Weyl Gu

@siwei

siwei.io/about

Joined on Sep 15, 2021

  • Rrf: https://app.sli.do/event/pNBdBi95c8ujLz9u9fdVeJ/live/questions How much do we have cost to study graph basics? (Cost means not only money.) wey: To me, I started from NebulaGraph(https://docs.nebula-graph.io/) and you could start from GNN as well, i.e. Stanford CS224W https://www.youtube.com/watch?v=JAB_plj2rbA, too, my expirence on this was not to dive into long course, but to start from creating something with it(learning by doing, i.e. redo following the SNS with Graph post https://www.siwei.io/en/nebulagraph-sns/ ), and find the answers you come across and learn with purposes(with the help of google,chatgpt,community,docs). How do you collect all your data and manage your database? (about the movie, graphs) wey: great question, I collected from two sources in this project: OMDB and MovieLens, with some ETL, I shared how I created the graph with dbt(opensource data transform project) on another blog post:
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  • 未来我们会定期公布 NebulaGraph 社区的新贡献者,我们最近三个月的新贡献者(15)位如下,我们已经、正在为他们办法贡献者证书,感谢、祝贺你们🎉! NGBATIS CorvusYe Nebula-Node wujjpp
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  • Nebula Graph 生态中有哪些 Spark 项目? 本文为大家介绍 Spark-connector(包括 PySpark), Nebula Algorithm 和 Nebula Exchange。 最近我试着搭建了方便大家一键试玩的 Nebula Graph 中的 Spark 相关的项目,今天就把它们整理成文分享给大家。而且,我趟出来了 PySpark 下的 Nebula Spark Connector 的使用方式,后边也会一并贡献到文档里。 Nebula Graph 的三个 Spark 子项目 我曾经围绕 Nebula Graph 的所有数据导入方法画过一个草图,其中已经包含了 Spark Connector,Nebula Exchange 的简单介绍。在这篇文章中我将它们和另外的 Nebula Algorithm 进行稍微深入的探讨。 注:(这篇文档)[https://docs.nebula-graph.com.cn/3.1.0/20.appendix/write-tools/]也很清楚为我们列举了不同导入工具的选择。 TL;DR
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  • [TOC] Nebula Graph Native Index explained, why did I see index not found? When should I use Nebula Index and full-text index? The term Index in Nebula Graph is quite similar to the same term in relational databases, but they are not exactly the same. I noticed that some Nebula Graph users are often confused when getting started with Nebula Graph. Typically, people want to know what exactly Nebula Graph Index is, when should they use it, and how it impacts the performance of Nebula Graph. Today I'm going to walk you through the Index concept in Nebula Graph and hopefully, this article will answer these questions. Let's get started!
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  • A common question many Nebula Graph community users have asked is how to apply our graph database to Spark-based analytics. People want to use our powerful graph processing capabilities in conjunction with Spark, which is one of the most popular engines for data analytics. In this article, I will try to walk you through four different ways that you can make Nebula Graph and Apache Spark work together. The first three approaches will use Nebula Graph’s three libraries: Spark Connector, Nebula Exchange, and Nebula Algorithm, whereas the fourth way will leverage PySpark, an interface for Spark in Python. I have introduced quite a few data importing methods for Nebula Graph in this video, including three methods that import data to Spark. In this article, I’d like to dive deeper into these Spark-related projects, hoping it will provide more help if you want to connect Nebula Graph with Spark. TL;DR Nebula Spark Connector is a Spark library to enable Spark applications to read from and write to Nebula Graph in the form of dataframes. Nebula Exchange, built on top of Nebula Spark Connector, is a Spark library and application to migrate different data sources like(MySQL, Neo4j, PostgreSQL, Clickhouse, Hive, etc.) to Nebula Graph. Besides writing directly to Nebula Graph, it can also optionally generate SST files to be ingested into Nebula Graph to offload the storage computation from Nebula Graph cluster to the Spark cluster. Nebula Algorithm, built on top of Nebula Spark Connector and GraphX, is a Spark library to run graph algorithms(PageRank, LPA, etc) on top of graph data from Nebula Graph. If you want to make Spark and Nebula Graph work together using Python, PySpark is the go-to solution, which I will cover in the last section.
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  • url: https://www.siwei.io/en/resolve-wordle/ --- title: "How I cracked Chinese Wordle using knowledge graph" date: 2022-02-28T19:18:59+08:00 draft: false lightgallery: true tags: ["Nebula Graph", "Knowledge Graph", "wordle"]
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  • index not found?找不到索引?为什么我要创建 Nebula Graph 索引?什么时候要用到 Nebula Graph 原生索引,一文把这些搞清楚。 Nebula Graph 的索引其实和传统的关系型数据库中的索引很像,但是又有一些容易让人疑惑的区别。刚开始了解 Nebula 的同学会疑惑于: 不清楚 Nebula Graph 图数据库中的索引到的是什么概念 我应该什么时候使用 Nebula Graph 索引 Nebula Graph 索引怎么影响到写入性能 这篇文章里,我们就把这些问题回答好。
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  • 如何利用图数据库从0-1构建一个特定领域问答助手?本文手把手带你构建一个简易版的篮球领域智能问答机器人。 前言 「问答机器人」在我们日常生活中并不少见到 :像是一些电商客服、智能问诊、技术支持等人工输入与沟通界面的场景下,机器人“智能”问答系统一定程度上可以在无需人力、不需要耗费终端用户心智去做知识库、商品搜索、科室选择等等的情况下实时给出问题答案。 问答机器人系统背后的技术有多重可能: 基于检索,全文搜索接近的问题 基于机器学习阅读理解 基于知识图谱(Knowledge-Based Question Answering system: KBQA)
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  • 如何构建一个具有股权分析的图谱与线上系统呢?本文里,我将利用图数据库从零到一带你构建一个简易版的股权穿透图谱系统。 我们知道无论是监管部门、企业还是个人,都有需求去针对一个企业、法人做一些背景调查,这些调查可以是法律诉讼、公开持股、企业任职等等多种多样的信息。这些背景信息可以辅助我们做商业上的重要决策,规避风险:比如根据公司的股权关系,了解是否存在利益冲突比如是否选择与一家公司进行商业往来。 在满足这样的关系分析需求的时候,我们往往面临一些挑战,比如: 如何将这些数据的关联关系体现在系统之中?使得它们可以被挖掘、利用 多种异构数据、数据源之间的关系可能随着业务的发展引申出更多的变化,在结构数据库中,这意味着 Schema 变更 分析系统需要尽可能实时获取需要的查询结果,这通常涉及到多跳关系查询 领域专家能否快速灵活、可视化获取分享信息
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