dataloader
Aeron
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dataloader | Aeron | |
---|---|---|
47 | 20 | |
12,632 | 7,054 | |
0.5% | 1.0% | |
3.3 | 9.8 | |
about 1 month ago | about 14 hours ago | |
JavaScript | Java | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dataloader
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Delving into the Black Magic of GraphQL DataLoader! 🌌✨
When I began working with GraphQL, I had concerns about the N+1 query problem. In my research, I came across the DataLoader pattern and its implementation on GitHub. While I explored various examples of its usage, I still struggled to grasp how it operates internally. Join me in delving a bit deeper into GraphQL DataLoader! :)
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How to use DataLoader with Mercurius GraphQL
DataLoader: it is the standard solution to N+1 problem.
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Best Practices in Testing GraphQL APIs
Additionally, you can use DataLoader or similar tools to optimize data fetching and avoid over-fetching or under-fetching data. Ultimately, performance and load tests ensure that your GraphQL API delivers optimal performance, meets response time expectations, and provides a smooth experience for users, even under heavy loads.
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Migrating Netflix to GraphQL Safely
The most common practice is to turn N+1 into 1+1 using dataloaders (https://github.com/graphql/dataloader for JS, there are equivalents for most implementations). The N resolvers invoke a single batched loader which receives a list of keys and returns a list of values.
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SQL vs. NoSQL - cutting through the Tech Twitter noise
Let's take Payload, for example. Surprise, surprise. We have a relationship field, and it can store IDs to other related documents which are seamlessly merged in when you retrieve documents from the DB. We leverage the dataloader pattern to batch together all "populations" required for a given query, returning them all super fast and with as few separate queries to the DB as possible. We actually even outperform SQL-based frameworks quite a bit. In a purely relational test, we were 3x faster than Directus and 7x faster than Strapi while both were running Postgres, and we were on MongoDB.
- NoSQL vs. SQL - cutting through the Tech Twitter noise with a real-world use case
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We Ditched REST and Went with GraphQL: Here’s Why
Also, have a look at Facebook's Dataloader[0].
[0] https://github.com/graphql/dataloader
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Implementing logger with metadata
In the next article, I'm going to implement a GraphQL server with dataloader using the tools we introduced.
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Typesafe, (almost) Zero Cost Dependency Injection in TypeScript
The one example of using Scoped dependency that comes to my mind, it's HTTP request level caching for libs like dataloader.
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GraphQL Trades Complexity
you would fetch these 1000 rows via dataloader that batches all requests for this relation to a single query... solving the n+1 issue
Aeron
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LMAX Disruptor – High Performance Inter-Thread Messaging Library
Semi-related is the Aeron project: https://github.com/real-logic/aeron
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Nálatok mi a helyzet?
- ez itt most egy izgalmasabb product (trading/matching engine, low latency code, aeron alapokon)
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How do you do UDP Flow control?
Look into Aeron for examples of high performance UDP message sending. We use it for high performance audio messaging, and I previously used it in high frequency trading https://github.com/real-logic/aeron. It is written in Java/C, but the general concepts of back pressure and reliable delivery over UDP are well documented.
- Aeron: Efficient reliable UDP unicast, UDP multicast, and IPC message transport
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Experience taking the training offer from real-logic Aeron framework creators?
They mention their training offer on the Aeron GitHub page here: https://github.com/real-logic/aeron
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Low Latency C++ programs for High Frequency Trading (HFT)
Yup the Disruptor paper actually shocked the industry a bit, b/c it was so out of place. BTW, Martin Thompson went on improving the Disruptor, and the result is the Aeron Protocol: https://github.com/real-logic/aeron
- What network messaging library do you recommend?
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Possibly stupid question, is java the right language for low latency and high throughput web servers?
I was about to suggest Chronicle, but it looks like they have gone closed-source. The older version is still interesting to look through though. Aeron / Disruptor / SBE are good projects for inspiration as well.
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Looking similar framework with Aeron ( Java) to do benchmark test
We are using this Java Aeron (https://github.com/real-logic/aeron) to build our production distributed messaging cluster. As a Rust lover, Is there any similar lib or framework in our ecosystem to test benchmark with it?
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if you had to restart at 0 knowledge what would you do?
Java: In the past years C++ in finance has been rapidly supplanted by Java thanks to breakthrough technologies in the past decade like LMAX Disruptor, Chronicle Queue, Azul JVM, and Aeron (not the ergonomic chair, but this one, the transport protocol that breaks kafka performance records out of the park - not really a full kafka replacement, as Kafka enforces subscriber GD and aeron is more of an OSI layer 4 better than TCP; google "Best-effort delivery vs reliable delivery"). There's plenty more but thanks to these technologies, they allowed a Java based stack to perform the latency and throughput requirements needed for high frequency trading/HFT. From top trading firms like Two Sigma to the New York Stock Exchange, they're in Java. For banks, large modern western banks worth their salt and have modernized their systems are dominated by Java, especially thanks to Azul. To list a few banks, ING, Wells Fargo, Credit Suisse, and Barclays are all in Azul. Even at work Java still dominates.
What are some alternatives?
Redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
Apache Kafka - Mirror of Apache Kafka
react-relay - Relay is a JavaScript framework for building data-driven React applications.
Embedded RabbitMQ - A JVM library to use RabbitMQ as an embedded service
Knex - A query builder for PostgreSQL, MySQL, CockroachDB, SQL Server, SQLite3 and Oracle, designed to be flexible, portable, and fun to use.
Apache Pulsar - Apache Pulsar - distributed pub-sub messaging system
jest - Delightful JavaScript Testing.
Apache ActiveMQ - Mirror of Apache ActiveMQ
Sequelize - Feature-rich ORM for modern Node.js and TypeScript, it supports PostgreSQL (with JSON and JSONB support), MySQL, MariaDB, SQLite, MS SQL Server, Snowflake, Oracle DB (v6), DB2 and DB2 for IBM i.
JeroMQ - Pure Java ZeroMQ
gRPC - The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
Apache Camel - Apache Camel is an open source integration framework that empowers you to quickly and easily integrate various systems consuming or producing data.