Salesforce Com, Inc.

Salesforce, Inc.

Xiaodan Wang

Mikhail Chainani

Vijayanth Devadhar

Ilya Zaslavsky

Sridevi Gopala Krishnan

Praveen Murugesan

Alan Arbizu

Ashwini Bijwe

Alex Ovesea

John Buisson

Olumayokun Obembe

Da Zhao

Jason Woods

Chen Liu

Ping-Hsiu Hsieh

Lauren Valdivia

Sidarth Conjeevaram

William Dumaresq

Kin Lun Wong

Zeyu Zheng

Paul E Jatkowski

Vipul Modani

Jae Young Park

Scott Ware

Fabio Meireles Fernandez Valbuena

Prakash Ramaswamy

Yichuan Cai

Hui Lam Kwong

Venkat Chandrasekaran

Paul Sydell

Utsavi Benani

Jia Chen

Vijay Devadhar

A request may be received to evacuate data from a database system associated with a designated computing pod that provides on-demand computing services to a plurality of entities via the internet. The data may include portions that each correspond with a respective one or more of the on-demand computing services. Data succession policies associated with the data may be identified, where each data succession policy corresponds with one of the data portions and identifies one or more constraints associated with evacuating the data portion. The data portions may be transmitted to recipient computing pods in accordance with the data succession policies, and removed from the database system.

Declarative data evacuation for distributed systems

Techniques and structures to prevent exhaustion of a database connection pool, including retrieving data from the database connection pool, monitoring the data to determine whether the connection pool is at risk of an exhaustion condition, analyzing the data to determine whether one or more clients accessing the database connection pool are offenders upon determining that the connection pool is at risk and throttling access to the one or more clients accessing the database connection pool upon determining the one or more clients to be offenders.

Connection pool anomaly detection mechanism

A first copy of a database object may be constructed prior to applying a designated database update request to a first database. The database object may be represented by a plurality of database table rows in the first database, and the request may update one or more of the plurality of rows. The request may be applied to the first database to update the one or more of the plurality of rows in the first database. A second copy of the database object may be constructed after applying the database update request to the first database. A message identifying a difference between the first copy of the database object and a second copy of the database object may be transmitted to a remote computing device.

Asynchronous row to object enrichment of database change streams

A request for an organization migration to move application data and application services of an organization hosted at a source system instance in a multi-tenant computing system to a target system instance in the multi-tenant computing system is received. Based on operational parameters, a time window is selected to execute the organization migration. Computing resource usages of one or both of the source and target system instances in the selected time window are monitored. If computing resources are available, the organization migration is enqueued.

Scheduling framework for organization migrations

A resource utilization level and a data size may be determined for each organization within a computing pod located within an on-demand computing services organization configured to provide computing services. One of the organizations may be selected for migration away from the computing pod based on the resource utilization levels and the data sizes. The designated organization may have a respective resource utilization level that is high in relation to its respective data size.

Load balancing through autonomous organization migration

Messages are transmitted to first and second server groups in an on-demand computing services environment. The first message instructs the first server group to reduce a first resource allocation level associated with a network-accessible computing resource, while the second message instructs the second server group to increase a second resource allocation level associated with the resource. The resource allocation levels designate respective proportions of the network-accessible computing resource shared among the server groups. Request traffic associated with providing services via the on-demand computing services environment is transferred from the first server group to the second server group after decreasing the first resource allocation level and increasing the second resource allocation level.

Intent-based allocation of database connections

A request may be received to relocate source data within a distributed database system arranged in a hierarchy composed of a plurality of levels. The plurality of levels may include a local level that includes a plurality of pods, which may be end points in the hierarchy. The data may be stored at a source pod. The request may identify a designated level in the hierarchy at which to relocate the source data. A target pod within the distributed database system may be selected. The source pod and the target pod may be located remotely from one another. The data may be replicated to the target pod via a local change bus in communication with the source pod. The local change bus may capture changes made to data stored in the source pod and transmit the captured changes to the target pod via the hierarchy.

Distributed database replication

Techniques are disclosed relating to processing data stored within database tables in a parallelized manner. In various embodiments, a computer system maintains a database having a database table storing data for a plurality of tenants and an index structure storing indexes for accessing data stored in the database table. In some embodiments, the computer system receives, from a particular tenant, a request to perform a task that includes operating on particular data. In some embodiments, the computer system determines a portion of the index structure corresponding to the particular tenant and divides a range of indexes within that portion into a plurality of index sub-ranges. In various embodiments, the computer system processes portions of the task in parallel by determining an index sub-range for each of a plurality of threads and causing each of the threads to operate on a portion of the particular data specified by its index sub-range.

Techniques for processing database tables using indexes

A staging table created in a database system may store a snapshot of live database table captured prior to an unintended change to the live database table. One or more entries in the staging table may be updated to incorporate one or more intended changes to the live database table that occurred after the unintended change. The live database table may be updated by merging each of the updated entries from the staging table to the live database table. The updated database table may eliminate the unintended change.

Branch-based recovery in a database system

A request may be received to migrate an organization from a first computing pod to a second computing pod located within an on-demand computing services organization configured to provide computing services. A migration resource utilization profile may be determined for the first computing pod. The migration resource utilization profile may identify one or more computing resources involved in transferring organizations from the first computing pod during one or more time windows. A migration time window for performing the requested migration may be selected based at least in part on the migration resource utilization profile.

In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamic hierarchical management of queue resources in an on-demand services environment in a multi-tenant environment according to one embodiment. In one embodiment and by way of example, a method includes assigning, in runtime, by the database system, weights to at least one of a plurality of tenants and a plurality of message types. The assigned weights are capable of being dynamically scaled, in runtime, based on one or more factors. The method may further include allocating, in runtime, by the database system, resources to one or more of the plurality of tenants and one or more of the plurality of message types based on their assigned one or more weights of the weights. The allocated resources are capable of being dynamically modified, in runtime, based on scaling of the assigned weights.

Facilitating dynamic hierarchical management of queue resources in an on-demand services environment

Methods and systems for providing a rewind of table data in a data management system include: storing a table having table data that defines a plurality of rows and a plurality of columns that define a plurality of cells; capturing change data associated with changes to at least one of the plurality of rows, the plurality of columns, and the plurality of cells; associating the change data with a transaction having a transaction identifier; storing the transaction and the change data in a change bus; retrieving the change data from the change bus based on a rewind request; performing a rewind of a subset of the changes by performing a reverse operation of the change data relating to the subset of changes and according to a reverse operation order; and outputting a clone of the table based on the rewind of the changes of the table.

Undo based logical rewind in a multi-tenant system

In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamic workload-aware shuffling of message types in message queues in an on-demand services environment in a multi-tenant environment according to one embodiment. In one embodiment and by way of example, a method includes monitoring, in runtime, workload patterns associated with incoming workloads, where each workload is associated with a plurality of message types and the plurality of message types are inspected and processed in a predetermined order. The method may further include collecting, in runtime, information regarding each message type based on a workload pattern of its associated workload, and dynamically shuffling the order based on the information, where shuffling includes ordering a first set of message types having one or more messages ahead of a second set of message types having fewer or no messages.

Facilitating workload-aware shuffling and management of message types in message queues in an on-demand services environment

Migration specific action requests to perform a set of migration specific actions are sent from a source system instance to a target system instance. Migration specific action responses are received from the target system instance. Based on the migration specific action responses, traffic lights for resource utilization of the target system instance are determined. Based on the traffic lights, a concurrency limit is determined for the specific time. The concurrency limit is applied to scale a total number of ongoing migration specific actions to be requested of the target system instance at the specific time.

Growing community of inventors

Dublin, CA, United States of America

Xiaodan Wang