batch processing

简明释义

1. 批量处理; 2. 成批处理; 3. 间歇处理; 4. 成组处理;

英英释义

例句

1.The company uses batch processing to handle large volumes of transactions at once.

公司使用批处理一次性处理大量交易。

2.Using batch processing, we can automate repetitive tasks and save time.

使用批处理，我们可以自动化重复任务并节省时间。

3.The software is designed for batch processing to improve efficiency in data analysis.

该软件设计用于批处理，以提高数据分析的效率。

4.By implementing batch processing, we can reduce the time taken for data entry.

通过实施批处理，我们可以减少数据输入所需的时间。

5.During the night, the system performs batch processing to update all records.

在夜间，系统进行批处理以更新所有记录。

作文

In today's fast-paced digital world, data processing has become an essential part of various industries. One of the most efficient methods of handling large volumes of data is through batch processing. This technique allows organizations to process data in groups or batches, rather than individually, which can significantly improve efficiency and reduce processing time.The concept of batch processing originated in the early days of computing when mainframe computers were used to handle large amounts of data. Instead of processing each transaction as it occurred, which was time-consuming and resource-intensive, companies would collect data over a period and then process it all at once. This method proved to be much more efficient, allowing for better resource management and reduced operational costs.One of the primary advantages of batch processing is its ability to handle large datasets effectively. For instance, in financial institutions, transactions are often processed in batches at the end of the day. This not only streamlines the workflow but also ensures that all transactions are accounted for before generating reports. Similarly, in manufacturing, data related to production processes can be collected throughout the day and analyzed at the end of the shift, enabling managers to make informed decisions based on comprehensive data.Moreover, batch processing is particularly useful in scenarios where immediate processing is not critical. For example, in data analytics, businesses may choose to run complex algorithms on large datasets after hours, allowing them to utilize resources more efficiently during peak hours. This approach minimizes downtime and maximizes productivity, which is crucial for maintaining a competitive edge in the market.Another significant benefit of batch processing is its cost-effectiveness. By processing data in batches, organizations can reduce the amount of computing power needed at any given time. This is especially important for cloud-based services, where costs are often tied to resource usage. By scheduling batch processing during off-peak hours, companies can take advantage of lower rates and optimize their cloud spending.However, batch processing is not without its challenges. One major drawback is the delay in data availability. Since data is processed in batches, there can be a lag between when data is generated and when it is available for analysis. This can be problematic for businesses that require real-time insights to make quick decisions. In such cases, organizations may need to implement a hybrid approach, combining both batch processing and real-time processing to meet their needs.In conclusion, batch processing is a powerful technique that allows organizations to efficiently manage and analyze large volumes of data. Its ability to streamline workflows, reduce costs, and maximize resource utilization makes it an attractive option for many industries. However, businesses must also consider the potential drawbacks, such as delays in data availability, and find ways to balance batch and real-time processing to achieve optimal results. As technology continues to evolve, the methods and tools for batch processing will likely become even more sophisticated, further enhancing its role in the data-driven landscape of the future.

在当今快速发展的数字世界中，数据处理已成为各行各业的重要组成部分。处理大量数据的最有效方法之一是通过批处理。这种技术允许组织以组或批次的方式处理数据，而不是单独处理，这可以显著提高效率并减少处理时间。批处理的概念起源于计算机早期，当时使用大型计算机来处理大量数据。与其在每次交易发生时进行处理，这既耗时又占用资源，企业会在一段时间内收集数据，然后一次性处理所有数据。这种方法被证明是更有效的，可以更好地管理资源并降低运营成本。批处理的一个主要优点是能够有效处理大数据集。例如，在金融机构，交易通常在一天结束时以批次处理。这不仅简化了工作流程，还确保在生成报告之前所有交易都得到了记录。同样，在制造业中，与生产过程相关的数据可以在一天内收集，并在班次结束时进行分析，使管理者能够根据全面的数据做出明智的决策。此外，批处理在即时处理不关键的场景中特别有用。例如，在数据分析中，企业可能选择在非高峰时段对大型数据集运行复杂算法，从而在高峰时段更有效地利用资源。这种方法最大限度地减少了停机时间并提高了生产力，这对于在市场中保持竞争优势至关重要。另一个重要的好处是批处理的成本效益。通过批量处理数据，组织可以减少在任何给定时间所需的计算能力。这对于基于云的服务尤为重要，因为成本通常与资源使用相关。通过在非高峰时段安排批处理，公司可以利用较低的费率，优化其云支出。然而，批处理并非没有挑战。一个主要的缺点是数据可用性的延迟。由于数据是批量处理的，因此从数据生成到数据可用于分析之间可能会有滞后。这对于需要实时洞察以快速做出决策的企业来说可能是个问题。在这种情况下，组织可能需要实施混合方法，结合批处理和实时处理，以满足其需求。总之，批处理是一种强大的技术，允许组织有效地管理和分析大量数据。它简化工作流程、降低成本和最大化资源利用的能力使其成为许多行业的吸引选项。然而，企业还必须考虑潜在的缺点，例如数据可用性的延迟，并找到平衡批处理和实时处理的方法，以实现最佳结果。随着技术的不断发展，用于批处理的方法和工具可能会变得更加复杂，进一步增强其在未来数据驱动环境中的作用。