Alibaba Group Holding Limited

Ant Financial (hang Zhou) Network Technology Co., Ltd.

Beijing Oceanbase Technology Co., Ltd.

Advanced New Technologies Co., Ltd.

Ant Financial Network Technology Co., Ltd.

Zhenkun Yang

Yuzhong Zhao

Jinliang Xiao

Huabing Du

Fusheng Han

Zhiyong Jiang

Wenhui Shi

Yangjun Ma

Yi Zhang

Hao Liu

Hu Xu

Gui Huang

Mingqiang Zhuang

Zhidong Sun

Hongdi Luo

Implementations of this specification provide methods and apparatuses for generating index entries. One method includes: acquiring a first sequence number of front large object data that is adjacent to a target data to be inserted in a large object data, wherein the first sequence number is generated based on a first code arrangement sequence and is comprised in a first index entry corresponding to the front large object data, in response to determining that the second sequence number immediately following the first sequence number is occupied, determining, based on a second code arrangement sequence, a branch index sequence number for the target data, and adding an index entry comprising the branch index sequence number to an index of the large object data, wherein the index entry is added between the first index entry comprising the first sequence number and a second index entry comprising the second sequence number.

Index entry generating methods, apparatuses, and devices for large object data block index

The present specification describes an adaptive resource allocation method and apparatus. One example method includes determining a request time, an execution time, and a response time corresponding to a service statement executed by the database system during a time period, wherein the request time is a time at which the service statement was executed by the database system, the execution time is an amount of time allocated for execution of the service statement by the database system, and the response time is an amount of time that elapsed between the request time and a time at which execution of the service statement ended; identifying a time segment of the time period based on the request time; determining a service type associated with the service statement; and updating a resource quota for the time segment based on the service type, the execution time, and the response time for the service statement.

Adaptive resource allocation method and apparatus

A data modification request for modifying data in a primary database is received at the primary database. Based on the data modification request, second data in the primary database is modified to first data. Based on the data modification request, a first log and a second log are generated, where the first log is a simplified log including the first data and the second log is a complete log including the second data. Persistence processing is performed on the first log. A modification result that corresponds to the data modification request is returned.

Database data modification request processing

A same voting time, a same vote counting time, and a same leader node tenure is configured by a host for all nodes. Time configuration information including the same configured voting time, the same vote counting time, and the same leader node tenure, is sent to all the nodes. The nodes are operable to vote during the same voting time, count the number of votes during the same vote counting time, and elect a leader node according to a vote counting result. The nodes are enabled to perform periodic node election according to the same leader node tenure.

Efficient, time-based leader node election in a distributed computing system

Embodiments provide a data block storage method applied to a database employing an LSM tree. According to the method, data in the 0layer of the LSM tree is organized in MacroBlocks. When the data in the LSM tree is transferred from an upper layer to a lower layer, the data is transferred to the lower layer in the form of MacroBlocks, so that all layers of the LSM tree are organized in the form of MacroBlocks. When inter-layer data merger is performed, the merger may be performed based on the MacroBlocks, which can avoid rewriting of all data on an entire layer and can effectively reduce disk IO and temporary space consumption. Moreover, as each MacroBlock comprises a plurality of variable-length MicroBlocks, the data may be stored in a storage space in a more compact manner.

Data block storage method and apparatus, and electronic device

The present disclosure relates to a data unit reuse method, where data is stored in a data unit in the form of a data block and the data block has a block ID. The method includes: successively reading each data block in a current data unit to search for a first specific data block whose block ID does not conform to a predetermined order; determining whether at least one data block whose block ID conforms to the predetermined order exists after the specific data block in the current data unit; when it exists, determining that the current data unit has been damaged, and when it does not exist, determining that a data block immediately previous to the specific data block is a data end.

Efficient data unit reuse method and system

One example method includes receiving, by the one or more processors, a request to update data stored on a distributed data storage system that comprises a primary server and a plurality of secondary servers, the request comprising data updates; sending, by the one or more processors, an update log instruction to the primary server and the plurality of secondary servers so that each of the primary server and the plurality of secondary servers records a log associated with the request; determining, by the one or more processors, that the log has been recorded; and in response to determining that the log has been recorded, sending, by the one or more processors, a data storage instruction to the primary server and a secondary server of the plurality of secondary servers so that each of the primary server and the secondary server stores the data updates.

Storing data in distributed systems

Example control methods of hybrid storage are provided, which are applied to each HDD-type storage device and each SSD-type storage device in a storage system having one or more HDD-type storage devices and one or more SSD-type storage devices. Each HDD-type storage device in the storage system is connected to the SSD-type storage device. Each HDD-type storage device and each SSD-type storage device stores one or more data blocks respectively. Access information of each data block stored in a storage device is periodically acquired. A storage location of each data block in the storage system is adjusted according to the acquired access information of each data block. By using the technical solution of the present disclosure, the storage location of the data block is dynamically configured according to an access frequency so that advantages of different storage devices are fully utilized.

Control of storage of data in a hybrid storage system

The present application describes techniques for managing primary and secondary databases. One example method includes determining whether a lock held by a primary database expires, wherein the primary database and the secondary databases share the lock; in response to determining that the lock held by the primary database has expired, determining whether a lock renewal request of the primary database has been received; and in response to determining that the lock renewal request of the primary database has not been received, selecting a particular secondary database from the secondary databases as a new primary database, and controlling the primary database to be switched to the particular secondary database.

Method, system and apparatus for managing primary and secondary databases

One embodiment of the present invention provides a system for facilitating dynamic load-based merging. During operation, the system identifies incremental data in memory of a first computing device. The incremental data comprises update to reference data in a storage device in a second computing device. If the size of the incremental data becomes greater than a threshold, the system selects a first server group from a plurality of server groups. The second computing device belongs to this first server group. The system then migrates data access requests from the first server group to other server groups in the plurality of server groups and merges the incremental data from the memory of the first computing device to the storage device in the second computing device. The merging includes batch sequential disk writes to the storage device of the second computing device.

Growing community of inventors

Hangzhou, China

Zhenkun Yang