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IT	気になる、記になる…	スクエニ、｢ファイナルファンタジー｣や｢聖剣伝説｣など人気シリーズのスマホゲームの値下げセールを開催中（8月14日まで）	https://taisy0.com/2022/08/05/159820.html	人気シリーズ	2022-08-04 15:00:24
AWS	AWS Machine Learning Blog	Optimal pricing for maximum profit using Amazon SageMaker	https://aws.amazon.com/blogs/machine-learning/optimal-pricing-for-maximum-profit-using-amazon-sagemaker/	Optimal pricing for maximum profit using Amazon SageMakerThis is a guest post by Viktor Enrico Jeney Senior Machine Learning Engineer at Adspert Adspert is a Berlin based ISV that developed a bid management tool designed to automatically optimize performance marketing and advertising campaigns The company s core principle is to automate maximization of profit of ecommerce advertising with the help of artificial intelligence The …	2022-08-04 15:53:04
Linux	Ubuntuタグが付けられた新着投稿 - Qiita	M1 Mac上でx86ビルドのバイナリを動かしたかった時にクソ遅くてもうろたえないためのメモ	https://qiita.com/o88o88/items/ce7acaefca5d01fe6006	snipcpuspeedeventsperseco	2022-08-05 00:39:28
Git	Gitタグが付けられた新着投稿 - Qiita	Git奮闘録	https://qiita.com/blue-skies_contrail/items/43d835176e398721f1cb	記録	2022-08-05 00:24:11
海外TECH	DEV Community	TypeScript vs. JavaScript	https://dev.to/iarchitsharma/typescript-vs-javascript-3i8d	TypeScript vs JavaScriptTypeScript vs JavaScript is one of the most controversial topics in tech Some developers prefer TypeScript because it offers static strong typing while others prefer JavaScript because it is less complex In this article I will discuss my thoughts on this debate of which one is better than the other What is TypeScript TypeScript is an open source programming language for developing large level applications TypeScript was developed by one of the tech giants Microsoft in The actual reason behind this TypeScript development was to handle large scale applications TypeScript is also used by Angular a JavaScript framework for web development services According to the report TypeScript is already used by almost of JavaScript developers and another want to deploy it So let s look at the advantages and drawbacks of TypeScript and see if it s worth adding not just on your own projects but also on bigger scale projects and what it brings to the table TypeScript is a long term investment it takes time to learn and time to add things to your code but if you accomplish both of those things you ll start getting some very nice rewards from it and I believe these rewards are worthwhile So lets take a look at the Advantages and Drawbacks of TypeScript Advantage of TypeScript over JavaScriptTypeScript constantly highlights compilation errors throughout development As a result although JavaScript is an interpreted language runtime errors are less common TypeScript supports static strong typing whereas this is not in JavaScript TypeScript runs on any browser or JavaScript engine Excellent tools support including IntelliSense which offers active suggestions as code is added It has a namespace concept by defining a module Drawbacks of TypeScript over JavaScriptGenerally TypeScript takes time to compile the code A compilation step is necessary to convert TypeScript into JavaScript if we want to run the TypeScript application in the browser TypeScript does not support abstract classes Should I learn JavaScript or TypeScript Well understanding TypeScript will be simple for you if you are familiar with JavaScript The syntax and run time behavior of both languages are identical Due to its popularity JavaScript has a large development community and a lot of resources Because both languages are frequently used in the same way TypeScript developers may likewise take advantage of such resources Will TypeScript Replace JavaScript The best answer to the above question is NO of course Speaking of TypeScript it is a totally distinct language that only shares JavaScript s fundamental characteristics JavaScript cannot and will not ever be replaced ConclusionIn the end after going through all the insights we have curated in this article we can say that both languages have advantages and drawbacks Developers that wish to write understandable organised and clean code should use TypeScript Well we are not mentioning what TypeScript offers are including various live bugs checking and static typing Although JavaScript is not a comprehensive programming language it can be used with HTML to improve the quality of web pages Moreover you will find many experienced developers who are proficient in JavaScript coding Despite not being a full featured programming language JavaScript may be used alongside HTML to enhance the quality of web pages Additionally you may discover a lot of seasoned engineers that are skilled at coding in JavaScript Thanks for reading this article I know this is a debatable topic so I would love to here your point of view on comments Do follow me for more content like this What s next How JavaScript Works The History of JavaScriptYou need to learn Kubernetes RIGHT NOW	2022-08-04 15:49:02
海外TECH	DEV Community	How to Configure JitPack for Recent JDK Versions	https://dev.to/cicirello/how-to-configure-jitpack-for-recent-jdk-versions-4pek	How to Configure JitPack for Recent JDK VersionsI intend for this to be the first post of a series with various tips and tricks related to effective use of Maven repositories for dependency management artifact storage etc for Java and other JDK languages such as Kotlin My preferred Maven repository is of course the Maven Central Repository for a variety of reasons and I will likely include some posts on Maven Central later in the series For now however I am beginning with a tip related to JitPack specifically how to configure JitPack builds if your project requires recent JDK versions e g JDK version gt or if you want to build with a specific JDK distribution I am not affiliated with JitPack and this post is based on my recent experience configuring JitPack builds in a couple of my projects where the JitPack documentation didn t entirely cover my requirements Table of Contents The rest of this post is organized as follows About JitPack I need to start with an explanation of how JitPack works because it is a bit different than other Maven repositories Why JitPack Brief explanation of why I ve begun making my libraries available via JitPack in addition to other repositories How to Specify a JitPack Dependency Although not the purpose of this post it will be useful to explain how to specify a dependency on an artifact served from JitPack How to Configure JitPack Builds Explanation with examples of configuring JitPack builds including an example in a live project on GitHub Where you can find me About JitPackJitPack works a bit differently than most other Maven artifact repositories For most Maven repositories such as Maven Central or GitHub Packages you first build the artifacts either locally on your own system or perhaps as part of a CI CD workflow e g via GitHub Actions and then after building your artifacts e g various jar files of compiled class files source code documentation etc you deploy them to your chosen Maven artifact repository JitPack doesn t work like this Instead JitPack is designed to build artifacts on demand direct from a source code repository hosted on GitHub or any other git host such as GitLab Bitbucket etc The on demand build occurs the first time a version of an artifact is requested and then simply served thereafter One unique aspect of JitPack that directly derives from its approach is that developers can include dependencies on any public git repository on GitHub Bitbucket and other git hosts even if the maintainers of those repositories don t explicitly publish artifacts to any Maven repository Why JitPack I am already publishing artifacts of all of the Java libraries I maintain to Maven Central arguably the definitive Maven repository so why do I also publish to JitPack JitPack enables specifying any git tag branch pull request or commit hash as the version for a dependency You wouldn t want to rely on one of these in production However during development at times it might be useful to build against a very specific unreleased version of a dependency With JitPack you can do this by specifying the hash of the commit as the version or even specifying a branch Isn t this just like using a SNAPSHOT build Yes but in this case there is no reason to create SNAPSHOT builds that you may or may not need Or perhaps your SNAPSHOTs are built nightly but you find a need to build against a specific point in the git history that occurred between the nightly builds Or perhaps your nightly SNAPSHOTs are built from the default branch and you want to build a dependent against a feature branch that is a work in progress in the dependency that you are also working on This is essentially why I ve started publishing artifacts to JitPack in addition to Maven Central Essentially as a source of SNAPSHOT builds for any and all commits and for any and all branches including short lived pull request branches without any intervention on my part But wait did you just say started publishing artifacts to JitPack I thought you said JitPack handles all of this regardless of whether the maintainer of a repository publishes artifacts anywhere I did say that and it is true provided that JitPack can find a build file such as a Maven pom xml or the Gradle equivalent and provided that your project can build with the JitPack defaults We ll get to this in a bit How to Specify a JitPack DependencyThe details of how to specify dependencies depends upon your build tool I use Maven so my examples will use Maven By default Maven searches for artifacts of dependencies in the Maven Central Repository If you want to import dependencies from anywhere else you need to add the details to the lt repositories gt lt repositories gt section of your pom xml To import from JitPack insert the following into that section of your pom xml you might need to create such a section if you are currently importing only from Maven Central lt repository gt lt id gt jitpack io lt id gt lt url gt lt url gt lt repository gt To import a dependency from a Maven repository you need to specify its coordinates which consists in its groupId its artifactId and its version The groupId is generally a reverse domain or subdomain controlled by the one publishing the artifacts For example on Maven Central and GitHub Packages I use org cicirello as the groupId for all of my Java libraries However although JitPack does support such custom groupIds the groupId for JitPack is usually formed from the domain of the git host along with the username or organization name who owns the repository that you want to import The artifactId is the name of the artifact which is sometimes the name of a package or module within it but it is not required to be For JitPack artifactId is the name of the repository And version is well the version that you want My examples here will assume you are specifying a GitHub repository as a dependency but you ll need something very similar for other hosts like Bitbucket To import using a tag such as a release tag like v insert the following into the lt dependencies gt lt dependencies gt section of your pom xml lt dependency gt lt groupId gt com github USERNAME lt groupId gt lt artifactId gt REPOSITORY NAME lt artifactId gt lt version gt v lt version gt lt dependency gt JitPack also automatically supports dropping the v so if you want to be consistent with other Maven repositories you can also use lt dependency gt lt groupId gt com github USERNAME lt groupId gt lt artifactId gt REPOSITORY NAME lt artifactId gt lt version gt lt version gt lt dependency gt Or if you want to build against the current state of a specific branch perhaps main you can use lt dependency gt lt groupId gt com github USERNAME lt groupId gt lt artifactId gt REPOSITORY NAME lt artifactId gt lt version gt main SNAPSHOT lt version gt lt dependency gt Or even a specific commit hash with lt dependency gt lt groupId gt com github USERNAME lt groupId gt lt artifactId gt REPOSITORY NAME lt artifactId gt lt version gt COMMIT HASH GOES HERE lt version gt lt dependency gt Whichever of the above you use be aware that if the version you are importing has not previously been built there will be a delay in your build while Maven or Gradle or whatever build tool you are using waits for a response from JitPack since JitPack must first build the dependency before delivering artifacts Any subsequent imports whether by you or someone else will be without such delay Here are the equivalent examples as above but using one of my repositories for a Java library I maintain of stochastic local search and evolutionary algorithms Chips n Salsa With tag lt dependency gt lt groupId gt com github cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt v lt version gt lt dependency gt Dropping the v from the tag lt dependency gt lt groupId gt com github cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt lt version gt lt dependency gt Latest commit in default branch lt dependency gt lt groupId gt com github cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt master SNAPSHOT lt version gt lt dependency gt From a commit hash lt dependency gt lt groupId gt com github cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt cebedeefbadecf lt version gt lt dependency gt From a pull request lt dependency gt lt groupId gt com github cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt PR SNAPSHOT lt version gt lt dependency gt JitPack also supports configuring reverse domain I have also configured my reverse domain on JitPack so all of the above will likewise work with lt groupId gt org cicirello lt groupId gt in addition to lt groupId gt com github cicirello lt groupId gt which is nice for consistency with Maven Central But only the released versions are available via Maven Central such as through a dependency like lt dependency gt lt groupId gt org cicirello lt groupId gt lt artifactId gt chips n salsa lt artifactId gt lt version gt lt version gt lt dependency gt How to Configure JitPack BuildsYou may or may not need to configure JitPack at all If you have a Maven pom xml in the root of your repository or whatever the equivalent of this is for Gradle AND if your project can be built with Java then you likely won t need any configuration You or anyone else for that matter can already utilize JitPack to import your repository as a Maven dependency Upon finding a pom xml at the root of your repository JitPack will attempt to build using Java with the following mvn install DskipTestsI imagine that it skips running your tests to decrease the length of the delay the first time an artifact is requested This seems reasonable In my case most of my libraries require Java so without configuration JitPack builds fail To configure for a more recent JDK here are the steps Step Create a file named jitpack yml at the root of your repository This is where all configuration takes place Feel free to consult the jitpack yml for the project this post is based upon Chips n Salsa for full details Step Specify the JDK version within jitpack yml such as with jdk openjdkNote that if you were to guess like I did that the above is sufficient you d be incorrect You now need to install the JDK distribution that you want to use as well as explicitly specify that you want to use it I m using the Temurin distribution of OpenJDK in the project that this post is based upon You need both of the statements I ve added below Without the sdk use JitPack will continue to use Java You can find the full list of available JDKs on the sdkman site jdk openjdkbefore install sdk install java tem sdk use java temStep Update Maven The above might be sufficient in some cases For me it was not JitPack currently as of the time of the writing of this post has Maven installed Maven was released over years ago in April The lt release gt property for configuring Java version didn t exist then If you are using that as I am your JitPack build will fail unless you update Maven You can do that by revising the above to what follows which as of the writing of this post will update Maven to jdk openjdkbefore install sdk install java tem sdk use java tem sdk install maven mvn vYou don t really need the mvn v above I included that to show the version in the build logs Step Customize the install step You might be done at this point provided that JitPack s default build command of mvn install DskipTests is relevant to your project In my case I wanted to also disable one of JitPack s features One of JitPack s features which many probably like is that if the build produces a jar of the javadocs JitPack will automatically extract the javadocs and serve them including maintaining the javadocs for each release I would prefer it if they simply served the jar of the javadocs as Maven Central does rather than automatically hosting them For the libraries that I maintain I also host the javadocs on the project s site and would prefer if the definitive version of the javadocs is unambiguously the version hosted on my domain cicirello org Thus for JitPack builds I simply disable javadoc generation leading to the complete jitpack yml below jdk openjdkbefore install sdk install java tem sdk use java tem sdk install maven mvn vinstall mvn install Dmaven javadoc skip true DskipTestsImportant Note Because of the way JitPack essentially builds a snapshot of your repository even for release builds the jitpack yml must be present within the specific snapshot of your repository in order to apply For example for the library that this post is based upon Chips n Salsa the first release where the repository contains the configuration file is so JitPack will fail to build any prior version although earlier versions are available via Maven Central and GitHub Packages Likewise if you specify any commit hash prior to that of the commit where that configuration file was introduced the JitPack build will also fail Live Configuration Example See this jitpack yml for a complete and live example which is found within the following repository cicirello Chips n Salsa A Java library of Customizable Hybridizable Iterative Parallel Stochastic and Self Adaptive Local Search Algorithms Chips n Salsa A Java library of customizable hybridizable iterative parallel stochastic and self adaptive local search algorithmsCopyright C Vincent A Cicirello Website API documentation Publications About the LibraryPackages and Releases Build Status JaCoCo Test Coverage Security DOILicenseSupport How to CiteIf you use this library in your research please cite the following paper Cicirello V A Chips n Salsa A Java Library of Customizable Hybridizable Iterative Parallel Stochastic and Self Adaptive Local Search Algorithms Journal of Open Source Software OverviewChips n Salsa is a Java library of customizable hybridizable iterative parallel stochastic and self adaptive local search algorithms The library includes implementations of several stochastic local search algorithms including simulated annealing hill climbers as well as constructive search algorithms such as stochastic sampling Chips n Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally The library very extensively supports simulated… View on GitHub Where you can find meOn the Web Vincent A Cicirello Professor of Computer Science Vincent A Cicirello Professor of Computer Science at Stockton University is aresearcher in artificial intelligence evolutionary computation swarm intelligence and computational intelligence with a Ph D in Robotics from Carnegie MellonUniversity He is an ACM Senior Member IEEE Senior Member AAAI Life Member EAI Distinguished Member and SIAM Member cicirello org Follow me here on DEV Vincent A CicirelloFollow Researcher and educator in A I algorithms evolutionary computation machine learning and swarm intelligence Follow me on GitHub cicirello cicirello My GitHub Profile Vincent A CicirelloSites where you can find me or my workWeb and social media Software development Publications If you want to generate the equivalent to the above for your own GitHub profile check out the cicirello user statisticianGitHub Action View on GitHub	2022-08-04 15:27:40
海外TECH	DEV Community	Cybersecurity Programming: SQL Injection Scanner with Python	https://dev.to/bekbrace/cybersecurity-programming-sql-injection-scanner-with-python-32c4	Cybersecurity Programming SQL Injection Scanner with PythonHey Whether you re running on Windows Kali Linux or any other Debian based Linux distro or even a Mac user this short script under lines of Python code will work just fine Now SQL injection is a real world threat especially for big companies getting access to your database and gaining full control is horrible and especially if you have your own business No surprise here that it ranks amongst the top cybersecurity threats in the world Let us build a simple yet powerful scanner for any SQL injection attacks and see how it works URL GitHub Facebook Twitter bekbraceInstagram bek braceDev to bekbrace	2022-08-04 15:20:47
海外TECH	DEV Community	Build On Data & Analytics - Show notes	https://dev.to/aws/build-on-data-analytics-show-notes-a36	Build On Data amp Analytics Show notesWelcome to our first Build On Live Event which focuses on Data and Analytics AWS experts and friends cover topics ranging from data engineering and large scale data processing to open source data analytics and machine learning for optimizing data insights This event was hosted by Dani Traphagen and Darko Mesaros me and we had a blast welcoming all the amazing speakers and interacting with you our audience These are the show notes from that event which was live streamed on the th of July The recording of this event is available on our YouTube channel but in this article I will be linking each segment notes with its video so make sure to hit that subscribe button Individual session notes Intro and WelcomeWhat s Happening in the World of Data and Analytics NoSQL DatabasesData Ingestion Change Data CaptureData Quality Data Observability Data ReliabilityThe Serverless Future of Cloud Data AnalyticsLarge Scale Data ProcessingNot Your Dad s ETL Accelerating ETL Modernization and MigrationStream Processing Large Scale Data AnalyticsCreate Train and Deploy Machine Learning Models in Amazon Redshift Using SQL with Amazon Redshift MLUsing Amazon Managed Workflows for Apache Airflow MWAA to Schedule Spark Jobs on Amazon EMR ServerlessUnify Data Silos by Connecting and Sharing Varied Data Sources A Financial Service Use CaseTransactional Data Lakes Using Apache HudiClose the Multi Cloud Gap with Open Source SolutionsThe History and Future of Data Analytics in the CloudHow does the AWS Prototyping team build Intro and Welcome Guest Damon Cortesi Developer Advocate at AWSKey Points Why should people care about data analytics The answer Insight There s all this data all around usーsales data marketing data application data etc ーbut we need to make sense of it How can we better do that Data is valuable We need to ask questions about the data in order to make informed decisions Understand the difference between “junk data vs “valuable data We have a problem at data you need to log and collect How should people know what data to collect It boils down to knowing what questions you have to ask from the data and working backwards from there The biggest paradigm shift in the last years is that data is now stored in the cloud not on computers Everything s moving up the stack We re making it easier for people to get the job done without having to go as deep You can now get started just by using SQL Three key steps to dealing with data Collect data Understand data Keep your data safe Joke Break Did you know that under half of all data science jokes are below average What s Happening in the World of Data and Analytics Guests Lena Hall Head of Developer Relations North America and Matt Wood VP Business Analytics at AWSKey Points Matt Wood talks about how he got into working with AWS He was working on the sequencing of a human genome in Cambridge In the earlier days they used an iPod for data coordination and physically shipped it to different sites Back then you could do individual genomes in about a week The industry was dealing in gigabytes of data But as things evolved they had to think in terabytes insteadーhundreds of terabytes per week They couldn t get enough cost effective power in the data center to plug in more storage They had to think about where they would store all this data They figured if they re having this problem in the genome field others may have figured it out in other fields This data problem got Matt interested in cloud computing and led him to AWS And here he is today So what exactly is data analytics For starters data analytics is really messy Because of the way the data is collected some of it is organized functionally while sometimes it s stored logically What does data governance entail You want to have control but usually you can only control about of data However a whopping of data tends to be available As such it gives builders creative freedom to take that data and build applications around it It becomes a “highly polished gem that has real value The paradigm shift to data mesh It s early days for this but it solves some of the messiness while providing teams with agility and speed The idea is that you have a series of consumers and producers It gives you a lot of insight into the data such as who owns it It allows you to take data and add value to it There are emerging best practices that will give organizations a tremendous accelerating effectーbut don t jump on a new paradigm just because everyone else is doing it Questions to ask your team when thinking about data What is our level of data readiness Where is the bright highly polished jewel in our crown that we can do something with Where are we less ready What data do we wish we had started on sooner You must really understand where the business priorities are What is a real needle mover for the organization Be candid about your team s level of expertise and then build on that over time Learning is a life long pursuit Be mindful that you ll have to keep learning to remain relevant with the latest literature In short get a good sense of data readiness business priorities and where you have to expand NoSQL Databases Guest Alex DeBrie AWS Data HeroKey Points Core differences between SQL and NoSQL It s a matter of scaling NoSQL allows horizontal scalability putting different parts of your data on different machines As you scale up you simply get more machines instead of bigger machines Comparing different databases Dynamo vs Cassandra and Dynamo vs Mongo Dynamo is more authoritarian Mongo is more libertarian If you aren t careful you can lose some horizontal scaling Do you want more flexibility but less consistent performance or the other way around Think about your query model up front knowing what you want to leverage as you progress with your database There are two places where Dynamo excels high scale applications like Amazon and in the serverless world NoSQL You re replicating the same piece of data across multiple machines What is “single table Basically you can t join tables in NoSQL databases What you can do is pre join data In your single table you don t have an “orders table and a “customer table You have an application table There are no joins but they still model it like a relational database What is the performance impact of single table design It helps you avoid multiple requests in Dynamo On your main table you can get strong consistency if you have conditions Alex s DynamoDB wish list Adding a more flexible query model to Dynamo Indexing some of your data allowing for more flexible querying And finally billing Currently there s a provision model and a pay per request model Alex would love to see a combination of it where you can set a provision capacity and get billed for anything above that Resources The DynamoDB BookDynamoDB Developer Guide Common DynamoDB Data Modeling Patterns FooBar Serverless YouTube GraphQL DynamoDB and Single table DesignDynamoDB GitHubJoke Break Two DBAs walked into a NoSQL bar but they left when no one would let them join their tables Data Ingestion Change Data Capture Guests Abhishek Gupta Principal Developer Advocate amp Steffen Hausmann Specialist Solutions Architect at AWSKey Points The problem with real time data is that traditional batch processing may not suffice The value of insights can diminish over time The quicker you can respond the more valuable the insights will be For example How quickly can a store react to weather conditions so that enough umbrellas are in stock How much more complicated and expensive does it get when you go real time Well it can be more challenging than batch based systems Things get more complex from an operations perspective As such don t make the switch to real time just because it s “nice and interesting You need a valid reason to invest in a real time data stream Change data capture Almost all databases have this notion of logs It s used to capture changes to data and tables It s a useful way of detecting changes in a database Watch Abhishek Gupta demo Change Data Capture capturing changes to a database in real time Watch Steffen Hausmann walk through Zeppelin using Change Data Capture to build something useful with real time analytics using revenue as an example Resources MSK workshop Blogs Best practices for right sizing your Apache Kafka clusters to optimize performance and cost Data Quality Data Observability Data Reliability Guests Barr Moses CEO Co Founder of Monte CarloKey Points Data is huge and it s accelerating even more Data is still front and center It s at the forefront of strategy Companies are using data to make really important decisions For example Financial loans and lending Fintech is driven by data more than ever Companies like Jet Blue are running on data It s powering all products and these products are relying on data to be accurate Industries from media to eCommerce and FinTech are all using data Even traditionally non data centric companies are using it As such data has to be of high quality It has to be accurate and trustworthy How do you measure high quality data Historically it was centered on accurate data that s clean upon ingestion But today data has to be accurate throughout the stack What is data observability The organization s ability to fully understand and trust the health of the data in their system and eliminate data downtime e g When Netflix was down for minutes in due to duplicate data In other words wrong data can cause application downtime What is the difference between Data Governance vs Data Observability Instead it s more important to ask What problem are you trying to solve Data Observability is solving situations where people are using data but the data is wrong For example when the price of an item on a website is inaccurate Data Governance is the method in which companies try to manage their data in better ways How data breaks It s usually because of miscommunication between teams Data detection problems The data team should be the first to know when data breaks but they re often the last Resolution Reduce the time it takes to resolve a problem from weeks and even months to just hours Prevention Can we maintain the velocity of how we build while also maintaining the trust in the data we have Having an end to end approach and a focus on automation and machine learning helps monitor data accuracy Resources O Reilly book Data Downtime Blog www montecarlodata com blog Contact barr montecarlodata com The Serverless Future of Cloud Data Analytics Guest Wojcieh Gawronski Sr Developer Advocate AWSKey Points Serverless data analytics requires a lot of operational expertise and knowledge Why should we even think about serverless It goes beyond efficiency and speed We can better leverage scalability and tackle operational issues Serverless data analytics services help to ease out the learning curve By leveraging the provider s offering you can focus on development activities instead of panically building operational experience when scaling up to the demand As the services are based and fully compatible with open source software you are able to safely choose between a fully managed service and your own operations allowing you to easily change the direction According to estimates by we will have ZB of data zettabyte is a trillion bytesーyes that s one and zeroes For years we have constantly been generating vast amounts of data and the question arises How do we prepare in such an environment for the challenges related to the continually growing demand for infrastructure while not multiplying the costs of its maintenance Serverless data analytics will answer those questions It s easier to get started scale and operate when you go serverlessーespecially if you lack operational experience Watch Wojtek walk through a three step demo Acquire the data transform the data for loading into the data warehouse to gain insights and leverage the serverless approach Learn more about Redshift serverless with a walkthrough from Wojtek Joke Break What do you call a group of data engineers A cluster Resources GitHub Check out following services Large Scale Data Processing Guests Gwen Shapira Chief Product Officer Stealth StartupKey Points “Data product is one of those terms that everyone throws around It first appeared in We have all this dataーhow can we use it to drive a good user experience Control Plane as a Service First ask if you need this kind of architecture A lot of people are thinking about adapting this early on as an architectural concept which is a big shift from a few years back Control Plane as a Service gives you an opinionated way to use specific services and databases e g data planes For example with DynamoDB you can do almost anything However if you want to use it for a specific use case a lot of effort needs to be put in how to transfer a given problem into DynamoDB User experience is the most important thing in analytics today This is a shift from before when the end user considerations came last Gwen s recommendations for up and coming data builders Start with asking who is going to be using the product and build from there Good user experience is key and you want your infrastructure to support this Make your product as smooth and frictionless as possible Start with the customer and work backwards always Resources Designing Data Products The faces of Data Products are a little bit differentPresentation SlidesInfrastructure SaaS A control plane first architecture Not Your Dad s ETL Accelerating ETL Modernization and Migration Guest Navnit Shukla Sr Solutions Architect AWSKey Points Navnit helps customers extract value from their data at AWS ETL which stands for “extract transform and load is a data integration process that combines data from multiple data sources into a single consistent data store that is loaded into a data warehouse or other target system ETL is one of the most important parts of data One of the biggest problems with traditional ETL is getting lots and lots of data from different sources Traditional ETL tools weren t built to scale or to handle a variety of data Watch Navnit walk through AWS Glue a powerful ETL tool It does batching scaling and securing for youーall the important tools you need It s like having someone else do the laundry for you Navnit s advice for up and coming data scientists and engineers Stop going to ETL Just go to ELT extract load and transform Build that ELT process instead Bring all the data as it is and then do your transformation on top of it Resources Glue Web Page AWS Summits AWS Big Data Blog Validate evolve and control schemas in Amazon MSK and Amazon Kinesis Data Streams with AWS Glue Schema RegistryAWS Glue Adding Classifiers to a CrawlerServerless Data Integration webinar Stream Processing Large Scale Data Analytics Guest Tim Berglund Vice President of Developer Relations StarTreeKey Points We re having an architectural paradigm shift The last major software architecture paradigm was in the late s It was called “client server Then the web happened but it didn t depart from client server in a meaningful way Today event driven architecture is commonplace This is demanding a new way of building systems The whole stack is different now Kafka is where the events based systems are living Event data is very valuable right now The value of that event declines quickly You want to respond right away On the other hand accumulating context gets you more and more value over time There s a fear regarding old tools that no longer work while not having clarity over what the new tools are just yet People are building things further down the stack because the stack hasn t come up to meet them yet OLTP databases record transactions in a system on an ongoing basis In OLAP databases you dump a lot of data in and then ask questions about it Data is losing its value over time For example you might ask how long it takes to get a local Smashburger delivered It becomes less relevant with each second Tim s advice for Cassandra or GitHub users Stuff is changing faster than you know See the upcoming waves faster than you did before Resources Perishable Insights Forrester Create Train and Deploy Machine Learning Models in Amazon Redshift Using SQL with Amazon Redshift ML Guest Rohit Bansal Analytics Specialist Solutions Architect AWSKey Points Rohit has over two decades of experience in data analytics What s Redshift Amazon Redshift is a fully managed petabyte scale data warehouse service in the cloud It s giving machine learning capabilities to data analysts Anyone who knows SQL can use Amazon Redshift to create train and deploy ML models using Redshift ML using SQL Why do we need Redshift ML Data analysts SQL users want to use ML with simple SQL commands without learning external tools Data scientists ML experts want to simplify their pipeline and eliminate the need to export data from Amazon Redshift BI professionals want to leverage ML from their SQL queries used in the Dashboard When you run the SQL command to create the model Amazon Redshift ML securely exports the specified data from Amazon Redshift to Amazon S and calls SageMaker Autopilot to automatically prepare the data select the appropriate pre built algorithm and apply the algorithm for model training Amazon Redshift ML handles all the interactions between Amazon Redshift Amazon S and SageMaker abstracting the steps involved in training and compilation After the model is trained Amazon Redshift ML makes it available as a SQL function in your Amazon Redshift data warehouse Types of algorithms supported by Redshift ML Supervised Model type XGBoost Linear Learner Multi Layer Percetron MLP Problem type Binary classification Multi class classification etc Non supervised Clustering Redshift helps operationalize insights It s solving for Data Analysts SQL users want to use ML with simple SQL commands without learning external tools Data scientists ML experts want to simplify their pipeline and eliminate the need to export data from Amazon Redshift BI professionals want to leverage ML from their SQL queries used in the DashboardHow much does Redshift cost Amazon Redshift ML leverages your existing cluster resources for prediction so you can avoid additional Amazon Redshift charges Redshift changes Rohit would like to see Look to include data drift in the future Watch Rohit do a walkthrough of Redshift It will showcase how easy it is to create ML models within Redshift using Redshift ML Sales data Resources Amazon Redshift ML Getting StartedCreate and Train ML Models with Ease Using Amazon Redshift ML Using Amazon Managed Workflows for Apache Airflow MWAA to Schedule Spark Jobs on Amazon EMR Serverless Guest Damon Cortesi Principal Developer Advocate AWSKey Points The current trends in data and analytics “Managed data lakes with modern storage layers like Hudi Iceberg and Delta Flurry of activity mid stack data catalogs streaming services and a desire to move up the stack and abstract the hard stuff Apache Airflow makes your job easy Why is MWAA better Why should developers and builders use it Airflow can be complex to set up and run But in order to run a production environment you need different components scheduler web server task runner You can run it yourself but if you want the environment to run for you then MWAA will do that You can worry about more important things Is there a cost to MWAA Yes It s a minimum of a month If you have a small Airflow environment it might be worth running it on your own EMR Serverless It s easy and fast to run Spark and Hive jobs on AWS How is EMR Serverless different from other EMR offerings such as EC EKS You can think of it as a broad spectrum EMR on EC gives you the most flexibility and control of configuration and underlying instances If your job has very specific characteristics and you need to optimize the underlying instances CPU vs Memory vs GPU for example or you need a specific set of resources EMR on EC is a good option EMR on EC also has the broadest set of frameworks supported Today EMR on EKS supports Spark and EMR Serverless supports Spark and Hive Watch Damon do an extensive walkthrough running EMR Serverless Spark jobs with Amazon Managed Workflows for Apache Airflow The team talks about the differences between using EMR Glue Athena etc to collect and manage data Resources You can take a look at on demand capacity mode that can increase the limits automatically depending on the workload More info here Error Handling with DynamoDBAWS Analytics on YouTubeDamon s GitHubData Containers on GitHub Unify Data Silos by Connecting and Sharing Varied Data Sources A Financial Service Use Case Guests Jessica Ho Sr Partner Solutions Architect and Saman Irfan Specialist SA at AWSKey Points Let s talk about data sharing What kind of data sharing are we talking about exactly And why are we doing it One of the best ways we use data sharing in our day to day lives is for making informed decisions For example when shopping We can see reviews which is basically other people sharing data Then we analyze it Based on this we decide whether we should buy the product or not When talking about organizations they can make informed business decisions through data sharing across different business units There s an incurring desire to drive insights from the massive data we have But how can we access it in a secure and efficient manner We need to bring all the data together to a single source and then share it out to different business units based on their needsーall without compromising the data s integrity For example Stripe produces software and API that allows businesses to process payments conduct ecommerce etc It s important for their customers to have access to this data so that they can understand how their business operates What problems did Stripe solve with data sharing They launched a product called Data Pipeline and it s built around the Redshift sharing ability Their customers can acquire specific data that s unique to that customer Stripe is always looking for ways for customers to extract relevant data from them How do we share data through Redshift Storage is shared with different compute clusters Watch Saman demo live data sharing on Amazon Redshift It s very simple and secure with Redshift Hear more about Amazon Redshift Spectrum too What is a feature Saman would remove from Redshift data sharing Currently the producer cluster owns the data Instead it would be good to have no owners of the data A one click painless migration would be great too Resources Seamless Data Sharing Using Amazon RedshiftAWS Big Data Blog Ingest Stripe data in a fast and reliable way using Stripe Data Pipeline for Amazon RedshiftAWS Big Data Blog Sharing Amazon Redshift data securely across Amazon Redshift clusters for workload isolationAWS Big Data Blog Share data securely across Regions using Amazon Redshift data sharingStripe Data Pipeline solution landing page Transactional Data Lakes Using Apache Hudi Guest Shana Schipers Specialist SA Analytics AWSKey Points Shana focuses on anything Big Data at AWS Defining Apache Hudi No one term can cover it all It s more than a tabling formatーit s a transaction data lake framework However it adds features on top of your data lake such as index transactions record level updates currency control etc Why does this matter We re using data lakes more and more often and collecting more data than ever before Data warehouses are getting expensive to scale and are limiting to data If we want to run machine learning and aggregate data we need to move toward a data lake At scale companies want to know that their data is good We need to ensure data consistency That s where Hudi comes in If you dump stuff into a data lake you want to be able to delete data too You need things like Hudi to make this possible Typically objects in data lakes are immutable This can be very time consuming Hudi manages this for you Hudi also does file size management Apache Hudi is an open source tool that allows you to use transactional elements on top of the data lake Hudi has two table types One of these is amazing at streaming data ingestion There are lots of options for streaming in data including Glue EMR Athena Presto Treno Spark etc Watch Shana do an extensive demo on Apache Hudi It s hard to explain but easy to learn What feature would Shana change in Apache Hudi To be able to ingest into multiple tables using Spark streaming and that EMR would autoconfigure all its sizing and memory for Spark if you re using Hudi Resources Apache HudiAmazon EMR HudiTransactional amp Mutable Data Lakes on AWS Immersion DayApache Hudi Connector for AWS Glue Close the Multi Cloud Gap with Open Source Solutions Guests Lotfi Mouhib Sr Territory Solutions Architect and Alex Tarasov Senior Solutions Architect at AWSKey Points Lotfi and Alex talk about Apache Nifi and Apache Hop There are a lot of different types of customers some more heavily into data than others Managing or building a framework yourself can be a very complicated task Open source tools can help speed up your development process and make it more endurable as well Apache NiFi allows you to move data from Source A to Source B without needing extensive data transformation You can deploy without heavy coding behind the scenes Apache Hop allows small bits of data to hop between different parts of the pipeline Both NiFi and Hop are similar in the way that the data is moving from one place to another It s data flow They can accelerate migration projects as there s less code to write They also help close the gap when there are no required connectors available in managed services Both Hop and NiFi allow you to extend the functionality by adding existing java libraries and using them with your data pipeline The Apache Hop community has done great work by decoupling the actual data pipeline from the execution engine so it can run on different engines That gives the flexibility to use managed services like EMR to run your pipelines with less management overhead Apache NiFi is a data movement toolーit s not a strong processing engine It helps you move data from one source to a sink while applying light transformation on it Why use Apache NiFi and not other tools Apache NiFi has been in the market for more than years has reached maturity and has a strong supporting community Apache NiFi also focuses solely on data movement and allows you to apply the transformation engine of your choice such as Apache Spark or any other ETL engine Apache NiFi allows you to follow IAM best practices Apache NiFi s core value is in data movement so it s not suitable for complex joins like a relational database or complex event processing for streams like Apache Flink Watch Alex demo Apache Hop Watch Lotfi demo Apache NiFi Resources Apache NiFiApache HopAWS Identity and Access Management introduces IAM Roles Anywhere for workloads outside of AWS The History and Future of Data Analytics in the Cloud Guests Imtiaz Sayed Tech Leader Analytics and TJ Green Principal Engineer at AWSKey Points How is data analytics evolving What does the future of analytics look like It s too early to talk about its history as it isn t actually that old But the evolution has been fascinating The biggest changes have happened in the last years The rate of evolution is huge Everything we do today leaves a digital footprint There s a need to mine these data points and generate insights to make improvements We ve evolved from data houses to data lakes to data meshes And to think that data used to live on something as simple as a cassette Much has changed Kafka used to be a message bus but now these systems are being used differently Kafka is now being placed as a buffer Data links were supposed to be mutable but now you can modify delete and insert data We have Redshift and Aurora performing independent memory and scale storage Redshift is now doing machine learning and real time streaming The big change that happened years ago was the beginning of the move to the cloud Before we were living in an on premise warehousing world It was very expensive a large investment that companies had to deal with Redshift was one of the pioneers of using cloud in You could just sign up and not have to buy or administer anything yourself The price was also very compelling Competition has always been fierce in this space since then moving innovation along The cloud also allows us to scale and be more flexible Use cases for data analytics today have traversed every industry such as retail healthcare and oil and gas It enables both large enterprises and startups What is moving the needle for customers today Price performance and ease of use A lot of these factors are built into AWS products For example Glue has features that provide an easy UI UX experience to work with your data You don t have to be in the weeds with ETL Most customers don t want to see how the sausage is made They want the thing to perform well and be cheap but they don t want to have to turn a bunch of knobs to make it happen We re taking on the pain to make it easier for the customer Pain points of moving to the cloud It s quite complex One of the major pain points is working with bringing all that data together Defining data mesh Having the ability to share your data securely with multiple producers who can share the data securely with multiple consumers Data mesh is not easy to implement and it s not for everyone Ultimately you ll want to start small and scale fast Joke Break What s the difference between God and DBA God does not think he s a DBA Joke Break Two managers are talking to each other One asks “How many data engineers work on your team The other replies “Half of them Resources Amazon Redshift Re Invented Paper How does the AWS Prototyping team build Guests Sebastien Stormacq Principal Developer Advocate amp Ahmmad Youssef Team Lead Big Data Prototyping at AWSIn this segment check out how our AWS Prototyping team builds together with our customers And see an amazing demo of get this moving data between a Relational Database and an Object store Ahmmad will show us how to migrate data from a Microsoft SQL Server running on an EC instance to an Amazon S bucket All that using Amazon Data Migration Service DMS Magic 🪄Thank you all for being part of this wonderful event Please stay tuned for more events like this And if you are looking for a weekly dose of Build On join us every Thursday at AM Pacific live on Twitch Keep up to date with us by answering a simple form here	2022-08-04 15:12:01
海外TECH	DEV Community	Hide Posts From Particular Categories From WordPress Homepage Without Using a Plugin	https://dev.to/digitalkube/hide-posts-from-particular-categories-from-wordpress-homepage-without-using-a-plugin-2f21	Hide Posts From Particular Categories From WordPress Homepage Without Using a PluginBy default the homepage of your WordPress site shows posts from all the categories However it is possible to exclude certain categories from being displayed on your homepage but there s no option to do that in WordPress out of the box I wanted to hide posts from the deals category on my site because a lot of affiliate programs misunderstand internet marketing blogs that post coupons as deals sites which they do not allow To avoid confusion I decided to hide all the posts from the deals category from my site s home In this tutorial I will show you how to create a category filter without using a plugin You need to edit your site s functions php file and add the following code function hide category home query if query gt is home query gt set cat return query add filter pre get posts hide category home Replace with your category s ID Don t remove Use the below code to hide posts from multiple categories function hide category home query if query gt is home query gt set cat return query add filter pre get posts hide category home Click save and you re done	2022-08-04 15:12:00
Apple	AppleInsider - Frontpage News	China smartphone market plummets as Apple gains ground	https://appleinsider.com/articles/22/08/04/china-smartphone-market-plummets-as-apple-gains-ground?utm_medium=rss	China smartphone market plummets as Apple gains groundOverall smartphone shipments in China are plummeting toward their lowest point in a decade though signs indicate Apple is still faring well in the environment iPhone modelsIn the first half of the smartphone market declined to million shipments according to information released by the China Academy of Information and Communications Technology that was seen by Nikkei Read more	2022-08-04 15:47:08
Apple	AppleInsider - Frontpage News	Foxconn reportedly expanding iPhone production in India	https://appleinsider.com/articles/22/08/04/foxconn-reportedly-expanding-iphone-production-in-india?utm_medium=rss	Foxconn reportedly expanding iPhone production in IndiaFoxconn is expected to expand one of its factories in India to enable iPhone manufacturing thus increasing production capabilities in the country Foxconn is building an addition on an India factory for iPhone productionThe existing facility in Tamil Nadu is close to the Chennai facility already used for iPhone production Foxconn is expected to finish the new expansion and begin hiring within the next two months Read more	2022-08-04 15:17:58
海外TECH	Engadget	Instagram is expanding NFT features to more than 100 countries	https://www.engadget.com/instagram-nft-expansion-154058568.html?src=rss	Instagram is expanding NFT features to more than countriesThe non fungible token NFT market has fallen off a cliff but that s not stopping Instagram from doubling down on digital collectibles After a test launch in May the app is expanding its NFT features to more than countries across Africa Asia Pacific the Middle East and the Americas Instagram users can include NFTs in their feed and messages as well as in augmented reality stickers in Stories NFT creators and collectors are automatically tagged for attribution You can t buy or sell NFTs on Instagram just yet but Meta has strongly hinted it s working on a marketplace As of today Instagram now supports third party wallets from Coinbase and Dapper in addition to Rainbow MetaMask and Trust Wallet On top of the Ethereum and Polygon blockchains it will also support Flow Meta CEO Mark Zuckerberg announced the expansion in where else an Instagram post He included photos of a Little League baseball card he had made of himself as a kid A young Zuckerberg gifted it to his favorite camp counselor Allie Tarantino who now plans to sell both the signed card and an associated NFT quot On the back of his card he put a batting average ーwhich is like impossible in baseball quot Tarantino told the Associated Press quot So even as a little kid he was aiming big View this post on InstagramA post shared by Mark Zuckerberg zuck	2022-08-04 15:40:58
海外TECH	Engadget	Paramount+ hits 43 million subscribers as streaming rivals struggle	https://www.engadget.com/paramount-plus-subscribers-grow-152820376.html?src=rss	Paramount hits million subscribers as streaming rivals struggleYou might think a network specific streaming services like Paramount doesn t stand a chance in a grim market when even Netflix is floundering but it s apparently thriving The company has revealed that Paramount added million subscribers in the second quarter with more than million total users And that s after withdrawing from Russia ーif it weren t for that the service would have added million viewers ViacomCBS partly credited the surge to expansions to more countries including the UK Ireland and South Korea However it also pointed to success with content that included its Halo series Star Trek Strange New Worlds movies like Sonic the Hedgehog and live Champions League matches Paramount is still leaning on its sci fi audience then but not as much as it has in the past The overall Paramount subscriber count is still tiny compared to Netflix million and Amazon Prime Video over million Its growth is a sharp contrast to Netflix s nearly million lost subscribers though The firm is also keen to note that it had the most sign ups and net additions of any US based premium subscription streaming service in the quarter according to Antenna data In other words Paramount was outperforming all its main rivals including Apple TV Hulu and Peacock Whether or not that trend continues is uncertain Paramount is still expanding to more countries and should be available in markets by the end of the year It can count on those newcomers to boost its numbers for a while Eventually though the streamer will be more reliant on the quality of its catalog to grow its audience And while there have clearly been some hits heavyweights like Amazon and Netflix still have plenty of money and momentum in their favor	2022-08-04 15:28:20
海外TECH	Engadget	UK trials roadside van that detects if drivers are holding their phone	https://www.engadget.com/roadside-van-test-detect-driver-phone-seatbelt-safety-151036701.html?src=rss	UK trials roadside van that detects if drivers are holding their phoneUK police are testing a roadside van that can detect whether a driver is holding a phone while they re at the wheel The three month trial is being conducted in Warwickshire with the help of government owned National Highways which oversees motorways and major A roads in England The test will help determine how the tech may be used in the future according to The Guardian The van which can also check whether drivers or passengers are wearing seatbelts is kitted out with several cameras that capture footage of passing vehicles An AI system analyzes the images for possible phone and seatbelt violations Police say the quot most serious breaches quot spotted during the trial may be prosecuted while other drivers will receive warning letters Distracted driving is a serious issue In Britain in there were collisions in which it was determined that a driver was using a phone Meanwhile data shows that percent of car occupants who died in crashes in the country in were not wearing their seatbelt The trial is part of National Highways plan to prevent any deaths or serious injuries on its network by Future tests may see the van being equipped with tech that can detect vehicles driving too close to each other	2022-08-04 15:10:36
Cisco	Cisco Blog	Compliant or not? Cisco DNA Center will help you figure this out.	https://blogs.cisco.com/networking/compliant-or-not-cisco-dna-center-will-help-you-figure-this-out	network	2022-08-04 15:00:38
Linux	OMG! Ubuntu!	Ubuntu 22.04 Point Release Delayed Until Aug 11	https://www.omgubuntu.co.uk/2022/08/first-ubuntu-22-04-point-release-delayed-until-august-11	Ubuntu Point Release Delayed Until Aug The first point release in the Ubuntu LTS series will arrive a week later than originally planned due to issue affecting the OEM install option This post Ubuntu Point Release Delayed Until Aug is from OMG Ubuntu Do not reproduce elsewhere without permission	2022-08-04 15:24:19
海外科学	NYT > Science	Fossil Find Tantalizes Loch Ness Monster Fans	https://www.nytimes.com/2022/08/04/science/loch-ness-monster.html	Fossil Find Tantalizes Loch Ness Monster FansPlesiosaurs went extinct million years ago but evidence that the long necked reptiles lived in freshwater not just oceans has offered hope to Nessie enthusiasts	2022-08-04 15:10:59
海外TECH	WIRED	Alex Jones' Accidental Text Dump Is Hilarious—and Alarming	https://www.wired.com/story/alex-jones-accidental-text-dump-is-hilarious-and-alarming/	accidental	2022-08-04 15:45:52
金融	◇◇　保険デイリーニュース　◇◇（損保担当者必携！）	保険デイリーニュース(08/05)	http://www.yanaharu.com/ins/?p=4994	oracl	2022-08-04 15:44:55
金融	RSS FILE - 日本証券業協会	株券等貸借取引状況（週間）	https://www.jsda.or.jp/shiryoshitsu/toukei/kabu-taiw/index.html	貸借	2022-08-04 15:30:00
金融	金融庁ホームページ	サステナブルファイナンスの取組みについて公表しました。	https://www.fsa.go.jp/policy/sustainable-finance/index.html	取組み	2022-08-04 17:00:00
ニュース	@日本経済新聞 電子版	「65歳未満で軽症・基礎疾患なし」は受診控えて　厚労相 https://t.co/dY9UGVRAUT	https://twitter.com/nikkei/statuses/1555209103084883968	軽症	2022-08-04 15:08:39
ニュース	BBC News - Home	Tim Westwood: BBC launches inquiry into response to claims against DJ	https://www.bbc.co.uk/news/entertainment-arts-62338288?at_medium=RSS&at_campaign=KARANGA	claims	2022-08-04 15:40:29
ニュース	BBC News - Home	Brittney Griner: Basketball star jailed for nine years on drug charges	https://www.bbc.co.uk/news/world-europe-62427635?at_medium=RSS&at_campaign=KARANGA	charges	2022-08-04 15:50:36
ニュース	BBC News - Home	China fires missiles near Taiwan after Pelosi visit	https://www.bbc.co.uk/news/world-asia-62419858?at_medium=RSS&at_campaign=KARANGA	beijing	2022-08-04 15:43:49
ニュース	BBC News - Home	US police charged over death of Breonna Taylor	https://www.bbc.co.uk/news/world-us-canada-62427546?at_medium=RSS&at_campaign=KARANGA	knock	2022-08-04 15:40:00
ニュース	BBC News - Home	This Is Going To Hurt creator Adam Kay issues NHS suicide warning	https://www.bbc.co.uk/news/uk-england-london-62348826?at_medium=RSS&at_campaign=KARANGA	memorial	2022-08-04 15:29:17
ニュース	BBC News - Home	UK interest rates see biggest rise in 27 years	https://www.bbc.co.uk/news/business-62405037?at_medium=RSS&at_campaign=KARANGA	england	2022-08-04 15:12:24
ニュース	BBC News - Home	Commonwealth Games: Fred Wright and Anna Henderson win time trial silver as Geraint Thomas takes bronze	https://www.bbc.co.uk/sport/commonwealth-games/62421241?at_medium=RSS&at_campaign=KARANGA	Commonwealth Games Fred Wright and Anna Henderson win time trial silver as Geraint Thomas takes bronzeEngland s Fred Wright and Anna Henderson win silvers in time trials as Wales Geraint Thomas takes bronze after crashing	2022-08-04 15:13:27
サブカルネタ	ラーブロ	22/217　中華そば　敦：煮干しそば　塩、味玉、チャーシュー、韮水餃子（6個、ショップカード10ポイントのサービス）	http://ra-blog.net/modules/rssc/single_feed.php?fid=201473	中華そば	2022-08-04 16:05:09
北海道	北海道新聞	渋野６５で好発進、全英女子ＯＰ　古江は７５と出遅れ	https://www.hokkaido-np.co.jp/article/714328/	女子ゴルフ	2022-08-05 00:21:17
北海道	北海道新聞	ポケＧＯ札幌ＧＯ　市電の低床車両　５日から運行	https://www.hokkaido-np.co.jp/article/714329/	札幌市中央区	2022-08-05 00:18:13
北海道	北海道新聞	ペロシ米下院議長、板門店訪問　尹氏、対面避け電話会談	https://www.hokkaido-np.co.jp/article/714271/	電話会談	2022-08-05 00:01:12
北海道	北海道新聞	夜景に大輪　３年ぶり　函館で道新花火大会	https://www.hokkaido-np.co.jp/article/714306/	花火大会	2022-08-05 00:14:12