GrocerySales10MDataset

This dataset represents a large-scale synthetic transactional sales dataset designed to simulate real-world e-commerce or point-of-sale systems. It consists of 10 million transaction records, where each record corresponds to a single product purchase made by a user. Each transaction contains a unique transaction identifier, user and product identifiers, product category, quantity purchased, unit price, timestamp of the transaction, and the geographic region where the transaction occurred. The timestamps span a full calendar year (2023), enabling temporal analysis such as daily, monthly, or seasonal trends. The dataset includes multiple product categories (Electronics, Clothing, Books, Toys, and Home) and regional information (Dhaka, Chittagong, Sylhet, and Rajshahi), making it suitable for analyzing customer behavior, sales patterns, regional demand, and time-based purchasing trends. Due to its large size, the dataset is particularly useful for evaluating big data processing frameworks, scalability of data analytics pipelines, and performance benchmarking of distributed data processing systems.本数据集为大规模合成交易销售数据集，旨在模拟真实世界的电子商务或销售点系统。该数据集包含1000万条交易记录，每条记录对应一名用户的单次商品购买行为。 每一条交易记录均包含唯一交易标识符、用户与商品标识符、商品类别、购买数量、单价、交易时间戳以及交易发生的地理区域。交易时间戳覆盖完整自然年（2023年），可支持日度、月度或季节性趋势等时序分析。 该数据集涵盖多类商品类别（电子产品（Electronics）、服装（Clothing）、图书（Books）、玩具（Toys）及家居用品（Home））与区域信息（达卡（Dhaka）、吉大港（Chittagong）、锡尔赫特（Sylhet）及拉杰沙希（Rajshahi）），适用于分析用户行为、销售模式、区域需求以及基于时间的购买趋势。鉴于其海量规模，该数据集尤其适用于评估大数据处理框架、数据分析流水线的可扩展性，以及分布式数据处理系统的性能基准测试。