Sap Se

Nosub Sung

Juchang Lee

Chang Gyoo Park

Chul Won Lee

Myunggon Park

Kyu Hwan Kim

Sung Heun Wi

Taehyung Lee

Deok Koo Kim

Kiyong Lee

Eunjin Song

Jaeyoung Choi

Jeong Hee Won

Chui Won Lee

Technologies are described for facilitating transaction processing in a distributed database environment. A database client sends database operations to a slave node, which mediates execution of the transaction. A connection between the database client and the slave node is associated with an identifier, and the transaction has an identifier. The database client sends a commit request to a master node over a network connection between the master node and the database client. The commit request includes the transaction identifier. The commit request can also include an indication of database nodes executing operations in the transaction.

Client-driven commit of distributed write transactions in a database environment

A process is provided for independently hashing and filtering a data set, such as during preprocessing. For the data set, one or more records, separately having one or more fields, may be identified. A record hash value set, containing one or more record hash values for the respective one or more records, may be generated. Generating a given record hash value may be accomplished as follows. For a given record, a hash value set may be generated, having one or more field hash values for the respective one or more fields of the given record. The record hash value for the given record may be generated based on the hash value set. A total hash value for the data set may be generated based on the record hash value set. The records of the data set may be filtered based on classification of the query that generated the records.

Order-independent multi-record hash generation and data filtering

Technologies are described for improving the performance of distributed database systems. The technologies provide suggested table distributions that can reduce the performance overhead associated with database operations that involve multiple nodes, and can provide more even distribution of computing resource use. In a particular example, a method includes minimizing a scoring function that includes a plurality of performance metrics, at least a portion of the metrics being associated with a weight. Candidate table distributions can be analyzed in an iterative manner to determine a lowest-score distribution. A final table distribution can be output, such as to a user.

Automatic determination of table distribution for multinode, distributed database systems

Technologies are described for facilitating transaction processing within a database environment that includes one or more processing units and a memory. A request for a database operation, such as a query, is received from a client. Execution statistics associated with the request are retrieved. At least some of the execution statistics are compared with one or more threshold values. Based on results of the comparing, the request is carried out with a first execution component or delegated to a second execution component. The request is executed and execution results are sent to the client.

Selective dispatching of OLAP requests using execution statistics

Improvements to the performance of distributed database systems are described. Suggested table distributions are provided that can reduce the performance overhead associated with database operations that involve multiple nodes, and can provide more even distribution of computing resource use. A method includes minimizing a cost function that includes a plurality of performance metrics, at least a portion of the metrics being associated with a weight. Candidate table distributions can be analyzed in an iterative manner to determine a lowest-cost distribution. A final table distribution can be output, such as to a user.

Technologies are described for facilitating replay of requests for database operations. A plurality of requests for database operations are received. Each of the plurality of requests includes a type, an access unit identifier, and a chronological identifier. Execution dependencies are determined between the plurality of requests based on the type, access unit identifier, and chronological identifier of each of the plurality of requests. The execution dependencies are stored.

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Nosub Sung