投稿時間:2022-10-17 01:17:15 RSSフィード2022-10-17 01:00 分まとめ(20件)

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AWS	AWS	Torc Robotics and the Massive Data Processing of Autonomous Trucking | AWS All Things Automotive	https://www.youtube.com/watch?v=oF6YH7mNIWE	Torc Robotics and the Massive Data Processing of Autonomous Trucking AWS All Things AutomotiveIn our latest episode exploring the Drivers of Transformation All Things Automotive welcomes Torc Robotics for a look at the technology behind their self driving trucks that is pioneering safety critical self driving innovation in the freight industry Guided by Stefano Marzani and Derek Johnson Head of Data Infrastructure Torc Robotics we go Under the Hood of Torc s platform to discuss the processing of massive amounts of data that comes from Torc s long haul fleet of Freightliner Cascadia trucks Become familiar with Torc s cloud architecture and the services that make simulations and deep learning possible on this vast amount of data AWS s Global Automotive Account Principal George Suriya takes you Around the Corner to discuss the latest trends and technologies among AWS customers specializing in autonomous vehicles Inspired by Torc s mission Check out the current technical openings to help drive their vision autonomoustrucks selfdriving aws VehicleSimulations	2022-10-16 15:00:35
python	Pythonタグが付けられた新着投稿 - Qiita	日経平均株価のチャート分析用グラフ作成	https://qiita.com/rexid/items/63d74b8e9d2bc9eeeb44	aderimportdataimportmat	2022-10-17 00:23:47
python	Pythonタグが付けられた新着投稿 - Qiita	TechFUL　難易度2「もじもじ文字」	https://qiita.com/My_me_admin/items/c6d5e3df444d57cde8e7	techful	2022-10-17 00:16:38
js	JavaScriptタグが付けられた新着投稿 - Qiita	【JS】map関数について理解する	https://qiita.com/pon-pn/items/5b8aac15235efd6a18c4	関数	2022-10-17 00:54:13
AWS	AWSタグが付けられた新着投稿 - Qiita	実務に向けたAWSのSAA対策①(基本的なサーバー構築)	https://qiita.com/Hashimoto-Noriaki/items/1ad8a1c96fb5bf142d39	sarchitectassociate	2022-10-17 00:31:16
Docker	dockerタグが付けられた新着投稿 - Qiita	固定文字列を返すAPIをDockerでデプロイする	https://qiita.com/kaikusakari/items/711c7d46a00c3ccff252	appservice	2022-10-17 00:17:40
海外TECH	MakeUseOf	How to Speed Up Slow PS4 Downloads	https://www.makeuseof.com/tag/slow-ps4-download-speed/	downloadsis	2022-10-16 15:31:14
海外TECH	MakeUseOf	How to Change Windows 11’s Boot Animation	https://www.makeuseof.com/windows-11-change-boot-animation/	animation	2022-10-16 15:15:14
海外TECH	DEV Community	In One Minute : V8 (JavaScript engine)	https://dev.to/rakeshkr2/in-one-minute-v8-javascript-engine-59b2	In One Minute V JavaScript engine V is a free and open source JavaScript engine developed by the Chromium Project for Google Chrome and Chromium web browsers The project s creator is Lars Bak The first version of the V engine was released at the same time as the first version of Chrome September V first generates an abstract syntax tree with its own parser Then Ignition generates bytecode from this syntax tree using the internal V bytecode format V can be used in a browser or integrated into independent projects V is used in the following software Chromium based web browsers Google Chrome Brave Opera Vivaldi and Microsoft Edge Couchbase database serverDeno runtime environmentElectron desktop application framework used by the Atom and Visual Studio Code text editorsMarkLogic database serverNativeScript mobile application frameworkNode js runtime environmentQt Quick runtime environmentOfficial website	2022-10-16 15:30:05
海外TECH	DEV Community	Repurposing Content for Content Creation	https://dev.to/nickytonline/repurposing-content-for-content-creation-3l4d	Repurposing Content for Content CreationSo I ve been streaming on Twitch since July blogging and given some talks To keep on with the learning in public theme and content creation I ve started a podcast called Nick s Cuts pod iamdeveloper com So what is it all about A podcast that is mainly tech related It s conversations I ve had on my Twitch stream livecoding ca with awesome people and maybe some other things That s the TL DR It s not exactly the Swyx Mixtape format from Shawn Wang swyx but I did take inspiration from it Another reason I started the podcast is to continue my content creation journey I work full time as an engineer so my time for content creation is limited to some degree I stream during my lunch hour and do editing in the evenings when I have time Aside from saving me time from creating new content repurposing content allows me to expand the reach of some of my content For example some friends can t always catch my Twitch streams dan ott danieltott Instant subscribe I love this idea so much I miss a lot of my friends streams and never remember to go back and rewatch not a problem with pods twitter com nickytonline s… PM Oct Nick Taylor nickytonline I ve started a podcast that is essentially great convos from my Twitch streams but it may end up being more than that You can find Nick s Cuts at Here s a taste of the first episode with bdougieyo chatting about OSS and saucedopen I m still no pro at content creation but folks in the space do like the concept of repurposing content bdougie on the internet bdougieyo nickytonline saucedopen This is a great idea Love repurposing content AM Oct I even came across a post about this topic from my co worker Jason Lengstorf jlengstorf a little while back titled Turn piece of dev content into ーuse the buffalo stick If you re a content creator I m curious about what your thoughts are on this or what other strategies you have for content creation Photo by Sigmund on Unsplash	2022-10-16 15:27:00
海外TECH	DEV Community	Getting Started with Amazon Elastic Container Service with Fargate	https://dev.to/aws-builders/getting-started-with-amazon-elastic-container-service-with-fargate-2ce2	Getting Started with Amazon Elastic Container Service with Fargate Introduction What is Docker Image SourceDocker is a tool that makes it easy to build deploy and run applications using containers Containers allow developers to package and deploy applications as a single package along with all necessary components such as libraries and other dependencies This ensures that the program will run on any other Linux machine regardless of your custom settings on the machine which may be different from the machine you use to write and test the code What is Amazon ECS Amazon ECS manages containers and allows developers to run applications in the cloud without configuring the environment to run their code It allows developers with AWS accounts to deploy and manage scalable applications running on groups of servers called clusters through application program interface calls and task definitions Amazon ECS makes it easy for developers to use Docker containers for a variety of tasks These range from hosting simple websites to running complex distributed microservices that require thousands of containers Running Amazon ECS with FargateYou can run services or tasks on AWS Fargate to deploy containers on serverless infrastructure managed by Amazon ECS Let s launch Amazon ECS on AWS Fargate using the Fargate launch type for our task In regions where Amazon ECS supports AWS Fargate the Amazon ECS First Startup wizard guides you through the Amazon ECS launch process using the Fargate launch type The wizard creates a cluster and gives you the option to run a sample web application Kindly watch the below video on how to create a task definition a service and a cluster using Fargate ConclusionYou have successfully created a task definition a service and a cluster using Fargate Gratitude for perusing my article till the end I hope you realized something unique today If you enjoyed this article then please share it with your buddies and if you have suggestions or thoughts to share with me then please write in the comment box Follow me and share your thoughts GitHubLinkedInTwitter	2022-10-16 15:02:34
海外TECH	DEV Community	AWS CDK Redshfit Demo	https://dev.to/aws-builders/aws-cdk-redshfit-demo-2ch5	AWS CDK Redshfit Demo AbstractFor getting started with AWS Redshift this post guides you to provide Redshift cluster and all necessary other resources such as VPC redshift IAM role S bucket where we load data to Amazon Redshift and a small EC instance as postgresql client using AWS CDK typescript Table Of ContentsAWS Redshift overviewRedshift cluster stacksDeploy stacksWorking with Redshift ClusterConclusion AWS Redshift overview AWS Redshift is a cloud based petabyte scale data warehouse service offered as one of Amazon s ecosystem of data solutions Based on PostgreSQL the platform integrates with most third party applications by applying its ODBC and JDBC drivers Amazon Redshift delivers fast query performance by using columnar storage technology to improve I O efficiency and parallelizing queries across multiple nodesRedshit cluster overviewNode slices in compute nodes Redshift cluster stacks The Redshift cluster is in VPC and under private subnet and security group so we first create the VPC stack and for saving cost max availabilityZones is set to const vpc new Vpc this prefix vpc vpcName prefix vpc maxAzs We will use S bucket to store JSON parquet datas and then load data from S bucket to redshift cluster as following flow Redshift needs a role so that it can consume that role to download data from S bucketconst s new Bucket this prefix data ingest bucketName prefix data ingest encryption BucketEncryption S MANAGED removalPolicy RemovalPolicy DESTROY enforceSSL true blockPublicAccess BlockPublicAccess BLOCK ALL const role new Role this prefix role roleName prefix role assumedBy new ServicePrincipal redshift amazonaws com s grantRead role In this post the redshift cluster is in multi node cluster with compute nodes type DC LARGE as default masterUser is created with password stored in secret manager as default option const cluster new Cluster this prefix cluster demo clusterName prefix demo vpc vpc masterUser masterUsername admin numberOfNodes clusterType ClusterType MULTI NODE removalPolicy RemovalPolicy DESTROY roles role Finally it s optional to create an EC instance as postgresql client to access redshift database as we can use Amazon Redshift query editor In practice application will use JDBC URL to connect to Redshift cluster in private network Back to the EC instance it requires following Only small instance type such as t smallAllocated in private subnet of redshift VPCAttached Security Group of the redshift cluster which already allow internal communicationInstance profile with only AmazonSSMManagedInstanceCore in order to start Amazon SSM agentAnd user data sh script to install postgresql at frist start const clusterSg cluster connections securityGroups clusterSg addIngressRule clusterSg Port allTcp Allow internal access Redshift const ec new Instance this prefix psql instanceName prefix psql vpc vpc securityGroup clusterSg instanceType InstanceType of InstanceClass T InstanceSize SMALL machineImage new AmazonLinuxImage generation AmazonLinuxGeneration AMAZON LINUX role new Role this prefix ec ssm roleName prefix ec ssm assumedBy new ServicePrincipal ec amazonaws com managedPolicies managedPolicyArn arn aws iam aws policy AmazonSSMManagedInstanceCore const userData readFileSync resolve dirname user data sh utf ec addUserData userData Deploy stacks Infrastructure of code for this project is ready we now deploy the stacks It s up to you to use concurrency option for fasten deployment and require approval to bypass confirmation of creating updating removing sensitive things cdk deploy concurrency require approval neverCheck redshift clusterGo to secret manager to get master user passwordOverview of all components Working with Redshift Cluster We use sample data in data sample amzn reviews en json you can find more in Amazon review data From the json file we use pyspark to convert it to parquet formatOverview of Parquet Parquet follows the Columnar Storage Model and is available to any project in the Hadoop Ecosystem Unlike the traditional Sequential Storage Model where data is written in sequence the Columnar Storage Model stores column values together Although the Sequential Storage Model has advantages in processing transactions it is not suitable for running Analytical Queries on Big Data Install pyspark by running pip install pyspark Note that it also require java openjdk to use the toolCovert json file to parquet cd data sample pysparkPython main Jun GCC on linuxWelcome to version gt gt gt df spark read json amzn reviews en json gt gt gt print Schema format df schema gt gt gt df show gt gt gt df write parquet amzn reviews en parquet Access EC instance by using SSM session aws ssm start session target i befc region ap southeast Connect redshift cluster database root ip bin psql h sin d redshift demo cnozowdmk ap southeast redshift amazonaws com U admin p d default db Password for user admin psql server SSL connection protocol TLSv cipher ECDHE RSA AES GCM SHA bits compression off Type help for help default db default db c prodreview prodreview Create json table view CREATE TABLE IF NOT EXISTS product reviews json review id varchar NOT NULL distkey sortkey product id varchar NOT NULL stars varchar NOT NULL review body varchar NOT NULL review title varchar NOT NULL reviewer id varchar NOT NULL language varchar NOT NULL product category varchar NOT NULL primary key review id Create parquet table view CREATE TABLE IF NOT EXISTS product reviews parquet language varchar NOT NULL ENCODE lzo product category varchar NOT NULL ENCODE lzo product id varchar NOT NULL ENCODE lzo review body varchar NOT NULL ENCODE lzo review id varchar NOT NULL distkey sortkey ENCODE lzo review title varchar NOT NULL ENCODE lzo reviewer id varchar NOT NULL ENCODE lzo stars varchar NOT NULL ENCODE lzo primary key review id Upload data amzn reviews en json and amzn reviews en parquet to S and then load them to redshift databaseLoad amzn reviews en json to the json table prodreview copy product reviews json prodreview FROM s sin d redshift data ingest amzn reviews en json prodreview IAM ROLE arn aws iam role sin d redshift role prodreview json auto ignorecase INFO Load into table product reviews json completed record s loaded successfully COPY prodreview SELECT COUNT FROM product reviews json count row Load amzn reviews en parquet to parquet table prodreview copy product reviews parquet FROM s sin d redshift data ingest amzn reviews en parquet IAM ROLE arn aws iam role sin d redshift role format as parquet INFO Load into table product reviews parquet completed record s loaded successfully COPY prodreview SELECT COUNT FROM product reviews parquet count row Compare loading time select datediff s starttime endtime as duration from stl query where query in query id of json copy query id of parquet copy RUN QUERIES query data for the question Do people who buy kitchen and grocery items leave higher ratings prodreview SELECT stars COUNT stars total ratings FROM product reviews json WHERE product category kitchen or product category grocery prodreview GROUP BY stars stars total ratings rows prodreview SELECT stars COUNT stars total ratings FROM product reviews parquet WHERE product category kitchen or product category grocery GROUP BY stars stars total ratings rows Conclusion Here we have demonstrated how to create a redshift cluster and its ETL using CDK typescript you can update the cluster as well as adding more S buckets or attach more roles to the redshift cluster for separte ETL processes through CDK stacks If you want to destroy all the resources created by the stack simply run cdk destroy all References COPY examplesredshift demoParquet Vu Dao Follow AWSome Devops AWS Community Builder AWS SA ️CloudOpz ️ vumdao vumdao	2022-10-16 15:02:32
海外TECH	DEV Community	Creating Skeleton Loading Animation in React	https://dev.to/documatic/creating-skeleton-loading-animation-in-react-4f38	Creating Skeleton Loading Animation in React IntroductionLoading screens are an important aspect f any application This lets the user know that the processing is going on There are lots of evolution in the loading screen We have moved from the simple Loading… message to the more advanced Skeleton Loading Animation Skeleton Loading animation is a more advanced loading animation and its looks dope You have seen it before on YouTube and other platforms Today we are going to create a Skeleton Loading Animation in React with the react loading skeleton library It is one of the most used libraries for creating skeleton loading animation with a single component In the end we will be able to achieve the below output for our loading screen So let s get started Setting Up the EnvironmentFor creating React app we have used Vite instead of CRA Vite creates a react application with minimal already created files and code This is quite fast in comparison with CRA You can start by running the following command in the terminal npm create vite latestAfter this entered the name of the project in the terminal I have used the skeleton loading react as the name After hitting enter choose the framework as React Lastly choose the programming language for the framework between JavaScript and TypeScript This will create the react application instantly Change the directory to skeleton loading react and run npm install in the terminal to install the packages Additionally we need to install the skeleton loading animation Run the below command in the terminal npm i react loading skeleton Other dependencies I have usedAxios For making calls to the APIChakra UI For building the component What are we building We are going to use the MovieDB API to fetch the trending movies and display them in the card component While making the call we are going to display our Loading Skeleton App jsLet s build the project with one component at a time Starting with the first component App js Let s look into the code then I explain it import useState useEffect from react import App css import axis from axios import AnimeCard from components AnimeCard import Grid from chakra ui react import LoadingSkeleton from components LoadingSkeleton function App const loading setLoading useState true state for loading const data setData useState data is extracted from the API const arr array for number of loading skeleton useEffect gt let timerId if loading timerId setTimeout async gt await axios get import meta env VITE MOVIEDB KEY then res gt setData res data results setLoading false return gt clearTimeout timerId loading return lt div className App gt lt h gt Trending Movie List lt h gt lt div className container gt loading amp amp lt Grid templateColumns repeat fr gap gt arr map item gt return lt LoadingSkeleton gt lt Grid gt loading amp amp lt Grid templateColumns repeat fr gap gt data amp amp data map item index gt return lt AnimeCard name item original title img item poster path genre id item genre ids gt lt Grid gt lt div gt lt div gt export default AppAt the top we are importing the necessary modules and libraries In the App function we use useState to define the variable The comments explain their purposes We have used the useEffect for making a call to MovieDB s API using Axios The function containing code for making a call only runs when the loading is set to true which is the default value We have also used the setTimeout function to delay the calling so that we can see the loading animation After making the call we are storing the response in the data variable In return we are conditionally rendering the component based on loading If it is true we are loading the LoadingSkeleton component otherwise MovieCard MovieCard ComponentCreating the final component should be done before creating the loading skeleton This will give us insight into the loading component We are creating the card in which the data of the movie will be displayed We have named the component MovieCard Here is the code for the component import React useState useEffect from react import axios from axios import Image Tag Heading from chakra ui react const MovieCard name img genre id gt const genre setGenre useState useEffect gt axios get then res gt let genre name res data genres filter item gt item id genre id setGenre genre name name genre id return lt div className cardContainer gt lt div className cardImg gt lt Image src img gt lt div gt lt div className tagContainer gt lt Tag size md variant solid colorScheme pink gt genre lt Tag gt lt div gt lt div className tagContainer gt lt Heading color white size md gt name lt Heading gt lt div gt lt div gt export default MovieCardIn MovieDB API the movie s genre comes with a code and for accessing the name of the genre using the code we are calling the API in the useEffect The return statement is where we are defining the card for the movie There is a parent container with the name cardContainer Within this we have the Image Genre name as a tag and title of the movie You can find the CSS of the component here container display flex justify content space between width max width px margin em auto cardContainer display flex flex direction column cursor pointer background color D border radius px margin top em border px solid transparent cardImg margin em border radius em tagContainer display flex flex wrap wrap justify content space between color white padding em padding bottom em This will result into the card look like this LoadingSkeletonNow it s time to create the loading skeleton The loading skeletons have the structure without the data We have to create these structures as per our data We are having an image container a tag for the genre and a heading tag with the title Let s discuss each component in our card one by one Parent ComponentThe parent component remains the same as it holds our component We do not need to recreate this Image ContainerWe need to create a component with the same resolution as the image This component will be displayed in place of an actual image while loading Here is the CSS for my card image cardImgLoading margin em width px height px background color a Genre TagI used another container for displaying the genre Here is the code for CSS tagContainerLoading margin left em margin bottom em width px height px background color DFC border radius px Title ContainerThe title is converted into a block component having a height and width This will be useful in displaying the loading animation Here is the code titleContainerLoading margin left em margin bottom em width px height px background color a border radius px Skeleton ComponentWe now just need to pass the above CSS as the class name in the Skeleton component lt Skeleton highlightColor ab baseColor ab className cardImgLoading gt Here is the description of the used props from loading skeleton react PropDescriptionDefaultbaseColor stringThe background color of the skeleton ebebebhighlightColor stringThe highlight color in the skeleton animation fffThe overall code of the LoadingSkeleton is import React from react import Skeleton from react loading skeleton importing the skeleton component import react loading skeleton dist skeleton css importing the css for the animation const LoadingSkeleton gt return lt div className cardContainer gt lt Skeleton highlightColor ab baseColor ab className cardImgLoading gt lt Skeleton highlightColor ab baseColor ab className tagContainerLoading gt lt Skeleton highlightColor ab baseColor ab className titleContainerLoading gt lt div gt export default LoadingSkeletonThis will result in the following loading animation Live WorkingI have created this project in a codesandbox container You can see it here ConclusionWe have successfully created a skeleton loading in React with skeleton loading react libraries You can explore with the Sandbox and create your own loading skeleton I hope this article has helped in understanding the loading skeleton in your React project Thanks for reading the article	2022-10-16 15:00:55
ニュース	BBC News - Home	Liz Truss still in charge despite U-turns, says Jeremy Hunt	https://www.bbc.co.uk/news/uk-politics-63275544?at_medium=RSS&at_campaign=KARANGA	calls	2022-10-16 15:48:01
ニュース	BBC News - Home	Track Cycling World Championships: GB's Neah Evans wins points race gold for first world title	https://www.bbc.co.uk/sport/cycling/63276701?at_medium=RSS&at_campaign=KARANGA	Track Cycling World Championships GB x s Neah Evans wins points race gold for first world titleBritain s Neah Evans wins her first World Championship title with victory in the women s points race in France	2022-10-16 15:21:10
ニュース	BBC News - Home	Leeds 0-1 Arsenal: Bukayo Saka scores winning goal	https://www.bbc.co.uk/sport/football/63189783?at_medium=RSS&at_campaign=KARANGA	outage	2022-10-16 15:57:40
ビジネス	不景気.com	愛知・豊田の家具店「タキソウ」に破産開始決定、負債2億円 - 不景気com	https://www.fukeiki.com/2022/10/takisou2.html	愛知県豊田市	2022-10-16 15:03:11
北海道	北海道新聞	久保建英、後半途中で退く　サッカースペイン１部、セルタ戦	https://www.hokkaido-np.co.jp/article/746261/	久保建英	2022-10-17 00:28:00
北海道	北海道新聞	習氏「台湾統一」踏み込む　長期支配にらみ「必ず実現」　中国共産党大会	https://www.hokkaido-np.co.jp/article/746245/	中国共産党	2022-10-17 00:28:19
北海道	北海道新聞	女子ケイリン、佐藤が２年連続銀　世界自転車、太田と梅川は敗退	https://www.hokkaido-np.co.jp/article/746259/	銀世界	2022-10-17 00:16:00