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StarTree
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Добавлен 28 мар 2019
StarTree, powered by Apache Pinot: real-time analytics for user-facing apps. Discover the latest technical developments, trends, and use cases for real-time analytics straight from our engineers and open source developers, and your fellow industry colleagues and practitioners.
StarTree is uniquely positioned to bring you fast, reliable and fresh perspectives on the shift from batch to real-time analytics, and from internal-facing to user-facing applications. Subscribe to our channel if you are designing systems that need to scale to petabytes of information, millions of users, and to provide results at sub-second scale latencies.
StarTree is uniquely positioned to bring you fast, reliable and fresh perspectives on the shift from batch to real-time analytics, and from internal-facing to user-facing applications. Subscribe to our channel if you are designing systems that need to scale to petabytes of information, millions of users, and to provide results at sub-second scale latencies.
What's New In Apache Pinot 1.2.0?
Join Viktor Gamov (Head of Developer Advocacy, StarTree) over the rooftops of Istanbul, walking you through the updates coming to Apache Pinot in its 1.2 release. Read the detailed blog at: startree.ai/blog/highlighting-innovation-in-apache-pinot-1-2
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► Learn about Apache Pinot: dev.startree.ai
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Site: startree.ai
ABOUT STARTREE
StarTree, powered by Apache Pinot: real-time analytics for user-facing apps. Discover the latest technical develo...
Join: stree.ai/slack | Sub: stree.ai/sub |
LEARN MORE
► Learn about Apache Pinot: dev.startree.ai
CONNECT
Subscribe on RUclips: ruclips.net/user/startreedata
Community Slack: stree.ai/slack
Twitter: startreedata
Linkedin: www.linkedin.com/company/startreedata
GitHub: github.com/startreedata
Site: startree.ai
ABOUT STARTREE
StarTree, powered by Apache Pinot: real-time analytics for user-facing apps. Discover the latest technical develo...
Просмотров: 245
Видео
StarTree Cloud & Apache Pinot at Amberdata
Просмотров 190Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | LEARN MORE ► Learn about Apache Pinot: dev.startree.ai CONNECT Subscribe on RUclips: ruclips.net/user/startreedata Community Slack: stree.ai/slack Twitter: startreedata Linkedin: www.linkedin.com/company/startreedata GitHub: github.com/startreedata Site: startree.ai ABOUT STARTREE StarTree, powered by Apache Pinot: real-time analytics for u...
How to Leverage Minions | Apache Pinot 201
Просмотров 107Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Explore the role of minions in Apache Pinot with Viktor Gamov in one of our final episodes of Apache Pinot 201. Far from animated characters, these minions are crucial background workers that optimize the performance of the Pinot cluster by handling tasks like data ingestion, purging, and formatting. Discover how these powerful components help maintain...
How to Leverage Upserts | Apache Pinot 201
Просмотров 70Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Dive deeper into our Advanced Apache Pinot series as Viktor explores the powerful feature of upserts. Upserts, a blend of update and insert operations, allow for seamless modifications to existing records or the addition of new ones within your Apache Pinot database. This functionality is crucial for maintaining data accuracy and freshness, especially ...
Introduction | Apache Pinot 201
Просмотров 377Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Welcome to Apache Pinot 201! Join Viktor Gamov as he guides you through advanced Apache Pinot topics, that builds upon our Apache Pinot 101 series. Starting with a solid foundation and progressing to sophisticated features like data ingestion techniques and performance optimization, this 11-part series is designed to enhance your skills and empower you...
How to Ingest Data | Apache Pinot 201
Просмотров 152Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Dive back into our Advanced Apache Pinot series with Viktor Gamov as he explores the critical world of data ingestion. Follow along as he guides you through various ingestion methods-batch, streaming, and hybrid-essential for effectively utilizing Pinot. This episode is full of practical tips and detailed steps for setting up and managing your data ing...
Use Cases That Work for Pinot | Apache Pinot 201
Просмотров 114Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | In this final module of our Pinot 201 course, Viktor delves into how Pinot thrives in environments demanding real-time analytics, from social media platforms to financial fraud detection. Discover how companies like LinkedIn leverage Pinot for user activity monitoring and how it empowers e-commerce sites to offer personalized shopping experiences. Whet...
How to Configure Tenants | Apache Pinot 201
Просмотров 135Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Today, we're tackling a crucial element of your Apache Pinot setup: configuring tenants. Discover how tenants function as dedicated spaces within your Pinot cluster, enabling you to manage different data sets and workloads effectively. Whether you're isolating resources for multiple teams or applications, this session provides step-by-step guidance on ...
How to Leverage Indexes | Apache Pinot 201
Просмотров 97Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Welcome back! In today's module, Viktor focuses on the transformative power of indexing to accelerate data retrieval and query efficiency. Viktor introduces a variety of indexes that serve as the "secret sauce" to supercharging your queries, from basic forward indexes to more specialized structures like star tree and geospatial indexes. This session is...
How to Query Data | Apache Pinot 201
Просмотров 126Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Join Viktor Gamov as he delves into the essentials of querying data using SQL. In this session, Viktor breaks down the functionalities and applications of both single stage and multi stage query engines within Apache Pinot. Whether you're handling simple queries or complex datasets, this episode will equip you with the knowledge to choose and utilize t...
How to Transform Data During Ingestion | Apache Pinot 201
Просмотров 58Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | In this module of our Apache Pinot 201 course, Viktor delves into the dynamic process of data transformation during ingestion. This crucial step allows you to refine and enhance raw data into insightful, actionable information directly as it enters your Apache Pinot system. Viktor will demonstrate how to implement Groovy-based and built-in functions to...
How to Create a Pinot Cluster | Apache Pinot 201
Просмотров 169Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | Welcome back to our Advanced Apache Pinot series with Viktor Gamov! In this session, we dive into the essential steps for setting up your Apache Pinot cluster, whether for development or production. Explore the flexibility of running Pinot on various platforms-from local machines using Docker Compose to cloud services-and learn how to manage data with ...
How to Create Schemas, Tables, and Segments | Apache Pinot 201
Просмотров 147Месяц назад
Join: stree.ai/slack | Sub: stree.ai/sub | In this module of Apache Pinot 201, we delve into the crucial task of configuring tables, an essential backbone of any database system. Viktor will guide you through creating schemas and understanding the different table types available in Pinot-offline, real-time, and hybrid-providing you with the knowledge to structure and store your data effectively...
Meetup: Enhanced Gamer Experience with Confluent, StarTree, and AWS
Просмотров 862 месяца назад
Meetup: Enhanced Gamer Experience with Confluent, StarTree, and AWS
Meetup: High Availability and Disaster Recovery (David Brown, StarTree)
Просмотров 593 месяца назад
Meetup: High Availability and Disaster Recovery (David Brown, StarTree)
On to the Next Chapter ft. Tim Berglund | Ep. 54 | Real-Time Analytics Podcast
Просмотров 3053 месяца назад
On to the Next Chapter ft. Tim Berglund | Ep. 54 | Real-Time Analytics Podcast
WebAssembly in Redpanda with Christina Lin | Ep. 53 | Real-Time Analytics Podcast
Просмотров 1404 месяца назад
WebAssembly in Redpanda with Christina Lin | Ep. 53 | Real-Time Analytics Podcast
WarpStream Unveiled: Cloud-Native Kafka Redefined with Richard Artoul | Ep. 52 | RTA Podcast
Просмотров 2854 месяца назад
WarpStream Unveiled: Cloud-Native Kafka Redefined with Richard Artoul | Ep. 52 | RTA Podcast
Keynote: Sanjeev Mohan (SanjMo) The Taxonomy of the Real-Time Analytics Landscape | RTA Summit '24
Просмотров 4684 месяца назад
Keynote: Sanjeev Mohan (SanjMo) The Taxonomy of the Real-Time Analytics Landscape | RTA Summit '24
Keynote: Jay Kreps (CEO, Confluent) Unifying the Operational & Analytical Worlds | RTA Summit '24
Просмотров 9934 месяца назад
Keynote: Jay Kreps (CEO, Confluent) Unifying the Operational & Analytical Worlds | RTA Summit '24
Panel: Mingmin (Uber), Kranti (Dialpad), Shaun (Confluent), Dipti (Microsoft) | RTA Summit '24
Просмотров 3614 месяца назад
Panel: Mingmin (Uber), Kranti (Dialpad), Shaun (Confluent), Dipti (Microsoft) | RTA Summit '24
Keynote: Kishore Gopalakrishna (CEO, StarTree) Mission Critical Data Can't Wait | RTA Summit '24
Просмотров 1,1 тыс.4 месяца назад
Keynote: Kishore Gopalakrishna (CEO, StarTree) Mission Critical Data Can't Wait | RTA Summit '24
Introducing StarTree Cloud's Free Tier
Просмотров 2804 месяца назад
Introducing StarTree Cloud's Free Tier
Testcontainers and Apache Pinot with Tim Veil | Ep. 51 | Real-Time Analytics Podcast
Просмотров 2004 месяца назад
Testcontainers and Apache Pinot with Tim Veil | Ep. 51 | Real-Time Analytics Podcast
Analytics Goes Real-Time with Apache Pinot | Ep. 13 | Keyboard and Quill Podcast
Просмотров 1094 месяца назад
Analytics Goes Real-Time with Apache Pinot | Ep. 13 | Keyboard and Quill Podcast
Data Goes Real-Time with Apache Kafka | Ep. 12 | Keyboard and Quill Podcast
Просмотров 1474 месяца назад
Data Goes Real-Time with Apache Kafka | Ep. 12 | Keyboard and Quill Podcast
From Small Data to Big Data | Ep. 11 | Keyboard and Quill Podcast
Просмотров 544 месяца назад
From Small Data to Big Data | Ep. 11 | Keyboard and Quill Podcast
From Early Statistics to Early Analytics | Ep. 10 | Keyboard and Quill Podcast
Просмотров 414 месяца назад
From Early Statistics to Early Analytics | Ep. 10 | Keyboard and Quill Podcast
The History of Food Delivery with Rachel Laudan | Ep. 50 | Real-Time Analytics Podcast
Просмотров 1094 месяца назад
The History of Food Delivery with Rachel Laudan | Ep. 50 | Real-Time Analytics Podcast
Good presentor, but I would prefer to read this.
Neither statefulsets or pods get ready 1/1
I never get the same results of minute 17:16
Pretty clear explanation !! Thankyou.
manyt rdbms like sqlserver columnar indesing also does the same thing
Hey! It would be great to see how it compares to in-memory data grids (GridGain/Ignite, Gemfire/Geode, Coherence) that provide some SQL-ish capabilities and are still commonly used for similar cases - muliti-QPS realtime analytics.
how to choose schema for table when creating table in the UI? after I create the schema in the UI then try to add realtime table there is no option so select the schema for the table.
Great Talk
This is the greatest intro song of all time.
Half of the stuff is wrong.
super cool visualization at the end for the star-tree index, really helped in understanding what that specific index is all about.
Is there no way to do table creation using a sql/hive-like statements/commands/scripts? My use case would be to use something similar to tables already created in hive...
I guess their comany StarTree is a Pinot service provider. Hence, to commoditize & sell their offering they would like to be baised towards Pinto😂 I mean nothing wrong in it from business perspective but open source fans will not love this. I don't think CliclHouse is that bad. Even in my company, we intentionally try to overpower serviceNow as we are serviceNow partners & service provider. Although there are other cheaper tools available in market to small use cases😂😂😂😂
It would be great if there is a cost calculator between those 4 options with few basic inputs like users, data volume, velocity etc. Another concern is ability to find resources.
When are you planning to release the grafana plugin ?
What about a spend insight dashboard?
Loving Flink so far and listening to Robert makes me realise why- it's so important to have a deep grasp of prior art and fundamentals. The insight that if you start with a streaming foundation you can implement batch over the top is so important. So often I see tools and systems try to add streaming later, and it just doesn't work. Whereas if you start pipelined, everything else is relatively easy. The hybrid source thing is so great, and I'm very happy never to have to write the plumbing for that myself ever again. Great interview, both of you.
I want to bring to your attention that your freelancers and distributors have been reported for using your advertising product to scam people worldwide. I urge you to take immediate action to ensure that your freelancers and/or distributors repay the money they have scammed from victims, and to promptly suspend the licenses of any scammers once you receive a report of their actions from the victims.
Amazing that this has no comments and only 70 ish views while there "data" and "AI" blasting from left and right 24/7
Hey, are you the head of a scamming group?
You’re so beautiful tho😊
I came across a combined task negative number and I can't find a solution what can be done
Hello, the combined task package consists of 2-3 common tasks. The commission for combined task packages is 3 times that of ordinary tasks. A combined task package consisting of 2 ordinary tasks means there will be one negative number, and a combined task package consisting of 3 ordinary tasks will have two negative numbers. This is your current last combined task, and you can cash it out on your own once completed.
They just don't know how clickhouse works
Tell us more!
I'm a bit late to the Real-Time Analytics Podcast but I've enjoyed the episodes I've gotten to listen to over the last few months. Best of luck on your next adventure, Tim!
What sort of latency timing are we seeing from event ingestion at the start of the pipe to dashboard calculation update?
Thanks Tim sorry to see you go once again. Hope the hiatus is short but sweet. Looking forward to what’s next. Keep up the great work in advocating and educating us all. ❤
Redpanda is doing some really cool things. Agree with you Tim in that it blew my mind to hear the embedding use case by sending voice notes as messages and creating embedding as part of the WASM library. Great architecture pattern to have in the toolbox.
Did they get a reverse printed tree specifically for this video!?
Tim - The last 3 episodes (51, 52 and 53) were absolutely fantastic to understand the cutting edge of innovation real time data analytics ! Great job !
great
tim rocks 💥
baised
Awesome 🎉
What a fantastic show - such a pity that this has not gone viral yet. I'd love to have my kids listen to this actually, great history lessons...
to use Confluent and have transformation needs, the points mentioned are very interesting. Using Flink vs Kafka Stream, doing stateful VS stateless, are questions that we ask ourselves a lot in the company.
I just explained 5.25" and 3.5" floppies to a kid yesterday.
There aren't any proper video tutorials of Apache Pinot available, but if there are any, it would be a big help.
Luckily, we do have quite a few Pinot tutorials and how-to's! Here are a few resources: We have a full Apache Pinot 101 course that breaks down all the components of Pinot: ruclips.net/video/LMb-OK_RExE/видео.html We also have a handful of StarTree Recipes that walk through how to use Pinot in real life examples: ruclips.net/video/6KuqCD7sVfQ/видео.html We hope these videos are useful!
Thank you to all of the 70 Apache Pinot committers! Vector indexing is an awesome new feature.
Can't we simply utilize the API to update the table and schema?
code not working
1962 was also the first year of the Bell 103 modem. 300 bauds of POWAH!
Fun fact: the 1962 Tornados song "Telstar" was named after that first communications satellite.
Telstar!
sinking it*
Quine is so cool. Streaming graphs lend themselves to many use cases. From cybersecurity and networking to social media analytics.
A lot of use cases indeed, i already point people to it
Been loving this series so far such unspoken truths. Provide we can trust the source of truth. Great job had to comment. Can’t wait for the Pinot part.😊 it’s a journey through realtime. Love factual history
I was able to test this method via refering the pinot docummentation related to unnest. I believe if this is the same concept it misses certains steps. Though my question is does this feature apply to only JSON source data in kafka or can i apply this feature to other data formats like protubuf which is the format in my kafka topic.