async-profiler
Weaviate
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| async-profiler | Weaviate | |
|---|---|---|
| 10 | 76 | |
| 7,112 | 9,524 | |
| 2.8% | 5.7% | |
| 8.7 | 10.0 | |
| 11 days ago | 4 days ago | |
| C++ | Go | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
async-profiler
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JVM Profiling in Action
We'll use async-profiler and flame graphs for profiling. To simplify the process, we'll run the code using JBang.
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The Return of the Frame Pointers
JIT'ed code is sadly poorly supported, but LLVM has had great hooks for noting each method that is produced and its address. So you can build a simple mixed-mode unwinder, pretty easily, but mostly in process.
I think Intel's DNN things dump their info out to some common file that perf can read instead, but because the *kernels* themselves reuse rbp throughout oneDNN, it's totally useless.
Finally, can any JVM folks explain this claim about DWARF info from the article:
> Doesn't exist for JIT'd runtimes like the Java JVM
that just sounds surprising to me. Is it off by default or literally not available? (Google searches have mostly pointed to people wanting to include the JNI/C side of a JVM stack, like https://github.com/async-profiler/async-profiler/issues/215).
- FLaNK Stack 29 Jan 2024
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Tracking Java Native Memory with JDK Flight Recorder
debugging native calls in itself is also painful. I have switched to using async-profiler (https://github.com/async-profiler/async-profiler) instead of JFR for most of my usecases.
A. it tracks native calls by default
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Show HN: Javaflame – Simple Flamegraph for your Java application
https://github.com/async-profiler/async-profiler#flame-graph...
Ok, Windows is not supported. But IntelliJ made a fork which works on Windows.
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Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU in production - Is it normal? Did you observe that in your environment? Any ways to optimize it?
Hi, today I used async-profiler to check the CPU usage of my Spring Boot app (just a normal backend) in production. Surprisingly, Lettuce (Redis) + Mybatis (MySQL) take up most of the CPU time. I am not talking about wall time here, but CPU time, since I know database requests need to wait for milliseconds and thus wall time will be very long. Therefore, I wonder:
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A question about Http4s new major version
You can use async-profiler to see what is happening under the hood.
- Reducing code size in (Rust) librsvg by removing an unnecessary generic struct
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what is your favorite programming trick/tool that not many People know about?
I have used visual vm quite a bit. https://github.com/async-profiler/async-profiler is also amazing... Throw the binary on the system and fire it up. It also profiles down into native code as well if you do that kind of thing.
Weaviate
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pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
- FLaNK Stack 29 Jan 2024
- Qdrant, the Vector Search Database, raised $28M in a Series A round
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How to use Weaviate to store and query vector embeddings
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.
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Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
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Who's hiring developer advocates? (October 2023)
Link to GitHub -->
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Do we think about vector dbs wrong?
Hey @rvrs, I work on Weaviate and we are doing some improvements around increasing write throughput:
1. gRPC. Using gRPC to write vectors has had a really nice performance boost. It is released in Weaviate core but here is still some work on do on the clients. Feel free to get in contact if you would like to try it out.
2. Parameter tuning. lowering `efConstruction` can speed up imports.
3. We are also working on async indexing https://github.com/weaviate/weaviate/issues/3463 which will further speed things up.
In comparison with pgvector, Weaviate has more flexible query options such as hybrid search and quantization to save memory on larger datasets.
- Weaviate vector database
- Weaviate 1.21: Support for ImageBind and GPT4all and more
- Weaviate Vector Database
What are some alternatives?
jmh - https://openjdk.org/projects/code-tools/jmh
Milvus - A cloud-native vector database, storage for next generation AI applications
container-jfr - Secure JDK Flight Recorder management for containerized JVMs
faiss - A library for efficient similarity search and clustering of dense vectors.
jfr-libraries - a list of libraries that generate JFR events
pgvector - Open-source vector similarity search for Postgres
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
jina - ☁️ Build multimodal AI applications with cloud-native stack
junit-jfr - a JUnit 5 extension that generates JFR events
vald - Vald. A Highly Scalable Distributed Vector Search Engine