This document summarizes Presto, an analytics engine used at Facebook. It provides ad-hoc querying for data warehouses and batch processing. It is used for analytics across Facebook's data warehouses and specialized data stores. The document outlines Presto's architecture, deployment, usage statistics, features, and enhancements made for specific Facebook use cases including user-facing products, large datasets, and reliable data loading.
Presto: Distributed SQL on Anything - Strata Hadoop 2017 San Jose, CAkbajda
Teradata joined the Presto community in 2015 and is now a leading contributor to this open source SQL engine, originally created by Facebook. The project has a rapidly growing community of users, including Airbnb, FINRA, Netflix, Twitter, and Uber. Kamil Bajda-Pawlikowski explores the key architectural components that allow querying variety of data sources and make Presto uniquely position to be applied in both Hadoop and Cloud use cases. Along the way, Kamil covers Teradata’s recent enhancements in query performance, security integrations, and ANSI SQL coverage and shares the roadmap for 2017 and beyond.
One of the key differences between Presto and Hive, also a crucial functional requirement Facebook made when launching this new SQL engine project, was to have the opportunity to query different kinds of data sources via a uniform ANSI SQL interface.
Presto, an open source distributed analytical SQL engine, implements this with it’s connector architecture, creating an abstraction layer for anything that can be expressed as in a row-like format, ranging from MySQL tables, HDFS, Amazon S3 to NoSQL stores, Kafka streams and proprietary data sources. Presto connector SPI allows anyone to implement a Presto connector and benefit from the capabilities of the Presto SQL engine, enabling them to join data from various sources within a single SQL query.
Presto: Distributed SQL on Anything - Strata Hadoop 2017 San Jose, CAkbajda
Teradata joined the Presto community in 2015 and is now a leading contributor to this open source SQL engine, originally created by Facebook. The project has a rapidly growing community of users, including Airbnb, FINRA, Netflix, Twitter, and Uber. Kamil Bajda-Pawlikowski explores the key architectural components that allow querying variety of data sources and make Presto uniquely position to be applied in both Hadoop and Cloud use cases. Along the way, Kamil covers Teradata’s recent enhancements in query performance, security integrations, and ANSI SQL coverage and shares the roadmap for 2017 and beyond.
One of the key differences between Presto and Hive, also a crucial functional requirement Facebook made when launching this new SQL engine project, was to have the opportunity to query different kinds of data sources via a uniform ANSI SQL interface.
Presto, an open source distributed analytical SQL engine, implements this with it’s connector architecture, creating an abstraction layer for anything that can be expressed as in a row-like format, ranging from MySQL tables, HDFS, Amazon S3 to NoSQL stores, Kafka streams and proprietary data sources. Presto connector SPI allows anyone to implement a Presto connector and benefit from the capabilities of the Presto SQL engine, enabling them to join data from various sources within a single SQL query.
Presto, an open source distributed SQL engine originally built at Facebook, has a rapidly growing community of developers and users. In this talk, speakers from both Facebook and Teradata, will discuss technical details of some of the recent developments such as integration with Hadoop ecosystem (YARN/Slider and Ambari), security features (Kerberos), enabling BI tools via JDBC/ODBC drivers, new connectors (Redis, MongoDB) and storage engines (Raptor) as well as improvements in performance and ANSI SQL coverage. In addition, we will present a few use cases and major new users that leverage interactive SQL capabilities Presto offers. Finally, we will present our roadmap for the next year.
See the video at https://youtu.be/wMy3LXuTb0U
Boston Hadoop Meetup: Presto for the EnterpriseMatt Fuller
Presentation Title: Presto for the Enterprise
Presenter(s): Matt Fuller and Kamil Bajda-Pawlikowski
Company: Teradata Center for Hadoop
Short Description:
Teradata will provide a technical overview and demo of Presto, focusing on Presto's architecture and Teradata's contributions to the project and community. Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. Originally developed by Facebook, Teradata now joins Facebook as the second largest contributor to the open source project. Come join us and learn more about Presto. And how you can join the Presto community.
Hello, Enterprise! Meet Presto. (Presto Boston Meetup 10062015)Matt Fuller
Teradata has been hard at work on Presto, and we want to share with you what we've done so far and our roadmap going forward. From presto-admin, a tool for installing and administering Presto, to YARN/Ambari support, to fully certified JDBC and ODBC drivers, we are committed to making Presto the best, most enterprise-ready SQL-on Hadoop solution out there.
Tempto is a product test framework that allows developers to write and execute tests for SQL databases running on Hadoop. Individual test requirements such as data generation, HDFS file copy/storage of generated data and schema creation are expressed declaratively and are automatically fulfilled by the framework. Developers can write tests using Java (using a TestNG like paradigm and AssertJ style assertion) or by providing query files with expected results. We will show how we use it for presto product tests.
Benchto is a benchmark framework that provides an easy and manageable way to define, run and analyze macro benchmarks in clustered environment. Understanding behavior of distributed systems is hard and requires good visibility intostate of the cluster and internals of tested system. This project was developed for repeatable benchmarking ofHadoop SQL engines, most importantly Presto.
Presto @ Treasure Data - Presto Meetup Boston 2015Taro L. Saito
Treasure Data simplifies event analytics for the complex digital
world. Our customers send us 1,000,000 events per second and issue 30,000+ Presto queries everyday to understand their customers better. One of the challenges is designing a cloud database with zero downtime to support a global customer base. We have achieved this goal by developing several open-source technologies; Fluentd and Embulk enable seamless log collection from stream/batch sources, and with MessagePack we can provide an extensible columnar store that accommodates future schema changes. Finally, Presto allows us to serve a wide variety of data processing our customers perform on our service. In this talk, I will present an overview of our system, and how our customers keep using Presto while collecting and extending their data set.
Lessons learned while taking Presto from alpha to production at Twitter. Presented at the Presto meetup at Facebook on 2015.03.22.
Video: https://www.facebook.com/prestodb/videos/531276353732033/
Presentation on Presto (http://prestodb.io) basics, design and Teradata's open source involvement. Presented on Sept 24th 2015 by Wojciech Biela and Łukasz Osipiuk at the #20 Warsaw Hadoop User Group meetup http://www.meetup.com/warsaw-hug/events/224872317
Presto, an open source distributed SQL engine originally built at Facebook, has a rapidly growing community of developers and users. In this talk, speakers from both Facebook and Teradata, will discuss technical details of some of the recent developments such as integration with Hadoop ecosystem (YARN/Slider and Ambari), security features (Kerberos), enabling BI tools via JDBC/ODBC drivers, new connectors (Redis, MongoDB) and storage engines (Raptor) as well as improvements in performance and ANSI SQL coverage. In addition, we will present a few use cases and major new users that leverage interactive SQL capabilities Presto offers. Finally, we will present our roadmap for the next year.
See the video at https://youtu.be/wMy3LXuTb0U
Boston Hadoop Meetup: Presto for the EnterpriseMatt Fuller
Presentation Title: Presto for the Enterprise
Presenter(s): Matt Fuller and Kamil Bajda-Pawlikowski
Company: Teradata Center for Hadoop
Short Description:
Teradata will provide a technical overview and demo of Presto, focusing on Presto's architecture and Teradata's contributions to the project and community. Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. Originally developed by Facebook, Teradata now joins Facebook as the second largest contributor to the open source project. Come join us and learn more about Presto. And how you can join the Presto community.
Hello, Enterprise! Meet Presto. (Presto Boston Meetup 10062015)Matt Fuller
Teradata has been hard at work on Presto, and we want to share with you what we've done so far and our roadmap going forward. From presto-admin, a tool for installing and administering Presto, to YARN/Ambari support, to fully certified JDBC and ODBC drivers, we are committed to making Presto the best, most enterprise-ready SQL-on Hadoop solution out there.
Tempto is a product test framework that allows developers to write and execute tests for SQL databases running on Hadoop. Individual test requirements such as data generation, HDFS file copy/storage of generated data and schema creation are expressed declaratively and are automatically fulfilled by the framework. Developers can write tests using Java (using a TestNG like paradigm and AssertJ style assertion) or by providing query files with expected results. We will show how we use it for presto product tests.
Benchto is a benchmark framework that provides an easy and manageable way to define, run and analyze macro benchmarks in clustered environment. Understanding behavior of distributed systems is hard and requires good visibility intostate of the cluster and internals of tested system. This project was developed for repeatable benchmarking ofHadoop SQL engines, most importantly Presto.
Presto @ Treasure Data - Presto Meetup Boston 2015Taro L. Saito
Treasure Data simplifies event analytics for the complex digital
world. Our customers send us 1,000,000 events per second and issue 30,000+ Presto queries everyday to understand their customers better. One of the challenges is designing a cloud database with zero downtime to support a global customer base. We have achieved this goal by developing several open-source technologies; Fluentd and Embulk enable seamless log collection from stream/batch sources, and with MessagePack we can provide an extensible columnar store that accommodates future schema changes. Finally, Presto allows us to serve a wide variety of data processing our customers perform on our service. In this talk, I will present an overview of our system, and how our customers keep using Presto while collecting and extending their data set.
Lessons learned while taking Presto from alpha to production at Twitter. Presented at the Presto meetup at Facebook on 2015.03.22.
Video: https://www.facebook.com/prestodb/videos/531276353732033/
Presentation on Presto (http://prestodb.io) basics, design and Teradata's open source involvement. Presented on Sept 24th 2015 by Wojciech Biela and Łukasz Osipiuk at the #20 Warsaw Hadoop User Group meetup http://www.meetup.com/warsaw-hug/events/224872317
Boost the Performance of SharePoint Today!Brian Culver
Is your farm struggling to server your organization? How long is it taking between page requests? Where is your bottleneck in your farm? Is your SQL Server tuned properly? Worried about upgrading due to poor performance? We will look at various tools for analyzing and measuring performance of your farm. We will look at simple SharePoint and IIS configuration options to instantly improve performance. I will discuss advanced approaches for analyzing, measuring and implementing optimizations in your farm as well as Performance Improvements in SharePoint 2013.
Transitioning From SQL Server to MySQL - Presentation from Percona Live 2016Dylan Butler
What if you were asked to support a database platform that you had never worked with before? First you would probably say no, but after you lost that fight, then what? That is exactly how I came to support MySQL. Over the last year my team has worked to learn MySQL, architect a production environment, and figure out how to support it alongside our other platforms (Microsoft SQL Server and Oracle). Along the way, I have also come to appreciate the unique offering of this platform and see it as an important part of our environment going forward.
To make things even more challenging, our first MySQL databases were the backend for a critical, web based application that needed to be highly available across multiple data centers. This meant that we did not have the luxury of standing up a simpler environment to start with and building confidence there. Our final architecture ended up using a five node Percona XtraDB Cluster spread across three data centers.
This session will focus on lessons learned along the way, as well as challenges related to supporting more than one database platforms. It should be interesting to anyone who is new to MySQL, anyone who is being asked to support more than one database platform, or anyone who wants to see how an outsider views the platform.
Adding Support for Networking and Web Technologies to an Embedded SystemJohn Efstathiades
These are the slides for a presentation we gave at Device Developer Conference 2014 in the UK. The presentation discusses the work done, experiences, and lessons learnt from adding an open source TCP/IP network stack and web server to an existing industrial control system running on an ARM Cortex M3-based processor from TI.
The presentation covers the following:
· Integrating the network stack into the existing software base
· Configuring and using the network stack and web server
· Adding support for HTTP basic authentication to restrict user access
· Using HTTP to remotely access the target system and retrieve operational data
· Debugging hints and tips
· Pitfalls to avoid and other lessons learnt
(BDT403) Best Practices for Building Real-time Streaming Applications with Am...Amazon Web Services
Amazon Kinesis is a fully managed, cloud-based service for real-time data processing over large, distributed data streams. Customers who use Amazon Kinesis can continuously capture and process real-time data such as website clickstreams, financial transactions, social media feeds, IT logs, location-tracking events, and more. In this session, we first focus on building a scalable, durable streaming data ingest workflow, from data producers like mobile devices, servers, or even a web browser, using the right tool for the right job. Then, we cover code design that minimizes duplicates and achieves exactly-once processing semantics in your elastic stream-processing application, built with the Kinesis Client Library. Attend this session to learn best practices for building a real-time streaming data architecture with Amazon Kinesis, and get answers to technical questions frequently asked by those starting to process streaming events.
Elastic Search Meetup Special - Yann Cluchey, Cogenta Internet World
The Marketplace - June 18th, 17:00-18:00
Learn from Cogenta about how they are using Elasticsearch to deliver real-time data insights to their business.
Similar to Presto at Facebook - Presto Meetup @ Boston (10/6/2015) (20)
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Why React Native as a Strategic Advantage for Startup Innovation.pdfayushiqss
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But what makes React Native so popular for mobile application development? It offers excellent cross-platform capabilities among other benefits. This way, with React Native, developers can write code once and run it on both iOS and Android devices thus saving time and resources leading to shorter development cycles hence faster time-to-market for your app.
Let’s take the example of a startup, which wanted to release their app on both iOS and Android at once. Through the use of React Native they managed to create an app and bring it into the market within a very short period. This helped them gain an advantage over their competitors because they had access to a large user base who were able to generate revenue quickly for them.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
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Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
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Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
2. Presto @ Facebook
• Ad-hoc/interactive queries for warehouse
• Batch processing for warehouse
• Analytics for user-facing products
• Analytics over various specialized stores
6. Stats
• 1000s of internal daily active users
• Millions of queries each month
• Scan PBs of data every day
• Process trillions of rows every day
• 10s of concurrent queries
15. Requirements
• Large data sets
• Seconds to minutes latency
• Predictable performance
• 5-15 minute load latency
• Reliable data loads (no duplicates, no missing data)
• 10s of concurrent queries
18. Additional Features
• Full featured and atomic DDL
• Table statistics
• Tiered storage
• Atomic data loads
• Physical organization
19. Table Statistics
• Table is divided into shards
• Each shard is stored in a separate replication unit (i.e., file)
• Typically 1 to 10 million rows
• Node assignment and stats stored in MySQL
20. Table Schema in MySQL
Tables
id name
1 orders
2 line_items
3 parts
table1 shards
uuid nodes c1_min c1_max c2_min c2_max c3_min c3_max
43a5 A 30 90 cat dog 2014 2014
6701 C 34 45 apple banana 2005 2015
9c0f A,D 25 26 cheese cracker 1982 1994
df31 B 23 71 tiger zebra 1999 2006
22. Tiered Storage
• One copy in local, expensive, flash
• Backup copy in cheap durable backup tier
• Currently Gluster internally, but can be anything durable
• Only assumes GET and PUT with client assigned ID methods
23. Atomic Data Loads
• Import data periodically from streaming event system
• Internally a Scribe based system similar to Kafka or Kinesis
• Provides continuation tokens
• Loads performed using SQL
24. Atomic Data Loads
INSERT INTO target
SELECT *
FROM source_stream
WHERE token BETWEEN ${last_token} AND ${next_token}
25. Loader Process
1. Record new job with “now” token in MySQL
2. Execute INSERT from last committed token to “now” token with
external batch id
3. Wait for INSERT to commit (check external batch status)
4. Record job complete
5. Repeat
26. Failure Recovery
• Loader crash
• Check status of jobs using external batch id
• INSERT hang
• Cancel query and rollback job (verify status to avoid race)
• Duplicate loader processes
• Process guarantees only one job can complete
• Monitor for lack of progress (catches no loaders also)
30. Background Organization
• Compaction
• Balance data
• Eager data recover (from backup)
• Garbage collection
• Junk created by compaction, delete, balance, recovery
31. Future Use Cases
• Hot data cache for Hadoop data
• 0-N local copies of “backup” tier
• Query results cache
• Raw, not rolled-up, data store for Sharded MySql customers
• Materialized view store
