amzn-drivers
Apache Arrow
amzn-drivers | Apache Arrow | |
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4 | 75 | |
441 | 13,562 | |
0.7% | 1.4% | |
9.1 | 10.0 | |
17 days ago | 1 day ago | |
C | C++ | |
- | Apache License 2.0 |
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amzn-drivers
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Looking for programmer volunteers who want to contribute/learn about low level C++, Linux, Networking, high frequency trading.
Amazon (AWS) cloud EC2 instance specific role (Kernel and User space networking, linux OS related). Amazon has it's own network card with it's own linux driver (open source), for user space they use DPDK (open source). https://github.com/amzn/amzn-drivers I've measured the time between calling tcp send in software, and packet leaving the NIC (network card), it is around ~50 microseconds latency, aws also stated in a paper it is around that number. Goals:- Figure out the way to build from source code and load the kernel.- Reduce latency
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FreeBSD optimizations used by Netflix to serve video at 800Gb/s [pdf]
It means, for example, writing a FreeBSD kernel driver for Elastic Network Adapter (ENA). Both Linux kernel driver and FreeBSD kernel driver is available at https://github.com/amzn/amzn-drivers
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Dragonflydb – A modern replacement for Redis and Memcached
Of course, there are.
I was mostly running on AWS. In terms of hardware, for small packets loadtests most systems are constrained on throughput, i.e. number of packets per second. Some systems saturate on interrupts reaching 100% CPU on all cores and some can not even saturate the CPU and you will see that CPU is at 60% but you can not go beyond some limit. Best systems networkwise are c6gn family types. They are also better than other cloud provide. btw, you mentioned hypervisors... About 8 months ago I opened a bug on AWS Graviton team https://github.com/amzn/amzn-drivers/issues/195 - about performance issue they had on their instances at high throughput. Recently they issued the fix. I suspect it was in their hypervisor.
In terms of my software I found many performance bugs at those speeds. For example, using a default allocator is a big no. I use mimalloc for uncontended allocations. In general, you can not use mutexes and spinlocks at those speeds. Those will just cripple the system. Sometimes it can be very annoying since you can not rely on a 3rd party library without carefully analyzing its design. For example, I could not use openmetrics c++ library because it was not performant enough. Even to implement a simple counter, say to gather statistics for INFO command becomes an interesting engineering problem:
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Ask HN: Anybody enabled IOMMU on AWS metal servers?
https://doc.dpdk.org/guides/nics/ena.html
and:
https://github.com/amzn/amzn-drivers/tree/master/userspace/dpdk/enav2-vfio-patch
Enabling IOMMU on i3 or c5 metal instances is as easy as adding "iommu=1 intel_iommu=on" to /etc/default/grub followed by update-grub, reboot.
I can't get this to work. Everything I update grub and reboot I cannot re-connected via ssh. Also EC2 console fails to get good status.
My config:
Ubuntu 20.04 stock AWS AMI x86 64-bit
Apache Arrow
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How moving from Pandas to Polars made me write better code without writing better code
In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++.
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From slow to SIMD: A Go optimization story
I learned yesterday about GoLang's assembler https://go.dev/doc/asm - after browsing how arrow is implemented for different languages (my experience is mainly C/C++) - https://github.com/apache/arrow/tree/main/go/arrow/math - there are bunch of .S ("asm" files) and I'm still not able to comprehend how these work exactly (I guess it'll take more reading) - it seems very peculiar.
The last time I've used inlined assembly was back in Turbo/Borland Pascal, then bit in Visual Studio (32-bit), until they got disabled. Then did very little gcc with their more strict specification (while the former you had to know how the ABI worked, the latter too - but it was specced out).
Anyway - I wasn't expecting to find this in "Go" :) But I guess you can always start with .go code then produce assembly (-S) then optimize it, or find/hire someone to do it.
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Time Series Analysis with Polars
One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on par with its NumPy-based features. Polars was built around Arrow from the get go. This makes it very powerful when it comes to exchanging data with other languages and reducing the number of in-memory copying operations, thus leading to better performance.
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TXR Lisp
IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/
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3D desktop Game Engine scriptable in Python
https://www.reddit.com/r/O3DE/comments/rdvxhx/why_python/ :
> Python is used for scripting the editor only, not in-game behaviors.
> For implementing entity behaviors the only out of box ways are C++, ScriptCanvas (visual scripting) or Lua. Python is currently not available for implementing game logic.
C++, Lua, and Python all implement CFFI (C Foreign Function Interface) for remote function and method calls.
"Using CFFI for embedding" https://cffi.readthedocs.io/en/latest/embedding.html :
> You can use CFFI to generate C code which exports the API of your choice to any C application that wants to link with this C code. This API, which you define yourself, ends up as the API of a .so/.dll/.dylib library—or you can statically link it within a larger application.
Apache Arrow already supports C, C++, Python, Rust, Go and has C GLib support Lua:
https://github.com/apache/arrow/tree/main/c_glib/example/lua :
> Arrow Lua example: All example codes use LGI to use Arrow GLib based bindings
pyarrow.from_numpy_dtype:
- Show HN: Udsv.js – A faster CSV parser in 5KB (min)
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Interacting with Amazon S3 using AWS Data Wrangler (awswrangler) SDK for Pandas: A Comprehensive Guide
AWS Data Wrangler is a Python library that simplifies the process of interacting with various AWS services, built on top of some useful data tools and open-source projects such as Pandas, Apache Arrow and Boto3. It offers streamlined functions to connect to, retrieve, transform, and load data from AWS services, with a strong focus on Amazon S3.
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Cap'n Proto 1.0
Worker should really adopt Apache Arrow, which has a much bigger ecosystem.
https://github.com/apache/arrow
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C++ Jobs - Q3 2023
Apache Arrow
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Wheel fails for pyarrow installation
I am aware of the fact that there are other posts about this issue but none of the ideas to solve it worked for me or sometimes none were found. The issue was discussed in the wheel git hub last December and seems to be solved but then it seems like I'm installing the wrong version? I simply used pip3 install pyarrow, is that wrong?
What are some alternatives?
dragonfly - A modern replacement for Redis and Memcached
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
neon - Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
h5py - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
cachegrand - cachegrand - a modern data ingestion, processing and serving platform built for today's hardware
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
helio - A modern framework for backend development based on io_uring Linux interface
FlatBuffers - FlatBuffers: Memory Efficient Serialization Library
midi-redis - A toy memory store with great performance
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
webdis - A Redis HTTP interface with JSON output
ClickHouse - ClickHouse® is a free analytics DBMS for big data