A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

Example systems, apparatus, and methods receive audio information including a plurality of frames from a source device, wherein each frame of the plurality of frames includes one or more audio samples and a time stamp indicating when to play the one or more audio samples of the respective frame. In an example, the time stamp is updated for each of the plurality of frames using a time differential value determined between clock information received from the source device and clock information associated with the device. The updated time stamp is stored for each of the plurality of frames, and the audio information is output based on the plurality of frames and associated updated time stamps. A number of samples per frame to be output is adjusted based on a comparison between the updated time stamp for the frame and a predicted time value for play back of the frame.

Systems and methods are provided for master-to-master OT-based artifact peering. A “master-to-master” architecture for artifacts is implemented in a network comprising a plurality of nodes and clients, where no node is designated a “master” or “primary” for a given artifact. A first node receives a subset of remote proposed operations from a second node and determines if a conflict exists between the received subset of remote proposed operations and at least one of a plurality of locally-proposed operations. The first node resolves the conflict based on a total-ordering agreed upon between the first node and the second node. The first node transforms at least one operation, either received or locally-proposed, based on the resolved conflict. The first node than updates a local log to include the transformed operation.

The cloud hybrid application storage management system spans local data center and cloud-based storage and provides a unified view of content and administration throughout an enterprise. The system manages synchronization of storage locations, ensuring that files are replicated, uniquely identified, and protected against corruption. The system ingests digital media assets and creates instances of the assets with their own identification and rights and houses the identification and relationships in a CAR (Central Asset Registry). The system tracks the different instances of the assets in multiple storage locations using the CAR, which is a central asset registry that ties together disparate digital asset management repository systems (DAMs) and cloud-based storage archives in which the instances reside. While the invention treats and manages multiple files/instances independently, the CAR identifies them as related to each other.

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

In the present invention, a management system has a storage device and a processor. The storage device holds an information processing program for controlling information pertaining to a storage system by utilizing a database. The processor executes an update program that updates the information processing program and the database utilized by the information processing program. The update program calculates an estimated update time needed to update the information processing program and the database on the basis of the size of at least a portion of the database utilized by the information processing program before being updated and the structure of the database utilized by the information processing program after being updated, and outputs the estimated update time thus calculated.

Streaming data, such as streaming records transmitted from entities, can be managed. For example, a new record associated with an entity can be received. There can be an existing record for the entity within a group of records. The group of records can form a block. A new block for the new record can be generated. A datastore can be updated to indicate that the new block has the most current record for the entity. Entries in the datastore can be filtered to identify a subgroup of blocks that has the most current record for each entity of multiple entities. A combined group of blocks can be generated by joining the new block with the subgroup of blocks. The combined group of blocks can be processed as a batch of data by a processing engine.

In a distributed database, a transaction is to be committed at a first coordinator server and one or more participant servers 1210. The first coordinator server is configured to receive a notification that each participant server of the transaction is prepared at a respective prepared timestamp, the respective prepared timestamp being chosen within a time range for which the respective participant server obtained at least one lock 1220. The first coordinator server computes the commit timestamp for the transaction equal or greater than each of the prepared timestamps 1230, and restrict the commit timestamp such that a second coordinator server sharing at least one of the participant servers for one or more other transactions at a shared shard cannot select the same commit timestamp for any of the other transactions 1240. The transaction is committed at the commit timestamp 1250.

Example distributed storage systems, delete managers, and methods provide for managing dependent delete operations among data stores. Dependent data operation entries and corresponding dependency sets may be identified in an operations log. Dependent data operations may be identified in each shard and data operation entries. A delete process for the data objects in the dependency set may be delayed until the delete process for the dependent data object completes.

A database system receives a query and determines that the query includes an inner join between a parent table and a child table. The database system determines that the following relationships exists between the parent table and the child table: referential integrity (“RI”) between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table and a temporal relationship constraint (“TRC”) between a period attribute in the parent table and a TRC-attribute in the child table. The database system determines that the query satisfies non-temporal join elimination conditions and temporal join elimination conditions and that the query contains no other qualification conditions on the parent table's period attribute and eliminates the inner join when planning execution of the query.