AI Notes For Learning

  • Kafka Disk I/O Tuning Guide

    Disk I/O is a critical bottleneck for Kafka performance. Kafka relies heavily on the file system for storing and retrieving messages, and inefficient disk I/O can lead to…

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  • Kafka Network Latency Tuning

    Network latency is a critical factor in Kafka performance, especially for applications requiring near-real-time data processing. High network latency can significantly increase the time it takes for messages…

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  • Kafka CPU Tuning Guide

    Optimizing CPU usage in your Kafka cluster is essential for achieving high throughput, low latency, and overall stability. Here’s a comprehensive guide to help you effectively tune Kafka…

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  • gRPC vs HTTP

    gRPC (gRPC Remote Procedure Calls) and HTTP (Hypertext Transfer Protocol) are both fundamental protocols used for communication between applications, but they differ significantly in their design, features, and…

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  • Databricks scalability

    Databricks is designed with scalability as a core tenet, allowing users to handle massive amounts of data and complex analytical workloads. Its scalability stems from several key architectural…

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  • Apache Spark

    Let’s illustrate Apache Spark with a classic “word count” example using PySpark (the Python API for Spark). This example demonstrates the fundamental concepts of distributed data processing with…

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