タグ検索の該当結果が少ないため、タイトル検索結果を表示しています。
Rails 6.1: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more!
Rails 6.1: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more! Rails 6.1 has been released and wow does it have a lot of great stuff! We’ve been hard at work these past few months implementing improvements to multiple databases, adding support for destroying associations in jobs instead of in-memory, turning errors into objects,
GitHub - microsoft/garnet: Garnet is a remote cache-store from Microsoft Research that offers strong performance (throughput and latency), scalability, storage, recovery, cluster sharding, key migration, and replication features. Garnet can work with exis
Garnet is a new remote cache-store from Microsoft Research, that offers several unique benefits: Garnet adopts the popular RESP wire protocol as a starting point, which makes it possible to use Garnet from unmodified Redis clients available in most programming languages of today, such as StackExchange.Redis in C#. Garnet offers much better throughput and scalability with many client connections an
Rails 6.1 RC1: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more!
Rails 6.1 RC1: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more! The first release candidate for Rails 6.1 has been released and wow does it have a lot of great stuff! We’ve been hard at work these past few months implementing improvements to multiple databases, adding support for destroying associations in jobs instead of in-m
GitHub - postgresml/pgcat: PostgreSQL pooler with sharding, load balancing and failover support.
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
Rails 6.1 RC2: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more!
Rails 6.1 RC2: Horizontal Sharding, Multi-DB Improvements, Strict Loading, Destroy Associations in Background, Error Objects, and more! The second release candidate for Rails 6.1 has been released and brings a more robust experience for those already trying this version. We’ve been hard at work tweaking and adjusting the nobs to have so using this version is a smooth ride to everyone. The final re
Herding elephants: lessons learned from sharding Postgres at Notion
Herding elephants: Lessons learned from sharding Postgres at Notion Earlier this year, we took Notion down for five minutes of scheduled maintenance. While our announcement gestured at “increased stability and performance,” behind the scenes was the culmination of months of focused, urgent teamwork: sharding Notion’s PostgreSQL monolith into a horizontally-partitioned database fleet. The shard nom
Lessons Learned: Sharding for startups is a technical post about database scalability. What caught my eye was the term. What an odd term — “sharding.” Why would a database be described that way? So I started reading a bit about it. It basically means running a bunch of parallel databases and looking into the right one, rather than trying to cram everything into one. Near as I can tell, a quick Goo
クリエーションライン株式会社 on Twitter: "[MongoDB System Alert] MongoDB System Alertが発表されています。 movePrimary may introduce sharding metadata inconsistency in… https://t.co/BKYPCGJSQO"
[MongoDB System Alert] MongoDB System Alertが発表されています。 movePrimary may introduce sharding metadata inconsistency in… https://t.co/BKYPCGJSQO
![クリエーションライン株式会社 on Twitter: "[MongoDB System Alert] MongoDB System Alertが発表されています。 movePrimary may introduce sharding metadata inconsistency in… https://t.co/BKYPCGJSQO"](https://cdn-ak-scissors.b.st-hatena.com/image/square/a32a8050b488ce28a4c45368ae3f8dcb4c7c4aef/height=288;version=1;width=512/https%3A%2F%2Fpbs.twimg.com%2Fprofile_images%2F875636971846066178%2Ffg6X4Yg_.jpg)
4 Data Sharding Strategies We Analyzed When Building YugabyteDB
A distributed SQL database needs to automatically partition the data in a table and distribute it across nodes. This is known as data sharding and it can be achieved through different strategies, each with its own tradeoffs. In this post, we will examine various data sharding strategies for a distributed SQL database, analyze the tradeoffs, explain the rationale for which of these strategies Yugab
Team: Nagavamsi (Vamsi) Ponnekanti, Lingduo Kong, Hwan Seung Yeo (manager) In this blog post, we discuss how Quora was able to scale our usage of MySQL to meet the growing requirements of our content. We’ll focus especially on the challenge of sharding the data stored in MySQL at scale. MySQL at Quora A simplified architecture diagram shown below We use MySQL to store critical data such as questio
GitHub - pg-sharding/spqr: Stateless Postgres Query Router
PostgreSQL is awesome, but it's hard to manage a single database with some terabytes of data and 105+ queries per second. Current sharding solutions focus on analytical and hybrid workloads (OLAP, HTAP). Moreover, most of those solutions do not provide a smooth path for monolith to sharded transitions, which is why Yandex Cloud's Data Platform team developed SPQR. SPQR is a production-ready system
Team: Nagavamsi (Vamsi) Ponnekanti, Lingduo Kong, Hwan Seung Yeo (manager) In this blog post, we discuss how Quora was able to scale our usage of MySQL to meet the growing requirements of our content. We’ll focus especially on the challenge of sharding the data stored in MySQL at scale. MySQL at Quora A simplified architecture diagram shown below We use MySQL to store critical data such as questio
Neural network scaling has been critical for improving the model quality in many real-world machine learning applications with vast amounts of training data and compute. Although this trend of scaling is affirmed to be a sure-fire approach for better model quality, there are challenges on the path such as the computation cost, ease of programming, and efficient implementation on parallel devices.
Dataflow Auto Sharding for BigQuery delivers 3x performance | Google Cloud Blog
Shanmugam (Shan) KulandaivelProduct Manager, Streaming Analytics, Google Cloud Many of you rely on Dataflow to build and operate mission critical streaming analytics pipelines. A key goal for us, the Dataflow team, is to make the technology work for users rather than the other way around. Autotuning, as a fundamental value proposition Dataflow offers, is a key part of making that goal a reality -
GitHub - gojek/weaver: An Advanced HTTP Reverse Proxy with Dynamic Sharding Strategies
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Database “sharding” came from UO?
MySQL sharding at Quora - Engineering at Quora - Quora
MySQL sharding at Quora - Engineering at Quora - Quora
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
charinko-tometai.com
ascii.jp
www.asahi.com
charinko-tometai.com
kakoo.jp
www.saisho.jp