Xuechao Serial War
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The document compares serialization formats JSON, Avro, and Protobuf by measuring size, latency, and throughput. It finds that JSON has around 50% larger size but 34% lower latency than Avro, while Protobuf has slightly higher size than Avro but 17% higher latency. It recommends JSON for latency-critical lightweight data, Avro for data-heavy real-time applications, and Protobuf for applications heavily relying on Google services needing perfect documentation.
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[1] http://www.meetup.com/Bay-Area-Julia-Users/events/226531171/
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Watch the video: http://wp.me/p3RLHQ-goG
Learn more: http://www.hpcadvisorycouncil.com/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
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#Abstract:
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#Prerequisites:
- Basic understanding of AWS services and architecture
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- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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- Validate access.
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- Access sensitive resources.
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- Perform administrative actions.
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Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Slides for the 4th Presentation on LLM Fine-Tuning with QLoRA Presented by Anant, featuring DataStax Astra
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- 2. Ideas and Motivations • What format should be used for real-time apps? • Bandwidth usage
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- 6. Protocol Buffers 33 Bytes *https://martin.kleppmann.com/2012/12/05/schema-ev olution- in-avr o-pr otocol- buffers-thrift.html
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- 8. AverageByKey latency_stream = message_DStream. map(lambda x:json.loads(x)). //x:{json} map(lambda x:(math.ceil(time.time()),time.time()-x["time"])). //(key_time,latency) combineByKey(lambda value: (value, 1),lambda x, value: (x[0] + value, x[1] + 1),lambda x, y: (x[0] + y[0], x[1] + y[1])). //(key_time, (value,1)) -> (key_time,(sum,count)) -> (key_time,(sum,count)) map(lambda (label, (value_sum, count)): (label, value_sum / count)) //(time,averaged_latency)
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- 10. Overall Performance: 2000 events/sec JSON ~50% more ~34% less latency Avro 100kb/s 38ms Protobuf 10% more 17% higher latency
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