Sap Se

Edward-Robert Tyercha

Gerrit Simon Kazmaier

Hinnerk Gildhoff

Lars Volker

Tim Grouisborn

Isil Pekel

Martin Heidel

Christian Bensberg

Lars Fricke

Reiner Singer

Andreas Tonder

Joern Schmidt

Janardhan Hungund

Thomas Theodor Koetter

Holger Bischoff

Deepak Shrivastava

Thomas Simenec

Juchang Lee

Computer-implemented methods, systems and products, the method comprising receiving, at a data server associated with a database, a command for data transfer between a client machine and the data server over a communications network, the data being stored in at least a data table comprising one or more columns; in response to receiving the command for data transfer, determining whether one or more columns of the data table are designated; identifying the one or more designated columns, such that data associated with the one or more designated columns is either considered or not considered for purpose of the data transfer; and executing the command to transfer the data in the database according to the designated columns.

Data transfer in a computer-implemented database

A computer implemented method for monitoring databases includes providing views for monitoring information associated with a first datacenter and proxy views for monitoring information associated with a second datacenter. The first datacenter receives a query for monitoring information and parses the query to identify filter information that identifies which of the first or second datacenter the requested services are running on. If the filter information indicates the service is running on the first datacenter, the first datacenter queries the views to request the monitoring information from the server on the first datacenter running the requested service. If the filter information indicates the service is running on the second datacenter, the first datacenter queries the proxy views to request the monitoring information from the server on the second datacenter running the requested service, and receives the monitoring information. Related apparatus, systems, techniques and articles are also described.

Proxy views for extended monitoring of database systems

Disclosed herein are system, method, and computer program product embodiments for performing database processing after a lock condition. An embodiment operates by receiving a release of a lock on data of a database. It is determined whether the data was modified by a processing of a first transaction associated with the first request. The lock is provided to a second transaction associated with a second request to access the data. If the first transaction did not modify the data, a second transaction associated with the second request is retried without refreshing a snapshot of the data. If the first transaction modified the data, the snapshot of the data is refreshed before the second transaction is retried.

Database processing after a lock condition

A first store and a second store can be configured to store a first partition of a table of a database and a second partition of the table of the database, respectively. A database management system can be configured to at least update at least a first portion of the first partition where the update includes an update to a first primary key column in the first partition and verify that the first primary key column is unique across the first partition and the second partition. A first row having a first primary key value of the first primary key column from the first partition can be deleted, when the first primary key value in the first partition conflicts with a second primary key value of a second primary key column in the second partition.

Synchronized updates across multiple database partitions

An update to a partitioning column for a partitioned table in a database can be performed by handling rows for which the update will not require moving to a different partition separately (e.g. 'locally') for each partition followed by re-inserting those rows that will require moving to a different partition and deleting them from the original partition. The re-inserted rows are directed to a correct partition by application of the partitioning criteria for the table. Methods, articles, and systems are described.

Updating a partitioning column

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a minimal bounding rectangle associated with the query is identified using a grid order scanning technique. The spatial data set corresponding to the received query is then mapped to physical storage in the database using the identified minimal bounding rectangle so that the spatial data set can be retrieved. Related apparatus, systems, techniques and articles are also described.

Querying spatial data in column stores using grid-order scans

DBSCAN clustering analyses can be improved by pre-processing of a data set using a Hilbert curve to intelligently identify the centers for initial partitional analysis by a partitional clustering algorithm such as CLARANS. Partitions output by the partitional clustering algorithm can be process by DBSCAN running in parallel before intermediate cluster results are merged.

Hilbert curve partitioning for parallelization of DBSCAN

A query of spatial data is received by a database comprising a columnar data store storing data in a column-oriented structure. Thereafter, a minimal bounding rectangle associated with the query is identified using a tree-order scanning technique. A spatial data set that corresponds to the received query is then mapped to the physical storage in the database using the identified minimal bounding rectangle. Next, the spatial data set is then retrieved. Related apparatus, systems, techniques and articles are also described.

Querying spatial data in column stores using tree-order scans

Using index clusters to approximate coordinate values for vertices of compressed simplexes of a spatial data set, valid subspaces can be identified and used to identify other simplexes that may intersect a first simplex. Such approaches can be used for filtering, refining, etc. analysis of intersections between areas, lines, volumes, etc. within spatial data sets.

Column store optimization using simplex store

Cluster analysis of data points in a data set can be optimized by identification of a preferred cluster analysis method. This identification can be based on indexing the data using a Hilbert curve and determining whether the data points are predominantly in spherical or non-spherical clusters. Methods, systems, and articles of manufacture are described.

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Heidelberg, Germany

Edward-Robert Tyercha