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Tag: Algorithm

  • Real-time Recommendation Engine AI Agent on AWS

    Real-time Recommendation Engine AI Agent on AWS Implementing a real-time recommendation engine AI agent on AWS requires a robust and scalable architecture. Here are implementation examples for key services in the tech stack: 1. Real-time Data Ingestion (Amazon Kinesis Data Streams): You would use the AWS SDK (Boto3 in Python) in your application backend to… Read more

  • Fixing CPU Spike Issues in Kafka

    Fixing CPU Spike Issues in Kafka 1. Monitoring CPU Usage: The first step is to effectively monitor the CPU utilization of your Kafka brokers. Key metrics to watch include: System CPU Utilization: The overall CPU usage of the server. User CPU Utilization: The CPU time spent running user-level code (the Kafka broker process itself). I/O… Read more

  • CPU vs IO Bound Sample Java Implementation (4-Core Optimized)

    CPU/IO Bound Java (4-Core Optimized) Here’s the Java code, optimized for a 4-core CPU. The following sections provide a detailed explanation of the code and the concepts behind it. import java.util.concurrent.ForkJoinPool; import java.util.concurrent.RecursiveTask; public class CPUBoundMultiThreaded { static class CalculationTask extends RecursiveTask<Long> { private final long start; // Start of the range to calculate private… Read more

  • Colocating data for Performance improvements

    Data Colocation for Performance in Large Clusters To colocate data in a huge cluster for performance, the primary goal is to minimize the distance and time it takes for computational resources to access the data they need. This reduces network congestion, latency, and improves overall processing speed. Here’s how: 1. Partitioning (Sharding) How it works:… Read more

  • Advanced Neo4j Tips

    Advanced Neo4j Tips Advanced Neo4j Tips This document provides advanced tips for optimizing your Neo4j graph database for performance, scalability, and efficient data management. It goes beyond the basics to help you leverage Neo4j’s full potential. Schema Design A well-designed schema is the foundation of a high-performance graph database. It dictates how your data is… Read more

  • Comprehensive Guide to Checkpointing

    Comprehensive Guide to Checkpointing Comprehensive Guide to Checkpointing in Various Applications Checkpointing is a fault-tolerance technique used across various computing systems and applications. It involves periodically saving a snapshot of the application or system’s state so that it can be restored from that point in case of failure. This is crucial for long-running processes and… Read more

  • Advanced Java Garbage Collection Tuning

    Advanced Java Garbage Collection Tuning Optimizing the JVM’s garbage collection (GC) is a critical aspect of ensuring high performance, low latency, and stability for Java applications, especially those handling significant loads or requiring stringent response times. 1. Understanding Garbage Collection Goals Before tuning, you need to define your application’s performance goals. The primary goals of… Read more

  • Detailed Workflow for Claims Adjudication with AI Integration

    Detailed Workflow for Claims Adjudication with AI Integration The claims adjudication process is being significantly enhanced by the integration of Artificial Intelligence (AI) at various stages. The following workflow highlights where AI tools and techniques can be applied to improve efficiency, accuracy, and speed. Phase 1: Claim Submission and Initial Review – AI Assistance Step… Read more

  • Algorithms for Vector Embeddings

    Here are some of the most common algorithms used for generating vector embeddings, particularly in Natural Language Processing (NLP): 1. Word2Vec (2013) Developed by: Google. Approach: Predicts a word given its context (Continuous Bag of Words – CBOW) or predicts the surrounding context words given a word (Skip-gram). Key Idea: Words appearing in similar contexts… Read more

  • Most used Search Algorithms

    Search Algorithms for Techies (2025) As techies, understanding search algorithms is fundamental. Whether you’re working with databases, web search, AI, or even game development, efficient search is often at the core of your applications. Here’s a look at essential search algorithms in 2025, categorized for clarity: Basic Search Algorithms Linear Search (Sequential Search): A straightforward… Read more

  • Broadcast Hash Join

    The Broadcast Hash Join is a join optimization strategy used in distributed data processing frameworks like Apache Spark, Dask, and others. It’s particularly effective when one of the tables being joined is significantly smaller than the other and can fit into the memory of each executor node in the cluster. Here’s how it works: Algorithm:… Read more

  • 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 for CPU efficiency: 1. Understanding Kafka’s CPU Consumption 2. Monitoring CPU Usage 3. Tuning Strategies 4. Best Practices By following these guidelines, you can effectively tune your… Read more

  • Output of machine learning (ML) model

    The output of a machine learning (ML) training process is a trained model. This model is an artifact that has learned patterns and relationships from the training data. The specific form of this output depends on the type of ML algorithm used. Here’s a breakdown of what constitutes the output of ML training: 1. The… Read more