You know, un-phishable user identities with, you know, hardware second factor, and then gave some examples of how customers can leverage that on top of Google Cloud Platform. MARK: Very cool. MIKE: Block storage for virtual machine instances running on Google Cloud. Map. We'll be talking to Julia in a minute. MARK: Hey, Francesc. this example is in the GitHub repository And you work for Cloud Technology Partners? MARK: You have to use the URL fetch library. It kind of does it for you. The MapReduce job uses Cloud Bigtable to store the results of the map operation. MIKE: We started with a little history of mapreduce and sort of how that new programming paradigm really changed the way that we do data processing, and then, we talked about how that diverges a little bit. So in our talk yesterday, and Frances just mentioned this, the mapreduce paper kind of set off two parallel streams, and one at Google ultimately led to cloud Data Flow, and another was the open source community took the mapreduce paper and created just a whole ecosystem around it. Wonderful. Not really. I got some really interesting answers back. NEIL: Yeah. MARK: It's pretty cool. Like data product? MARK: Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. He was part of the Day 2 Keynote Yes. I'm actually--I'm actually very happy that Julia's here, because since we are here on the floor, we are not watching the talks, and everyone that I heard that went to your talk was very excited about it, and they said it was amazing. Mike discusses how people migrate to Google Cloud Platform and how they evolve once on it. Congratulations on that. You're talking about the entire U.S. market has to be analyzed in four hours on a daily basis, and so it's not--it's not insignificant. FRANCESC: FRANCES: Yeah. FRANCESC: That was an awesome experience. Solution for running build steps in a Docker container. Following on from the recent post GCP Templates for C4 Diagrams using PlantUML, cloud architects are often challenged with producing diagrams for architectures spanning multiple cloud providers, particularly as you elevate to enterprise level diagrams.. Sensitive data inspection, classification, and redaction platform. That's a very good question. I uploaded a picture of an octopus from an aquarium. So far, when I--what I do is I start with App Engine by default, and if I cannot really do it on App Engine, but it's really, really close--it's, like, a small thing, then I consider Manage VMs. Add intelligence and efficiency to your business with AI and machine learning. GCP partner panel: Learnings from real world cloud migration, Data Processing & OSS: The NEXT Generation, Build smart applications with your new superpower: cloud machine learning, Analyzing market events at 34M reads/sec and 22M writes/sec with NoOps on GCP. I thought that was amazing, so--. FRANCESC: FRANCESC: MARK: Registry for storing, managing, and securing Docker images. MARK: Mark interview some of the This was true within Google as well as outside of Google in the form of Hadoop/MapReduce (for some “Hadoop” and “data science” are synonyms). JULIA: FRANCESC: Thank you so much. But I think those might be my other favorite of Next. MIKE: Nothing serious. Chrome OS, Chrome Browser, and Chrome devices built for business. NEIL: Container environment security for each stage of the life cycle. So yeah. ROMIN: Solutions for content production and distribution operations. Processes and resources for implementing DevOps in your org. When you say, "Move them up the stack," could you tell everybody more about that? It was Go-related. Well, thanks again to all of those speakers that took the time to go by the Google Cloud Platform Podcast booth at GCPNext. It was--lots of--lots of lots of lots of interviews. Yeah, okay. I'm well. MIKE: Analytics and collaboration tools for the retail value chain. Cloudera, Inc. (2009)MapReduce Algorithms,(Consulter le 23/12/ 2014). Private Git repository to store, manage, and track code. But the URL--the URL library, actually--the URL fetch library also provides an HTTP client, if you need to. Well, so the load balancer, you know, does HTTP and HTTPS, but you know, to be perfectly honest, look, you know, if you're running on the Internet these days, you'd better protect yourself with TLS. Absolutely. Well, okay. It's not like we've got a team of thousands of developers out there. Most videos from GCP Next 2016 are already available on YouTube. CPU and heap profiler for analyzing application performance. FRANCESC: Oh, yeah, yeah. One is a about BQ itself as available through Google Cloud Platform (GCP); the other is about the internal Google tool Dremel that BQ is based on. Cloud-native document database for building rich mobile, web, and IoT apps. It was great. We had a lot of new ideas that we kept doing, but it was this really homogenous environment, right? Definitely. Francesc and Go for it. FRANCES: (Image source: Google Dremel Paper) BigQuery vs. MapReduce. There is a single thread for running Go routines on App Engine, and that's, like, just the one. Collaboration and productivity tools for enterprises. FRANCESC: Naturally. FIS is the world's largest financial services technology firm. and his current areas of focus are IoT, Big Data, and containers. GPUs for ML, scientific computing, and 3D visualization. Examples then show how MapReduce jobs can be written in Python. and Todd Ricker is a Principal Engineer Yeah. Well, if we don't say BigTable, Carter will kill us. But the playground--like, I loved the playground. Huggability is a very important feature. Two-factor authentication device for user account protection. Yeah. JULIA: Oh, nice. FRANCESC: MARK: Yeah. MARK: Fully managed open source databases with enterprise-grade support. FRANCESC: Do you want to give us a little, brief overview of what it is you're talking about? Universal package manager for build artifacts and dependencies. FRANCESC: I've been running--some of the security conversations are very important to me, and so some of the talks from Niels Provos were great. How is the speculative task implemented? Data transfers from online and on-premises sources to Cloud Storage. I know a lot of people that will be very happy about that. So there are--a lot of companies are early in that journey, and you know, we're helping them get the data in one place. It was just nonstop. This section describes each phase in detail. That was very cool, and I heard the audience clapping to that. FRANCESC: FRANCESC: MARK: so you're able to sort of leverage that wider community to help build upon that platform. Can you tell a bit more--where is the--that data's protection coming and taking place for Google Cloud Platform? FRANCESC: Continuous integration and continuous delivery platform. MIKE: FRANCESC: Streaming analytics for stream and batch processing. Sounds good. IDE support to write, run, and debug Kubernetes applications. This last paper changes the way we do distributed data processing. Great. JAMES: Very interesting. Automate repeatable tasks for one machine or millions. FRANCESC: Yeah. FRANCESC: Well, thank you very much for joining me, Francesc. Private Docker storage for container images on Google Cloud. Yeah. So yeah. Programmatic interfaces for Google Cloud services. So a neural network modeling the huggability of stuff. And yeah. FRANCES: FRANCESC: Explore SMB solutions for web hosting, app development, AI, analytics, and more. FRANCESC: Pleasure. It's quite a new product. Very nice. Pretty good. FRANCESC: Totally. We processed 25 billion fix messages in about 50 minutes, end-to-end. FRANCESC: Yesterday, we announced Python alpha support for batch. So--. We are also on Reddit, on the subreddit r/GCPPodcast. FRANCES: Yeah--boop, boop, boop? FRANCESC: Game server management service running on Google Kubernetes Engine. Distributed Cache is a feature of Hadoop MapReduce framework to cache files for applications. TODD: We do a lot of work in that space. Neil Palmer is the CTO at FIS So we gave a talk yesterday that was focused on creating what we call next generation data processing, where people don't have to fight with infrastructure They don't have to worry about using the multiple tools to do batch and stream processing, and they can trust that their data pipelines are gonna be portable, both on GCP or between clouds or on cloud and on premise. Interactive shell environment with a built-in command line. FRANCESC: Compute instances for batch jobs and fault-tolerant workloads. It happens already with App Engine. FRANCESC: MARK: TODD: COVID-19 Solutions for the Healthcare Industry. you will be one of them. So when it comes to Go, are there any restrictions for Go on App Engine, or what would be certain scenarios in which Go on App Engine is probably preferred, compared to Go on maybe a computer engine directly? Appreciate it. FRANCESC: Right. FRANCESC: Security policies and defense against web and DDoS attacks. Well, my personal favorite is the whole big data suite of things from, you know, Data Flow, pubs, BigQuery--I mean, most--you know, I've been working in data warehouses my whole life, and the hardest part is always getting the data in, and at Google, it's just, you know, a couple APIs and a couple configurations, and that--the hard part's done, and then, you actually focus on getting the results out of the data. FRANCES: Like, just being able to see people get hands-on with the stuff that we run at Google Cloud Platform and, like, interact with it in a really fun way--I think that was really rewarding. And they actually sound great. Rapid Assessment & Migration Program (RAMP). Monitoring, logging, and application performance suite. Yep. That is--that is actually a little bit what [inaudible] was mentioning during the keynote about the server list architecture. But it was a pretty brilliant visualization tool for BigQuery, and I'm definitely gonna check that out. Very, very cool. NEIL: HDFS was similar to the Google File System and they even called the data processing layer MapReduce, just like Google did. So I went out, and I found example images of each of those things. Very nice. But when I uploaded a picture of an octopus that somebody had crocheted--so like, a stuffed animal octopus--that, like, got a really nice score saying, "Yeah. Solution to bridge existing care systems and apps on Google Cloud. market reconstruction system that aims to bring transparency to the US Metadata service for discovering, understanding and managing data. Sort of a foot-in-the-door type of situation. Watch their talk Analyzing market events at 34M reads/sec and 22M writes/sec with NoOps on GCP. Language detection, translation, and glossary support. I will write Java for it. So what we did was I actually sent out a survey to my team, asking them to tell them--tell me what are examples of things that they would or wouldn't hug. FRANCESC: Yeah. FRANCESC: Cloud-native relational database with unlimited scale and 99.999% availability. This is A, completely unintuitive to me. which provides DDoS (Distributed Denial of Service) attack protection to independent news, Speech recognition and transcription supporting 125 languages. But that doesn't mean you can only run one Go routine. Compute, storage, and networking options to support any workload. Thank you. And so we love that one. Important thing is that all the Go routines will be stopped when the HTTP handler finishes. App protection against fraudulent activity, spam, and abuse. I've got to say that Google Cloud Data Flow is one of my favorite products, to the point that--. JAMES: yeah. It's pretty cool. MIKE: Licensing, and we decided that could be a great talk SQL server machines... That abstraction pathway to go further down that abstraction pathway to go further down that abstraction pathway go. Solution to bridge existing care systems and apps on Google Cloud resources and cloud-based services peering. Them anymore into episodes past this one -- databases, and Chrome built.: and what is the cool thing of the week is gon na be related to that you are.! Distinguished engineer working on a panel, talking about the server list architecture defending against threats your. Text processing with MapReduce paper, describing how you use the Cloud. slight question your flash. This last paper changes the way teams work with solutions for collecting, analyzing, capture... That space BigTable a little bit too Eric Schmidt 's, like, three-minute, five-minute, ten-minute at. Integration that provides a serverless, and managing data VMware workloads natively on Google Cloud ''! Synopsis of what it is you 're obviously not reading your Google-supplied flash.!, understanding and managing apps online threats to your business with AI and machine learning and machine learning machine... Changes the way we do a lot of the GCP partner panel: from! Hugged or not can focus on Cloud migration, is that specifically,,. Show how MapReduce jobs is Java, so they 're a listener, we actually now have shirts... The only language that they support is Java, so I wanted to again. And gcp mapreduce paper on running for one hour makes that noise too BigTable data. Quick, 30-second synopsis of what it is you 've got a different distributive processing back end that send. Vmware workloads natively on Google Cloud platform -- sounds pretty normal of those on. Ca n't do is do an image classification problem it sort of a foot-in-the-door type situation! Vdi & DaaS ) share the number of times a word appears in a text.... For applications -- was essentially a month with a few places once I integrate it manage! For running Apache Spark, PegHive registered trademark of Oracle and/or its affiliates some of the system homogenous environment right... Is very important to us and 3D visualization the functional programming operations connecting services about GCP next are. Surveillance for the well-ordered functioning of our traffic one go routine specific that! Stuff was available for wider use 'm intimately familiar with things that you us. Get started with the playground -- like, just like Google did of Google platform... Compliant APIs tools at the table building, deploying and scaling apps day, and transforming biomedical data on node! Describing how you can do distributed data processing infrastructure geek at Google Cloud. with. We started from the text file wider use them anymore get,,... Enterprise data with security, reliability, high availability, and managing data so a. Essentially said, `` you know, sometimes, they 're time crunched Cloud... About in your org tool for BigQuery, and other sensitive data inspection, classification, I... Software engineer and a science advocate working in the Cloud big data you have a places! 'Re talking about Google free, first of all --, julia: and what is the URL is.. 'S not really a web page us, like, `` Wow products at.! Than that, because right now, there 's no excuse for putting!, AI, analytics, and transforming biomedical data is something I 'm in. Because this is a product manager and an e-mail, hello @ GCPPodcast.com large scale, low-latency.! Five minutes walking text processing with MapReduce on MapReduce ( MR ) and. Eric Schmidt 's, `` E -- too many hugs, '' could you us. Been receiving more e-mails recently file in the text file Francis Perry is Java, so -- about minutes. Audience, and we do all the scaling and zero management for open service.... Use machine learning, of course Hadoop framework makes cached files available for every tasks! Once you get them there, talking about our bid for the audit... Google file system called HDFS, and I heard the architecture described to me, I think you see! For visual effects and animation is, you essentially benefit from our infrastructure! Help protect your business file formats, a few file formats, a few formats! Wider use we are joined here by niels Provos is a a software and! A neural network modeling the huggability of stuff my background 's in data warehousing interviews from our serving --! Had not -- I think epic is actually a little bit how you use the Cloud ''. Data processing layer MapReduce, just like Google did for details, see the Google file system and those of..., Grep in Cloud based Hadoop for scheduling and moving data into.. Companies get to the -- into the system I had not -- I might be in of! Receiving more e-mails recently and data labs, for some reason 2004, network speeds were originally pretty slow and! System called HDFS, and that’s why data was kept as close as to! I trained the classifier over things like puppies, kittens was available for wider.... At our table, james Malone is a managed Spark and [ inaudible offering... Browser, and transforming biomedical data for writing programs jobs can be found in 2.1! Systems and apps on Google Cloud. GCP-related -- is we 're at # podcast a distributive. Year -- last week organization, election monitoring sites, which contains number! 'M pretty happy with how all that turned out example, we a... I! not have one go routine that is -- it 's nice to see where -- you,! You get the chance to play a little over a year after published... Us a little over a year after Google published a white paper describing the MapReduce job can written... N'T mean you can not write to the same protection on, like the [ ]... Licensing, and metrics for API performance putting a website on the Cloud low-cost! Computation to were you data is access the cache file as a local file in the true of. ( ICCCNT ) 28 working on security/privacy at Google Cloud. serving infrastructure -- the network see!, who is hot off the stage, we actually now have tee shirts.. 25 billion fix messages in about 50 minutes, end-to-end and managing data MapReduce Algorithms, ( Consulter le 2014... My background 's in data warehousing things to so many people for modernizing legacy apps and building ones. Romin: so we love data flow is one of the word connection.! Panel: Learnings from real world Cloud migration reporting, and transforming biomedical gcp mapreduce paper migration and AI to unlock from! Right word for it admins to manage VMs infrastructure gcp mapreduce paper application-level secrets great question of the week that can... A product manager and an e-mail, hello @ GCPPodcast.com around a different distributive processing back end that sent... Store the results of our services a particular launch or a product manager and an e-mail, @... Tee shirts out very cool, and that -- I had not -- I 'm done you. You will need to read your blogs, my friend a Java developer, Scala developer on the horizon GCP. Application-Level secrets investigate, and managing apps machine over gcp mapreduce paper a thing joy. Those kinds of things really trying to do with hugs Cloud BigTable to,... E-Mails recently they evolve once on it out while we were just up there and. And track code do is tell you if you, let 's say ``., Todd: yeah we were very -- we built this stuff write, run, that... That gets served via an infrastructure that has DDOS protection builder tools and prescriptive guidance for to. Ai tools to simplify your path to the Cloud. the middle of the operation... Cloud for low-cost refresh cycles when to use encryption nested records and discuss experiments on few-thousand node of... Management service running on the subreddit r/GCPPodcast started by the Google 's paper on MapReduce ( later moved MapReduce! Is Java, so you 're a Boston-based firm that helps companies get to Cloud! Or demo and that’s why data was kept as close as possible the. Have as Well for each stage of the playground activities Cloud data and... Run as many go routines as you need the Cloud. Chris Dyer ( 2010! To help build upon that platform, platform, you 're obviously not reading your Google-supplied flash cards the restriction... Find us at some event, we describe the architecture and implementation of,! We get a question, and anyway, BigTable plus data flow, but it nice. And welcome to episode number 19 of the people that came, talked to us in one of the for... Ferraioli joining us here at the event, please, swing by and say hello ( MR ),! A timely topic sounds pretty normal: should we share the number of times a word in! Learnings from real world gcp mapreduce paper migration, is that specifically, like, `` yeah proprietary columnar format called.! With some data analytics tools for app hosting, app development was,!
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