Processing of data chunks using a database calculation engine

    公开(公告)号:US10255316B2

    公开(公告)日:2019-04-09

    申请号:US14945339

    申请日:2015-11-18

    Applicant: SAP SE

    Abstract: A database server receives a request to perform a primary query on a table of a database. A first table query can be generated and can include a starting row identifier, ROW A, and a number of rows, n, for generating a data chunk from the table of the database. Multiple table queries can be performed each having a different starting row identifier and each defining the number of rows forming a data chunk. The primary query can be extended with the first table query in preparation for performing the primary query on the first data chunk.

    FIRST/LAST AGGREGATION OPERATOR ON MULTIPLE KEYFIGURES WITH A SINGLE TABLE SCAN

    公开(公告)号:US20170147636A1

    公开(公告)日:2017-05-25

    申请号:US14947627

    申请日:2015-11-20

    Applicant: SAP SE

    Abstract: Methods and apparatus, including computer program products, are provided for first and last aggregation. In one aspect, there is provided a method, which may include receiving, by a calculation engine, a query; detecting, by the calculation engine, whether the query includes a first aggregation and/or a last aggregation over at least one group and at least one keyfigure; optimizing the received query, when the detecting indicates the received query includes the first aggregation and/or the last aggregation, wherein the optimizing further comprises initiating execution of the received query by at least: performing a single read of a table, detecting, from the single table read, at least one group, and indicating, in the detected at least one group, the first aggregation in the at least one keyfigure and/or the last aggregation in the at least one keyfigure; and returning, for the at least one detected group, the indicated first aggregation and/or the indicated second aggregation. Related apparatus, systems, methods, and articles are also described.

    Database Calculation Engine With Nested Multiprovider Merging
    14.
    发明申请
    Database Calculation Engine With Nested Multiprovider Merging 审中-公开
    数据库计算引擎与嵌套多重编译器合并

    公开(公告)号:US20160350374A1

    公开(公告)日:2016-12-01

    申请号:US14723205

    申请日:2015-05-27

    Applicant: SAP SE

    CPC classification number: G06F17/30466

    Abstract: A query is received by a database server from a remote application server that is associated with a calculation scenario that defines a data flow model including one or more calculation nodes including stacked multiproviders. Subsequently, the database server instantiates the calculation scenario and afterwards optimizes the calculation scenario. As part of the optimization, the calculation scenario is optimized by merging the two multiproviders. Thereafter, the operations defined by the calculation nodes of the optimized calculation scenario can be executed to result in a responsive data set. Next, the data set is provided to the application server by the database server.

    Abstract translation: 来自远程应用服务器的数据库服务器接收到查询,该远程应用程序服务器与定义包括一个或多个计算节点(包括堆叠的多维数据集)的数据流模型的计算方案相关联。 随后,数据库服务器实例化计算方案,然后优化计算方案。 作为优化的一部分,通过合并两个多维数据集优化计算方案。 此后,可以执行由优化的计算场景的计算节点定义的操作以产生响应数据集。 接下来,由数据库服务器将数据集提供给应用服务器。

    Partition aware partial query processing

    公开(公告)号:US11455308B2

    公开(公告)日:2022-09-27

    申请号:US15354852

    申请日:2016-11-17

    Applicant: SAP SE

    Abstract: Described herein includes a calculation scenario of a calculation engine that efficiently partitions data for processing at separate hosts, including in parallel, and unions intermediate results from such separate processing when required for further processing. Such parallel processing of partitions can allow for faster processing times, and such unioning of data only when required for further processing can limit the transferring of data that results in slower processing.

    Ranking filter operation for calculation scenarios

    公开(公告)号:US11372863B2

    公开(公告)日:2022-06-28

    申请号:US16711141

    申请日:2019-12-11

    Applicant: SAP SE

    Abstract: A calculation engine of a database management system is described. The calculation engine may receive a query associated with a calculation scenario that defines a data flow model. The data flow model may include one or more calculation nodes, each of which corresponding to an operation performed on one or more database tables stored at a database. The one or more calculation nodes may include at least one calculation node corresponding to a ranking filter operation. The calculation engine may execute the query including by executing the calculation scenario. The executing of the calculation scenario may include performing the ranking filter operation to generate a result corresponding to at least a portion of rows included in a first partition of a database table stored at the database. Related systems, methods, and articles of manufacture are provided.

    Integration of relational calculation views into a relational engine

    公开(公告)号:US10831784B2

    公开(公告)日:2020-11-10

    申请号:US15150365

    申请日:2016-05-09

    Applicant: SAP SE

    Abstract: A calculation engine of a database management system is described. In some implementations, the calculation engine receives a calculation scenario including a plurality of calculation views comprising one or more relational operations. The calculation engine determines whether a first calculation view includes a second calculation view configured as an operand of one of the relational operations of the first calculation view, and also determines whether the second calculation view comprises a non-relational operation. The calculation engine further converts the plurality of calculation views into a calculation plan via merging the first calculation view with the second calculation view when the first calculation view is determined to comprise the second calculation view as an operand, and replacing the second calculation view with a view search operation when the second calculation view is determined to comprise the non-relational operation. Related systems, methods, and articles of manufacture are also described.

    Calculation engine optimizations for join operations utilizing automatic detection of forced constraints

    公开(公告)号:US10713244B2

    公开(公告)日:2020-07-14

    申请号:US15150371

    申请日:2016-05-09

    Applicant: SAP SE

    Abstract: A calculation engine of a database management system is described. In some implementations, the calculation engine receives a calculation scenario including a plurality of join operations defining an intersection between at least two nodes. The calculation engine optimizes a first join which is of a certain cardinality, and for which no attributes are requested, other than a join attribute. The optimization includes determining whether a static filter is present for a first node or a second node of the first join, and pruning the first node and/or the second node from the hierarchical join when the attribute is not requested from the first node or the second node and/or when the static filter is not present for the first node or the second node. Related systems, methods, and articles of manufacture are also described.

    FILTER AND JOIN OPERATIONS IN QUERY PROCESSING

    公开(公告)号:US20190311059A1

    公开(公告)日:2019-10-10

    申请号:US15945605

    申请日:2018-04-04

    Applicant: SAP SE

    Abstract: Described herein includes a calculation scenario of a calculation engine that efficiently filters and joins data for processing. The calculation engine enhances the performance of the join operations by allowing join inputs to be pre-filtered more effectively. Such join operations can allow for faster processing times, and a reduction in the amount of data to be joined, resulting in more efficient processing.

    PARTITION AWARE PARTIAL QUERY PROCESSING
    20.
    发明申请

    公开(公告)号:US20190311058A1

    公开(公告)日:2019-10-10

    申请号:US15945022

    申请日:2018-04-04

    Applicant: SAP SE

    Abstract: Described herein includes a calculation scenario of a calculation engine that efficiently partitions data for processing at separate hosts, including in parallel, and unions intermediate results from such separate processing when required for further processing. Such parallel processing of partitions can allow for faster processing times, and such unioning of data only when required for further processing can limit the transferring of data that results in slower processing.

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