Future Wei Technologies, Inc.

Couchbase, Inc.

Huawei Technologies Co., Limited

Kamini Jagtiani

Gangavara Prasad Varakur

Siew Sim-Tang

Yang Sun

Raghupathi Keshava Murthy

Sitaram Vemulapalli

Qingqing Zhou

Le Cai

Jason Yang Sun

Chunfeng Pei

Bai Yang

Jianjun Chen

Yuan Dai

Ye Liu

A distributed database system receives and executes a transaction including a first modification statement describing a first modification operation on a subset of records, a second modification statement describing a second modification operation on the subset of records, and a commit statement. Responsive to executing the first and second modification statements, the system receives a copy of the subset of records from data servers; performs the first modification operation to generate a first modified subset of records; and performs the second modification operation on the first modified subset of records. Responsive to executing the commit statement, the system stores the second modified subset of records in a commit table and causes the subset of records to be updated at the data servers.

Executing transactions on distributed databases

A computer-implemented method for performing application data consistency management among a plurality of computing devices within a communication network includes retrieving by a first device, application data from a second device. The application data includes an app ID and a first application version number of an app residing on the second device. A first database table is updated using an object type associated with the app ID and the first application version number. The object type identifies a database table schema of a data object used by the app and a plurality of data fields of the data object. Data stored by one or more of the plurality of data fields is synchronized with a third device based on a second application version number of the app residing on the third device and the first database table.

Multi-schema version support in data synchronization

A distributed database system executes transactions on a distributed database. A received transaction includes statements describing modifications of records stored in the distributed database. The distributed database system executes the transaction at a query server by obtaining copies of records corresponding to the statements of the transaction and performing the modifications specified by the statements of the transaction on the record copies. The distributed database system stores the modified record copies at the query server during execution of the transaction. After the transaction has successfully been executed at the query server, the distributed database system attempts to perform a commit process to update the records stored in the distributed database based on the modified record copies.

A device such as a data storage system comprises a non-transitory memory storage comprising instructions, and one or more processors in communication with the memory. The one or more processors execute the instructions to: map a different portion of data in a storage device to each of different caches, wherein each cache is in a computing node with a processor; change a number of the computing nodes; provide a modified mapping in response to the change; and pass queries to the computing nodes. The computing nodes can continue to operate uninterrupted while the number of computing nodes is changed. Data transfer between the nodes can also be avoided.

Separation of computation from storage in database for better elasticity

In one embodiment, a method for adding partitions to a massively parallel processing (MPP) cluster includes determining whether a first number of available nodes of a first leaf sub-cluster (LSC) of a meta sub-cluster (MSC) of the MPP cluster is greater than or equal to a second number of partitions of a table and assigning a first node of the first LSC to a first partition when the first number of available nodes is greater than or equal to the second number of partitions. The method also includes searching for a second LSC in the MSC when the first number of available nodes is less than the second number of partitions.

System and method for massively parallel processing database

In one embodiment, a method includes determining a number of initial servers in a massively parallel processing (MPP) database cluster and determining an initial bucket configuration of the MPP database cluster, where the initial bucket configuration has a number of initial buckets. The method also includes adding a number of additional servers to the MPP database cluster to produce a number of updated servers, where the updated servers include the initial servers and the additional servers and creating an updated bucket configuration in accordance with the number of initial servers, the initial bucket configuration, and the number of additional servers, where the updated bucket configuration has a number of updated buckets. Additionally, the method includes redistributing data of the MPP cluster in accordance with the updated bucket configuration.

System and method for massively parallel processor database

An embodiment method for massively parallel processing includes initiating a management instance on an initial machine, the management instance generating an initial partition corresponding to the initial machine, determining a total number of partitions desired for processing a database, the total number of partitions including the initial partition, determining a number of additional machines available to process the database, grouping the initial machine and the additional machines together in a pod, and launching the management instance on the additional machines in the pod to generate the total number of partitions desired for the database. Additional embodiment methods and an embodiment system operable to perform such methods are also disclosed.

System and method for flexible distributed massively parallel processing (MPP)

An embodiment method for massively parallel processing includes assigning a primary key to a first table in a database and a foreign key to a second table in the database, the foreign key of the second table identical to the primary key of the first table, determining a number of partition groups desired for the database, partitioning the first table into first partitions based on the primary key assigned and the number of partition groups desired, partitioning the second table into second partitions based on the foreign key assigned and the number of partition groups desired, and distributing the first partitions and the second partitions to the partition groups as partitioned. An embodiment system for implementing the embodiment methods is also disclosed.

System and method for flexible distributed massively parallel processing (MPP) database

A massively parallel processing (MPP) database can be re-partitioned/re-balanced while remaining on-line through a staged migration procedure. Staged migration may include a first stage and a second stage. During the first stage, entries in an existing partition are reallocated to the new partition, and the catalog is updated to associate the re-allocated entries with both the existing partition and the new partition such that queries for the re-allocated entries are directed toward the existing partition and the new partition. During the second stage, the re-allocated entries are migrated from the existing partition to the new partition, and after the migration is complete, the catalog is re-updated to associate the migrated entries with the new partition such that new queries are directed toward the new partition.

Growing community of inventors

Sunnyvale, CA, United States of America

Kamini Jagtiani