Resource efficient full bootstrap

Abstract

Systems and methods are disclosed for a resource efficient full bootstrap of a destination database. Instead of executing, e.g., a single Apache Spark™ job that may encounter errors and require restarting the entire job and reallocation of Spark cluster resources, the data pulls from a data source for a full bootstrap may be divided into smaller jobs. Dividing the set of data pulls into smaller jobs (which may be kept as a simpler Java™ program as compared to an Apache Spark job) allows only the impacted job to again be executed if an error occurs during execution of that job. In addition, resources to execute the job for bootstrapping a database may be allocated only once, which may allow the resources to be less than if estimated and grown based on errors and multiple attempts to execute the job (such as for an Apache Spark job to bootstrap the database).