Abstract:
A system and method of logless atomic data movement. An internal transaction is started within a multi-level storage architecture, the internal transaction to merge data from the first level storage structure to the second level storage structure. Committed data is read from a first level storage structure of the multi-level storage architecture as specified by the internal transaction. The committed data from the first level storage structure is inserted into a second level storage structure in a bulk insertion process, and the committed data is marked as being deleted from the first level storage. The internal transaction is then committed to the multi-level storage architecture when the committed data has been inserted into the second level storage structure.
Abstract:
A method may include receiving a query for data to be provided by a database server, wherein the query includes an indication of a maximum lag. The method may further include determining whether a hint is available to apply to the query, wherein the hint affects an execution of the query. When no hint is available, a baseline database server may be selected to be the database server. When the hint is available, a replication server or a cache server may be selected to be the database server based on the hint and the maximum lag. The query may be processed at the selected database server.
Abstract:
Disclosed herein are system, method, and computer program product embodiments for efficiently providing transaction-consistent snapshots of data stored in or associated with a database stored within a database management system. An embodiment operates by receiving, at a source database, an update request to update a table at the source database and transmitting a message to a cache node to invalidate a copy of a table time stamp associated with the table, where the copy of the table time stamp is stored at the cache node. The embodiment continues by updating the table at the source database based on the update request.
Abstract:
Technologies are described for performing replication within a database environment. Where a database transaction is replicated at multiple replica nodes, a replica node is selected as a coordinator replica node for the transaction. The other replica node or nodes are designated as follower replica nodes for the transaction. A follower replica node sends the coordinator replica node a precommit notification when the follower replica node has precommitted the transaction. The coordinator replica node sends the follower replica node a postcommit notification to commit the transaction when the transaction has been precommitted by all of the replica nodes to which the transaction is to be replicated.
Abstract:
Technologies are provided for reducing or eliminating transaction consistency anomalies that can occur during data replication, such as during database table replication. For example, commit values can be used to coordinate requests so that the requests are not performed on database tables with inconsistent data.
Abstract:
Deleting a data record from the second level storage or main store is disclosed. A look-up is performed for the data record in the first level storage, where the data record is defined by a row identifier. If the row identifier is found in the first level storage, a look-up is performed for an updated row identifier representing an update of the data record in the second level storage and the main store, the update of the data record being defined by an updated row identifier. If the updated row identifier is found in the second level storage, an undo log is generated from the first level storage to invalidate a row identifier of the row identifier. A flag is generated representing an invalid updated row identifier, and a redo log is generated to restore the data record in the first level storage.
Abstract:
A system and method of query processing in a multi-level storage system having a unified table architecture. A query is received by a common query execution engine connected with the unified table architecture, the query specifying a data record. The common query execution engine performs a look-up for the data record based on the query at the first level storage structure. If the data record is not present at the first level storage structure, the common query execution engine performs separate look-ups in each of the second level storage structure and the main store.
Abstract:
A client computer establishes one or more sessions with a DBMS. Session context information for each session is cached in a client-side session cache. When a session disconnection is detected, the session recovery includes establishing a new session with the DBMS, and restoring the session context of the disconnected session from the session information of the disconnected session that is stored in the session cache.
Abstract:
Innovations in the area of server-side processing when committing transactions to disk in a distributed database system can improve computational efficiency at database nodes and/or reduce network bandwidth utilization. For example, when transactions are committed in a database system, at a master node of the database system, a server uses different threads for certain processor-intensive operations and certain I/O-intensive operations.
Abstract:
Technologies are described for routing structured query language (SQL) statements to elastic compute nodes (ECNs) using workload classes within a distributed database environment. The elastic compute nodes do not store persistent database tables. For example, a SQL statement can be received for execution within the distributed database environment. A workload class can be identified that matches properties of the SQL statement. Based on the workload class, a routing location hint can be obtained that identifies a set of elastic compute nodes. The SQL statement can then be routed to one of the identified elastic compute nodes for execution. Execution of the SQL statement at the elastic compute node can involve retrieving database data from other nodes which store persistent database tables.