2024-08-01 16:30:00 ~ 2024-08-02 16:30:00
In the One Billion Row Challenge, the task is to write a program capable of reading an 1-billion-line file (with around 13GB), process and aggregate temperature readings from various weather stations,…
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破解 IK 分词器的秘密:如何选择 ik_smart 和 ik_max_word 模式?
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首先应该明确的是JVM调优不是常规手段,JVM的存在本身就是为了减轻开发对于内存管理的负担,当出现性能问题的时候第一时间考虑的是代码逻辑与设计方案,以及是否达到依赖中间件的瓶颈,最后才是针对JVM进行优化。
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JavaScript是一种动态类型、弱类型语言,它在处理字符和字符串时表现出了独特的灵活性和复杂性。在本文中,我们将从探讨JavaScript中的一段通过隐式类型转换的看似疯狂但有效的代码片段到熟知Javascript中的隐式类型转换规则。
To get all three properties, create an SVG file with the icon(s) you want to use with each one wrapped in a 
文章主要讲述了阿里云ARMS团队与程序语言与编译器团队合作研发的面向OpenTelemetry的Golang应用无侵入插桩技术解决方案,旨在解决Golang应用监控的挑战。
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At Airbnb, Apache Flink was introduced in 2018 as a supplementary solution for stream processing. It ran alongside Apache Spark™ Streaming for several years before transitioning to become the primary stream processing platform. In this blog post, we will delve into the evolution of Flink architecture at Airbnb and compare our prior Hadoop Yarn platform with the current Kubernetes-based architecture. Additionally, we will discuss the efforts undertaken throughout the migration process and explore the challenges that arose during this journey. In the end we will summarize the impact, learnings along the way and future plans.
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Pinterest is a visual discovery platform where people can find ideas like recipes, home and style inspiration, and much more. The platform offers its partners shopping capabilities as well as a significant advertising opportunity with 500+ million monthly active users. Advertisers can purchase ads directly on Pinterest or through partnerships with advertising agencies. Due to our huge scale, advertisers get an opportunity to learn about their Pins and their interaction with Pinterest users from the analytical data. This gives advertisers an opportunity to make decisions which will allow their ads to perform better on our platform.
At Pinterest, real-time insights play a critical role in empowering our advertisers and team members to make data-driven decisions. These decisions impact campaign performance, our experiments’ performance, and our policies such as rules to catch spam. We have been using Druid to store and provide these real-time insights, but as our scale and requirements continue to change, we have been evaluating different storage options. In the end we decided to migrate this data to StarRocks.
In this blog post, we’ll discuss and share our experience of launching our Analytics app on StarRocks. In the past, we have published our thoughts on using Druid and the benefits we have gotten from it. This post highlights the need for a new system as our scale and requirements have changed over time.
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本文重点讲述淘天集团算法技术团队在淘宝App首页猜你喜欢场景召回侧的工作,即如何让首猜通过LLM的模型能力,增加具有发现性的召回商品。
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小红书作为一个集内容分享、社区互动与电商购物于一体的平台,其搜索功能已成为人们获取信息、做出消费决策的重要渠道。随着用户需求的多样化和广告物料的快速增长,小红书搜索广告召回系统面临着业务与技术上的多重挑战。
本文深入探讨了小红书在业务增长阶段的搜索广告召回实践与思考,通过召回水位分析与策略演进,介绍了如何通过构建数据循环、优化复杂召回模型等技术手段,在保证用户体验的同时实现广告的高效分发。
此外,大模型技术的应用,如复杂查询常识推理、大模型表征等,也为召回系统带来了新的突破。在大模型时代,搜索技术栈的变革将不可避免,小红书搜索广告召回协同算力引擎团队已经为未来做好了准备。
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本文首先简单介绍了一下RPC的概念、应用场景及常用的RPC框架,然后讲述了如何自己手动实现一个RPC框架的基本功能。
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