The invention provides an electricity consumption data batch high speed processing method and system based on distributed offline technology, and relates to a data batch processing method system. At present, there is a lacking of the high speed mass data storage and calculation model, and not all the types and forms of mass data storage and calculation can be fulfilled. The method comprises the steps of (1) an electricity consumption front sampler sending the sampled electricity consumption data to a Kafka data queue for buffering in a real-time mode, (2) Storm cluster reading the electricity consumption information in the Kafka queue, and storing the information in a real-time mode to a Hbase, (3) Spark extracting the electricity consumption information to be processed from the Hbase, and uploading the information to a Hive data sheet, (4) through Spark conducting the offline operation of related Hive data sheet to acquire the electricity consumption of the current period, and processing related abnormalities. The method combines the advantages of both the Storm and the Spark, enhances the overall processing capacity. From the dynamic migration technology of transaction security node, a transaction security protocol of complete task node migration is proposed. On the foundation of the guarantee of no packet loss, no repetition in the migration process, at the same time the execution efficiency of the migration itself is enhanced, and the system stability is elevated.