Abstract: Techniques are disclosed relating to bulk data extraction systems. In some embodiments, a streaming server system may receive a first request, from a data storage system, that is sent prior to initiation of a bulk data extraction for a first group of users. In response to the first request, the streaming server system may receive, from the data storage system, a first notification message that includes a particular event identifier for a most recent data event generated at the data storage system. The streaming server system may receive, from the data storage system, those messages associated with the bulk data extraction for the first group. Subsequent to completion of the bulk data extraction, the streaming server system may send, to the data storage system, a request to subscribe to notification messages for data events associated with the first group.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for facilitating smart streaming of data between external systems and service providers in an on-demand services environment according to one embodiment. In one embodiment and by way of example, a method comprises splitting, by a streaming server computing device (“streaming device”), a file including messages associated with multiple tenants in a multitenant environment based on growth of the file over a time-period. The method may further include grouping, by the streaming device, the messages into multiple files based on intelligence fields associated with one or more of the messages and the tenants, where each file of the multiple files corresponds to a tenant of the multiple tenants. The method may further include uploading, by the streaming device, the multiple files to a database device associated with a service provider and coupled to the streaming server device.

Abstract: A method is described for collapsing a plurality of detected changes to data in a database into a reduced set of changes. The method includes detecting a plurality of changes to the database; determining that one or more changes in the plurality of changes are superfluous to demonstrating the current state of data in the database to an external system; determining, in response to determining that one or more changes in the plurality of changes are superfluous, a reduced set of changes that demonstrates the current state of data in the database based on the plurality of changes, wherein a number of changes in the plurality of changes is greater than a number of changes in the reduced set of changes; and determining a set of messages to generate based on the reduced set of changes, wherein the set of messages demonstrate the current state of data.

Abstract: A method by a computing system implementing a node within a cluster of nodes to load balance among the cluster of nodes using retroactive refusal. Each of the nodes within the cluster of nodes is capable of processing work items. The method includes accepting a work item to be processed by the node, monitoring a resource utilization of the node, determining whether the resource utilization of the node exceeds a predetermined threshold, and retroactively refusing the work item in response to a determination that the resource utilization of the node exceeds the predetermined threshold, wherein the retroactive refusal causes the work item to be reassigned from the node to another node within the cluster of nodes.

Abstract: Dynamic selection of data sources for streaming dynamic data is described. A data streaming service receives a dynamic selection of a data source after the data streaming service begins executing, the dynamic selection of the data source including an identifier of a host of a multi-tenant database and an identifier of a tenant of multiple tenants storing data in the multi-tenant database. The data streaming service streams dynamic data from the data source to a data destination.