👉 Indexed computing is a paradigm that leverages the power of distributed indexing and query processing to accelerate data analysis and machine learning tasks. In this approach, raw data is indexed using a structured, searchable format that allows for efficient retrieval and querying. Instead of processing large datasets directly, indexed computing involves creating an index that maps data elements to their locations or summaries, enabling rapid access to relevant information. This method is particularly beneficial for big data applications where traditional processing methods would be too slow or resource-intensive. By offloading the heavy indexing work to specialized hardware or software, indexed computing significantly reduces latency and computational overhead, making it possible to perform complex analytics and machine learning tasks in real-time or near-real-time.
