【技术头条10/09/PM 11点闪读】Go语言入门教程(十)之函数|Redis Cluster 原…|redis简介以及集成环境塔建|Squeeze AWS Lam…|Connect the Mul…|

  1. Go语言入门教程(十)之函数

    Hello 各位小伙伴大家好,我是小栈君,假期一眨眼就过去了。不知道大家玩的是否开心呢? 上次我们讲到了关于Go语言的流程控制,小栈君也希望小伙伴跟着小栈君一步一个脚印的敲一下代码,相互进步。本期我们要分享的Go语言系列之函数。 一、什么是函数? 函数是指一段在一起的、可以做某一件事儿的程序。也叫做 …

  2. Redis Cluster 原理相关说明

    背景 之前写的 Redis Cluster部署、管理和测试 和 Redis 5.0 redis-cli –cluster help说明 已经比较详细的介绍了如何安装和维护Cluster。但关于Cluster各个节点的通信和原理没有说明,为了方便自己以后查阅,先做些记录。顺便对Redis 4.0和5 …

  3. redis简介以及集成环境塔建

    redis简介: 首先redis是一款高速的内存缓存数据库,他的数据是存储在内存上,而mysql的数据是存储在硬盘上面,可想而知在数据的读写方面redis比mysql快了一个量级, redis是非关系型数据库,他的数…

  4. Squeeze AWS Lambda For Everything It’s Worth!

    In a nutshell, the service allows users to run code without having to meddle with management technicalities, server shenanigans, or any of that update or upgrade nonsense … Using AWS Lambda to its full potential gives you a nice Edge, but make sure you’Re proactive in your approach … Take the time to understand what Lambda can and cannot do and test the limits of the computing and storage resources at your disposal.

  5. Connect the MuleSoft Database Connector to Heroku Postgres

    The MuleSoft Database Connector provides the ability to easily connect to any database as long as you have the JDBC driver … The Flow will listen for an HTTP request, make a call to Heroku Postgres, and return the Data in JSON format … Once you click OK, fill in the SQL Query Text field with a valid SQL query that returns Data back from your Heroku Postgres database.

  6. Recommendation System Using Spark, ML Akka, and Cassandra

    A recommendation system is an information filtering mechanism that attempts to predict the rating a user would give a particular product … The ALS algorithm should uncover the latent factors that explain the observed user to item ratings and tries to Find optimal factor weights to minimize the least squares between predicted and actual ratings … With collaborative filtering, The idea is to approximate the ratings Matrix by factorizing it as the product of two matrices:One that describes properties of each user (shown in Green), and One that describes properties of each movie (shown in Blue).

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