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Azure Storage Accounts: Azure Blob storage is a distributed object storage service that stores unstructured data. It uses a partition-based architecture to distribute data across multiple servers. Each partition is managed by a set of servers that collectively handle requests for that partition. Azure Blob storage employs consistenthashing_algorithm to determine the partition for each object based on its unique identifier.
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CosmosDB: Azure Cosmos DB is a globally distributed, multi-model database service. It uses a combination of different data structures and algorithms depending on the data model used. For document data model support, Cosmos DB employs B Tree orlog_structured_merge (LSM) trees for efficient indexing and retrieval. For graph data model support, Cosmos DB utilizes graph-specific data structures likeadjacency_list oradjacency_matrix to represent and traverse Graph data efficiently.
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Azure HDInsight: HDInsight is a cloud-based service for big data processing and analytics. It supports various distributed processing frameworks like Hadoop, Spark, andHive. HDInsight leverages the Hadoop Distributed File System (HDFS), which uses a block-based storage approach. HDFS divides large files into smaller blocks and distributes them across a cluster of machines. It employs algorithms such asreplication_algorithm (to ensure data redundancy) and distributed data locality (to minimize data movement during computation).
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Azure Machine Learning: Azure Machine Learning provides a wide range of machine learning algorithms for training and deploying models. These algorithms are implemented using various mathematical and statistical techniques. For example, algorithms like decision trees are implemented using techniques such as recursive partitioning and entropy-based information gain. Neural networks use backpropagation algorithms for training. Support Vector Machines (SVM) rely on convex optimization algorithms to find the optimal hyperplane separating classes.
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Azure Load Balancer: Azure Load Balancer is a traffic distribution service that balances incoming requests across multiple virtual machines or servers. It employs algorithms such as round-robin, where requests are sequentially distributed to each server in rotation. Weighted round-robin allows assigning different weights to servers based on their capacity, enabling better resource allocation. Least connections algorithm directs traffic to the server with the fewest active connections, distributing the load evenly.
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Sorting and Searching Algorithms: Azure’s data storage services often utilize efficient sorting and searching algorithms to retrieve and organize data quickly. Algorithms like quicksort, mergesort, binary search, and B-trees are commonly used in these scenarios.
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MapReduce: Azure offers a service called Azure HDInsight, which supports the MapReduce programming model. MapReduce is a distributed algorithm used for processing and analyzing large datasets across a cluster of computers. It allows for parallel processing and fault tolerance, making it suitable for big data analytics.
Links
https://learn.microsoft.com/en-in/azure/load-balancer/concepts