A Mass Data Update Method in Distributed Systems

Today, distributed business systems are used widely, and the consistency of their databases are maintained by the distributed transactions. On the other hand, a great deal of data is often updated in a lump-sum in the business systems. And, since the non-stop service has become general, it is necessary to perform this lump-sum update concurrently with the online transactions that service to users. So, some methods are utilized to avoid the influences on the online transactions, like the mini-batch that splits a lump-sum update into small transactions and executes them one after another. However, in the distributed systems, since it has to be executed by the distributed transactions, there is a problem on the efficiency to update a great deal of data by this method. For this problem, we propose to apply an update method to the distributed systems, which utilizes the records of data about the time to avoid conflicts between the lump-sum update and the online transactions. Moreover, through experiments using a prototype, we confirmed that it can update data more efficiently than the chain of small transactions even in the distributed systems.