,我们的服务器已经记录所有的翻译,因此您不必担心会因为您的失误遭到无法挽回的破坏。(改编自维基百科)

负责人:zyBourn:379991171

章节列表

  • Apache Flink Documentation
  • Dataflow Programming Model
  • Distributed Runtime Environment
  • DataStream API Tutorial
  • Local Setup Tutorial
  • Running Flink on Windows
  • Examples
  • Batch Examples
  • Project Template for Java
  • Project Template for Scala
  • Configuring Dependencies, Connectors, Libraries
  • Basic API Concepts
  • Scala API Extensions
  • Java Lambda Expressions
  • Flink DataStream API Programming Guide
  • Event Time
  • Generating Timestamps / Watermarks
  • Pre-defined Timestamp Extractors / Watermark Emitters
  • State & Fault Tolerance
  • Working with State
  • The Broadcast State Pattern
  • Checkpointing
  • Queryable State Beta
  • State Backends
  • State Schema Evolution
  • Custom Serialization for Managed State
  • Operators
  • Windows
  • Joining
  • Process Function (Low-level Operations)
  • Asynchronous I/O for External Data Access
  • Streaming Connectors
  • Fault Tolerance Guarantees of Data Sources and Sinks
  • Apache Kafka Connector
  • Apache Cassandra Connector
  • Amazon AWS Kinesis Streams Connector
  • Elasticsearch Connector
  • HDFS Connector
  • Streaming File Sink
  • RabbitMQ Connector
  • Apache NiFi Connector
  • Twitter Connector
  • Side Outputs
  • Python Programming Guide (Streaming) Beta
  • Testing
  • Experimental Features
  • Flink DataSet API Programming Guide
  • DataSet Transformations
  • Fault Tolerance
  • Iterations
  • Zipping Elements in a DataSet
  • Connectors
  • Python Programming Guide Beta
  • Hadoop Compatibility Beta
  • Local Execution
  • Cluster Execution
  • Table API & SQL
  • Concepts & Common API
  • Streaming Concepts
  • Dynamic Tables
  • Time Attributes
  • Joins in Continuous Queries
  • Temporal Tables
  • Detecting Patterns in Tables Beta
  • Query Configuration
  • Connect to External Systems
  • Table API
  • SQL
  • Built-In Functions
  • User-defined Sources & Sinks
  • User-defined Functions
  • SQL Client Beta
  • Data Types & Serialization
  • Register a custom serializer for your Flink program
  • Execution Configuration
  • Program Packaging and Distributed Execution
  • Parallel Execution
  • Execution Plans
  • Restart Strategies
  • FlinkCEP - Complex event processing for Flink
  • Storm Compatibility Beta
  • Gelly: Flink Graph API
  • Graph API
  • Iterative Graph Processing
  • Library Methods
  • Graph Algorithms
  • Graph Generators
  • Bipartite Graph
  • FlinkML - Machine Learning for Flink
  • Quickstart Guide
  • Alternating Least Squares
  • How to Contribute
  • Cross Validation
  • Distance Metrics
  • k-Nearest Neighbors Join
  • MinMax Scaler
  • Multiple Linear Regression
  • Looking under the hood of pipelines
  • Polynomial Features
  • Stochastic Outlier Selection
  • Standard Scaler
  • SVM using CoCoA
  • Best Practices
  • API Migration Guides
  • Standalone Cluster
  • YARN Setup
  • Mesos Setup
  • Docker Setup
  • Kubernetes Setup
  • Amazon Web Services (AWS)
  • Google Compute Engine Setup
  • MapR Setup
  • Hadoop Integration
  • JobManager High Availability (HA)
  • Checkpoints
  • Savepoints
  • State Backends
  • Tuning Checkpoints and Large State
  • Configuration
  • Production Readiness Checklist
  • Command-Line Interface
  • Scala REPL
  • Kerberos Authentication Setup and Configuration
  • SSL Setup
  • File Systems
  • Upgrading Applications and Flink Versions
  • Metrics
  • How to use logging
  • History Server
  • Monitoring Checkpointing
  • Monitoring Back Pressure
  • Monitoring REST API
  • Debugging Windows & Event Time
  • Debugging Classloading
  • Application Profiling
  • Importing Flink into an IDE
  • Building Flink from Source
  • Component Stack
  • Data Streaming Fault Tolerance
  • Jobs and Scheduling
  • Task Lifecycle
  • File Systems

流程

一、认领

首先查看整体进度,确认没有人认领了你想认领的章节。

然后回复 ISSUE,注明“章节 + QQ 号”(一定要留 QQ)。

二、翻译

可以合理利用翻译引擎(例如谷歌),但一定要把它变得可读!

如果遇到格式问题,请随手把它改正。

三、提交

  • fork Github 项目
  • 将译文放在docs文件夹下
  • push
  • pull request

请见 Github 入门指南。


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