International Business Machines Corporation

Daniel Martin

Andreas Brodt

Knut Stolze

Namik Hrle

Oliver Schiller

James D Spyker

Thomas F Boehme

Yongfeng Yao

Felix O Beier

Oliver Benke

Oliver Koeth

Ruiping Li

Vassil Radkov Dimov

Jens Mueller

Chandrasekaran Mohan

Einar Lueck

Sabine Perathoner-Tschaffler

Johannes S Kern

Sowmya Kameswaran

Manogari Nogi Simanjuntak

Peter Bendel

Maryela Evelin Weihrauch

Christian Michel

Matthias Tschaffler

Dennis Butterstein

Bjoern Broll

Jens Müller

Andreas Lohrer

Jia Heng Zhong

Oliver Draese

Sunil Sarin

Florian Braun

Christian Wilhelm Paul Hoerst

Christopher R G O'Quinn

Kevin Pelletier

Hao Zhang

Jing Chang Huang

Luis Eduardo Oliveira Lizardo

Liang Lu

Meng Guo

Jing F Fan

Eirini Kalogeiton

Björn Broll

Deng Ke Zhao

Mehmet Cuneyt Goksu

Patric Becker

Zhang Xiaowei

Thomas Immel

Huiyan Roy

An embodiment for archiving data in a data analysis system. The embodiment may receive a request to archive a source partition of a source table of source database system of the data analysis system. The embodiment may determine whether the source table is partitioned into partitions by ranges of an attribute of the source table. The embodiment may, in response to determining that the source table is partitioned by range, lock the source partition to prevent changes of the source partition. The embodiment may determine whether the source partition is synchronized with a corresponding partition in the target table. In response to determining that the source partition is synchronized with the corresponding partition in the target table, the embodiment may remove data in the source partition from the source table.

Archiving a table in a data analysis system

A method for processing an unsupported data type in a database is disclosed. The method for processing an unsupported data type in a database comprises detecting, while copying data from a primary to a secondary database, a table for data comprising a data type that is unsupported by the secondary database. Furthermore, the method comprises generating a base table in the secondary database as a copy of the detected table of the primary database without the data of the unsupported data type, generating an additional table in the secondary database for data of the unsupported data type, and linking the additional table to the base table in the secondary database via a row-identifier relationship. Additionally, the method comprises accessing data of the unsupported data type via the additional table while performing queries against the secondary database.

Large object data type support for column-based database system

A method for executing a query on a target database against the most recent source data is disclosed. The method comprises maintaining linked—i.e., at least partially synchronized—databases comprising a source and a target database. The method comprises receiving a direct query against a table in the target database, the query comprising a request for using the most recent source data and requesting by the target database from the source database a status about latest data regarding the table. Upon the status indicating that data in the table do not correspond to the most recent data, the method comprises waiting up to a predefined time period for the most recent data of the table to be synchronized from the source database to the target database, and upon the data of the table not being synchronized within the predefined time period, the method comprises issuing a timeout signal.

Query execution on a replicated database with most recent data

Technology for routing queries in a system with a plurality of nodes (for example online analytical processing sub-systems) where each node has an associated replicated local database and a local latency value and replication velocity values. The workload balancing for incoming received queries among and between the plurality of nodes is based, at least in part, on consideration of latency values and/or replication velocity values for the various nodes. The best node to handle a given query is thereby selected and the query is routed to the selected node for response.

Distribution of workloads among online analytics processing systems

In an approach, a processor receives a data manipulation request on a target database. A processor sends the data manipulation request to a source database. The source database attempts to persist a data manipulation action relating to the data manipulation request. Responsive to a successful attempt to persist the data manipulation action: the source database sends a log position of the data manipulation action to a data replication engine; a processor replicates the data manipulation request triggering the data manipulation action in the target database; and a processor confirms to the target database that the data manipulation action in the target database has been completed.

Bidirectional data replication with wait for data function

The present disclosure relates to a method for data synchronization between a source database system and target database system, wherein execution of a database transaction of the source database system is complete if a processing step followed by an application step of the database transaction is performed. For each identified database transaction, a processing step and/or application step may be performed.

Data synchronization between a source database system and target database system

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: receiving by primary database system a query statement that references a first table, wherein the primary database system is associated to a first accelerator database system and a second accelerator database system, wherein modifications performed on tables of the primary database system are iteratively replicated into the first accelerator database system and the second accelerator database system; examining latency data that specifies a latency with which a modification to the first table has been replicated into the first accelerator database system and a latency with which a modification to the first table has been replicated into the second accelerator database system; selecting, in dependence on the examining, the first accelerator database system for execution of the query statement; routing the query statement to the first accelerator database system for execution in response to the selecting.

Reduced latency query processing

In an approach, a primary data center is provided including primary source and primary target database systems, where a function is activated causing the primary target database system to: include a copy of data and receive analysis queries from the primary source database system; and execute the analysis queries on data. A processor, in response to detecting a failure in the primary source database system: offloads queries intended for the primary source database system to a secondary source database system of a secondary data center also including a secondary target database system and a copy of data, where the function is deactivated. A processor, responsive to the primary target database system being available: receives analysis queries, processed by the secondary source database system, of the offloaded queries; and copies data to the secondary target database system. A processor causes the function to be activated in the secondary data center.

Operating a data center

Embodiments of the present invention provide a method and system for processing a query on a set of data blocks in analytical databases. The query is on a set of data blocks, having at least one attribute and specifies at least one selection condition on the attribute. The selection condition is associated with at least one selection expression. Attribute value information on each attribute is generated for each data block. Next, a condition is generated on each attribute to negate the selection expression, if the selection expression has a negation operator. Additional conditions are generated for each selection expression that does not contain a negation operation. The attribute value is used to select the positive and negative subsets of data blocks for each condition. Next, a negative subset that does not require processing to evaluate the query is skipped and the positive subsets and the non-skipped negative subsets are processed.

Executing conditions with negation operators in analytical databases

Creating at a target database system, a target table and a history table each having a set of attributes of a source table in addition to at least one time attribute, wherein the time attribute of a record indicates the time when the record is valid. Receiving a request for applying a change of the source table to the target table. The request comprises a time value generated by the source database system indicating a time of the change. The change to the target table and the time value may be assigned to the time attribute of the current version and previous version of the record. The previous version of the record may be stored in the history table. The target table and the history table may be used to process a redirected query comprising a selection criterion on the time attribute.

Maintaining at a target database system a copy of a source table of a source database system

The present disclosure relates to a method for data replication in a data analysis system (). A source database system () of the data analysis system () comprises a transaction log () storing log records generated by database transactions. The method comprises in response to determining () that a received log record is generated by a database transaction that rolls back a change of another database transaction whose log records are buffered in at least one record buffer, data indicative of a log record generated by the other database transaction buffering () in the compensation buffer tag data. The tag data may be used () for replicating to a target database system of the data analysis system buffered log records of the record buffer which are not marked as compensation records.

Data replication in a data analysis system

A method, system and computer program product for copying data from a source database to a target database. A first database engine of the source database assigns a data-change-ID to each changed row in the source table. The data rows of the source table are stored in a plurality of source pages. Each source page comprises a source-page-ID and a highest-data-change-ID indicating its most recently changed data row. The target table comprises a source-page-ID-column. A second database engine of the target database maintains a metadata table comprising a source-page-ID column and a highest-data-change-ID column. The highest-data-change-IDs in the metadata table are compared with the highest-data-change-IDs of the source pages for selectively copying source table rows of source pages whose highest-data-change-ID is higher than their highest-data-change-ID in the metadata table to the target table.

Copying data changes to a target database

A method for deleting a row from a table in a database system comprises logically deleting the row in the first table in the database system by inserting a key of the row into a corresponding row of a dedicated table in the database system; querying the dedicated table during a query against the first table to identify the corresponding row in the dedicated table; and in response to identifying the corresponding row in the dedicated table, deleting the row from the first table and the corresponding row from the dedicated table as part of query processing during a subsequent query.

Deleting rows from tables in a database without an index

A computer-implemented method for operating a database management system which includes a source database and a target database. A database management system is configured for asynchronously replicating data changes of the source database to the target database. The database management system receiving a request to perform a database statement. The method can identify the most recently committed one of a plurality of transactions having been committed in the source database before the receiving of the request. Identifying repeatedly the one of the plurality of transactions having been replicated most recently to the target database. Execution of the requested statement in the target database is delayed until an evaluation of the repeatedly identified most recently replicated transaction returns that the identified most recently committed transaction has been replicated to the target database. After the delaying execution, the method executes the requested statement in the target database.

Database management system and method of operation

Approaches presented herein enable replicating data records between a source database and a target database. More specifically, for a batch of change records in a table received from the source database, a first estimated replication duration needed to apply the batch as a bulk change to the target is determined. For the same batch, a second estimated replication duration needed to apply a set of changes in a single row of the table to the target is determined based on time penalties for each column in the row. A threshold quantity of rows at which the first duration equals a summed total of second durations for the quantity is calculated. The bulk change is selected if a number of rows in the batch exceeds the threshold. Applying change records singly is selected if the number of rows in the batch is less than the threshold.

Dynamic selection of data apply strategy during database replication

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Stuttgart, Germany

Daniel Martin