Systems and methods are disclosed for stateless stream handling and resharding. In one implementation, a first shard including one or more messages is generated. The first shard is associated with a first shard version attribute. The first shard and the first shard version attribute are provided as a first atomic update within a data stream. The first shard is resharded into at least a second shard. The second shard is associated with a second shard version attribute. The second shard and the second shard version attribute are provided as a second atomic update within the data stream.

A data partition storage system is provided. The system includes: a data analysis device, configured to determine, according to a data feature of target data comprised in a database, a heat level corresponding to the target data; and a database kernel, deployed on a target device different from the data analysis device to form the database, and configured to: acquire the heat level corresponding to the target data transmitted by the data analysis device; and store the target data in a storage area corresponding to the heat level.

A system and method for partitioned snapshot creation of caches in a distributed data grid is provided. The system and method enables a snapshot to be created in a running system without quiescing a cache service. Moreover for each particular partition, execution of read/write requests are not blocked during the period that a snapshot creation task is being performed for the particular partition. The cache service thread continues to execute read requests for all partitions with write requests for the partition under snapshot experiencing delayed response. The system and method reduces the period of time for which partitions are unavailable during a snapshot process and increases the availability of cache services provided by a distributed data grid compared to prior snapshot systems.

Techniques for ordering predicates in column partitioned databases for query optimization. Predicates on a single CP table within a query are organized to predicate-CP nodes with various sets of column partitions. The predicates within each predicate-CP node and the predicate-CP nodes as a whole are ordered in ascending order of cost which is determined by CPU/IO cost and predicate selectivity. The reorganized query is then executed.

The present disclosure relates to a digital asset synchronization system that provides improved local and remote synchronization of digital assets. In particular, the digital asset synchronization system manages digital assets by separating each digital asset into multiple components stored as a set of distributed individual files. Employing individual components for a digital asset rather than single monolithic file enables the digital asset synchronization system to provide safe concurrent access to the digital asset from multiple applications on the same device and across different devices. In addition, using components for a digital asset provides the digital asset synchronization system with the ability to efficiently store and synchronize multiple versions of the digital asset, both locally and remotely.

Systems, methods, and devices for offloading network data to a datastore. A system includes a publisher device in a network computing environment. The system includes a subscriber device in the network computing environment. The system includes a datastore independent of the publisher device and the subscriber device, the datastore comprising one or more processors in a processing platform configurable to execute instructions stored in non-transitory computer readable storage media. The instructions includes receiving data from the publisher device. The instructions include storing the data across one or more of a plurality of shared storage devices. The instructions include providing the data to the subscriber device.

Systems, methods, and computer program products are provided for load balancing for processing large data sets. The method includes identifying a number of segments and a transaction data set comprising transaction data for a plurality of transactions, the transaction data for each transaction of the plurality of transactions comprising a transaction value, determining an entropy of the transaction data set based on the transaction value of each transaction of the plurality of transactions, segmenting the transaction data set into the number of segments based on the entropy of the transaction data set and balancing respective entropies of each segment of the number of segments, and distributing processing tasks associated with each segment of the number of segments to at least one processor of a plurality of processors to process each transaction in each respective segment.

The present application relates to a data processing method and system of a distributed graph database. The present application solves the problem of how to improve the efficiency of adding, deleting, modifying and checking data in a graph database, realizes balanced storage and concurrent computing of distributed index, reduces network overhead caused by data operation, and improves the efficiency of data operation effectively.

Described are a system, method, and computer program product for reconfiguring a data table for processing on a server cluster. The method includes extracting a data table from a relational database and determining whether the data table includes a column having a range of values with a uniform distribution. The method also includes, in response to determining that the data table includes the column, classifying the column as a candidate column for splitting the data table. The method further includes, in response to determining that the data table does not include the column, inserting an index column into the data table and classifying the index column as the candidate column. The method further includes splitting the data table based on the candidate column and distributing each subdivision to a node of the server cluster so as to cause the server cluster to collectively process the data table.

Techniques of implementing partition level operations with concurrent activities are disclosed. A first operation can be performed on a first partition of a table of data. The first partition can be one of a plurality of partitions of the table, where each partition has a plurality of rows. A first partition level lock can be applied to the first partition for a period in which the first operation is being performed on the first partition, thereby preventing any operation other than the first operation from being performed on the first partition during the period the first partition level lock is being applied to the first partition. A second operation can be performed on a second partition of the table at a point in time during which the first operation is being performed on the first partition.