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Data Scientist Vs Data Analyst: Key Differences, Career Paths, and How to Choose the Right Role

WeCloudData

quintillion bytes of data are generated every day and thats a great sign for anyone interested in a data-driven career. This blog focuses […] The post Data Scientist Vs Data Analyst: Key Differences, Career Paths, and How to Choose the Right Role appeared first on WeCloudData.

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Handling Network Throttling with AWS EC2 at Pinterest

Pinterest Engineering

In this blog post, well discuss our experiences in identifying the challenges associated with EC2 network throttling. In the remainder of this blog post, well share how we root cause and mitigate the aboveissues. This prompted us to engage with AWS and dive deep into the network performance of our clusters. 4xl with up to 12.5

AWS 57
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Fault Tolerance in Distributed Systems: Tracing with Apache Kafka and Jaeger

Confluent

Instead, in this post I will point you to an earlier blog post where I already answered that question and then I will focus on what should be your next question: now that I’m relying on Jaeger to trace how data is flowing through my distributed system, what if Jaeger goes down? Distributed tracing with Apache Kafka and Jaeger.

Kafka 54
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Improving Efficiency Of Goku Time Series Database at Pinterest (Part?—?1)

Pinterest Engineering

In the first blog, we will share a short summary on the GokuS and GokuL architecture, data format for Goku Long Term, and how we improved the bootstrap time for our storage and serving components. More information about the architecture can be found in the GokuL blog and the cost reduction blog.

Database 111
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LLM finetuning memory requirements by Alex Birch

Scott Logic

Cost increases when gradient accumulation is enabled, or becomes ~free if used in concert with DDP DDP usually costs ~4 bytes/param, but becomes cheaper if used in concert with AMP DDP can be made 2.5 Transformer Math does not mention a "4 bytes/param master gradients" cost.

Bytes 102
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Open-Sourcing AvroTensorDataset: A Performant TensorFlow Dataset For Processing Avro Data

LinkedIn Engineering

In this blog post, we will discuss the AvroTensorDataset API, techniques we used to improve data processing speeds by up to 162x over existing solutions (thereby decreasing overall training time by up to 66%), and performance results from benchmarks and production. an array within a map, within a union, etc…). Default is 128 * 1024 (128KB).

Datasets 102
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Memory Optimizations for Analytic Queries in Cloudera Data Warehouse

Cloudera

You can read previous blog posts on Impala’s performance and querying techniques here – “ New Multithreading Model for Apache Impala ”, “ Keeping Small Queries Fast – Short query optimizations in Apache Impala ” and “ Faster Performance for Selective Queries ”. . Total size of the Bucket is 16 bytes. Folding data into pointers.