Abstract: This application relates to a client-server architecture that enables file sharing between an instructor and a class. The files are stored in a storage service accessible via a network, and a separate copy of each file can be shared with each student in the class. In order to facilitate the sharing of multiple copies of the file, a share pool is created in a partition of the storage service allocated to the instructor. The share pool includes a number of stub files that are placeholders for clones of the shared file. A share handler service receives a request to share a file with a class, requests a number of stub files from the share pool, and utilizes the number of stub files to generate clones of the shared file in the partition of the storage service. Students are then granted access to the clones in the partition.

Abstract: This application relates to a client-server architecture that enables file sharing between an instructor and a class. The files are stored in a storage service accessible via a network, and a separate copy of each file can be shared with each student in the class. In order to facilitate the sharing of multiple copies of the file, a share pool is created in a partition of the storage service allocated to the instructor. The share pool includes a number of stub files that are placeholders for clones of the shared file. A share handler service receives a request to share a file with a class, requests a number of stub files from the share pool, and utilizes the number of stub files to generate clones of the shared file in the partition of the storage service. Students are then granted access to the clones in the partition.

Abstract: This application relates to load balancing for a number of partitions of a network-based storage service. Each partition includes a number of server devices and/or network devices located in a data center and configured to provide access to storage resources hosted within the data center. User accounts are assigned to a particular partition such that requests related to a particular user account are routed to that partition. Periodically, a load balancing algorithm is executed to re-assign user accounts to different partitions to rebalance resource consumption across the different partitions. The load balancing algorithm can balance resource consumption for any number of resource types by generating a vector of resource utilization parameters for each user account, sorting the plurality of user accounts into clusters based on the vectors, and mapping at least some user accounts to different partitions.

Abstract: A messaging system uses a cloud storage backup system for messages and a temporary storage for messages that are not deliverable to offline devices at the time that the messages are sent by one or more messaging servers. The messages are backed up through a synchronization process that transfers a batch of a plurality of messages rather than a single message or an entire database of messages. A conversation state can be synchronized first before synchronizing messages through the transfer of one or more batches of messages.

Abstract: Data items such as files or database records associated with particular applications (such as messaging applications and other applications) can be stored in one or more remote locations, such as a cloud storage system, and synchronized with other devices. The remote storage can be configured such that each application executing on a client device can only view data items stored at the remote location to which the application has permission to access. An access manager on each client device enforces application specific access policies. Storage at the remote location can be secured for each application associated with a user or user account, for example, using isolated containers. The cloud storage of data can be anonymized and anonymous group data can be stored in the cloud storage.

Abstract: A messaging system uses a cloud storage backup system for messages and a temporary storage for messages that are not deliverable to offline devices at the time that the messages are sent by one or more messaging servers. The messages are backed up through a synchronization process that transfers a batch of a plurality of messages rather than a single message or an entire database of messages. A conversation state can be synchronized first before synchronizing messages through the transfer of one or more batches of messages.

Abstract: Data items such as files or database records associated with particular applications (such as messaging applications and other applications) can be stored in one or more remote locations, such as a cloud storage system, and synchronized with other devices. The remote storage can be configured such that each application executing on a client device can only view data items stored at the remote location to which the application has permission to access. An access manager on each client device enforces application specific access policies. Storage at the remote location can be secured for each application associated with a user or user account, for example, using isolated containers. The cloud storage of data can be anonymized and anonymous group data can be stored in the cloud storage.

Abstract: A messaging system uses a cloud storage backup system for messages and a temporary storage for messages that are not deliverable to offline devices at the time that the messages are sent by one or more messaging servers. The messages are backed up through a synchronization process that transfers a batch of a plurality of messages rather than a single message or an entire database of messages. A conversation state can be synchronized first before synchronizing messages through the transfer of one or more batches of messages.

Abstract: This application relates to load balancing for a number of partitions of a network-based storage service. Each partition includes a number of server devices and/or network devices located in a data center and configured to provide access to storage resources hosted within the data center. User accounts are assigned to a particular partition such that requests related to a particular user account are routed to that partition. Periodically, a load balancing algorithm is executed to re-assign user accounts to different partitions to rebalance resource consumption across the different partitions. The load balancing algorithm can balance resource consumption for any number of resource types by generating a vector of resource utilization parameters for each user account, sorting the plurality of user accounts into clusters based on the vectors, and mapping at least some user accounts to different partitions.

Abstract: This application relates to a client-server architecture that enables file sharing between an instructor and a class. The files are stored in a storage service accessible via a network, and a separate copy of each file can be shared with each student in the class. In order to facilitate the sharing of multiple copies of the file, a share pool is created in a partition of the storage service allocated to the instructor. The share pool includes a number of stub files that are placeholders for clones of the shared file. A share handler service receives a request to share a file with a class, requests a number of stub files from the share pool, and utilizes the number of stub files to generate clones of the shared file in the partition of the storage service. Students are then granted access to the clones in the partition.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A set of operators on group-structured data enable creation of efficient execution plans. These operators are of two (2) distinct types. They operate similarly. For each row that matches an input row type, an hkey is obtained. The hkey uniquely identifies a table row within a table group. The hkey is transformed into a modified hkey associated with an output row type. Starting with a row of interest associated with the modified hkey, a table group is probed to identify one or more additional rows. As the additional rows are identified, they are written into an output stream.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.

Abstract: A database management system stores data form a plurality of logical tables as independent copies in different format. In one specific example the system organizes tables into table groups and de-normalizes the table in each table group. It also organizes data in a second format including vertical column containers that store all the data for one attribute, there being one column container for each table and each attribute within that table. The receipt of a query causes the system to develop a query plan that can interact with either or both of the container sets.