Auflistung nach Autor:in "May, Norman"
1 - 4 von 4
Treffer pro Seite
Sortieroptionen
- ZeitschriftenartikelManaged Query Processing within the SAP HANA Database Platform(Datenbank-Spektrum: Vol. 15, No. 2, 2015) May, Norman; Böhm, Alexander; Block, Meinolf; Lehner, WolfgangThe SAP HANA database extends the scope of traditional database engines as it supports data models beyond regular tables, e.g. text, graphs or hierarchies. Moreover, SAP HANA also provides developers with a more fine-grained control to define their database application logic, e.g. exposing specific operators which are difficult to express in SQL. Finally, the SAP HANA database implements efficient communication to dedicated client applications using more effective communication mechanisms than available with standard interfaces like JDBC or ODBC. These features of the HANA database are complemented by the extended scripting engine–an application server for server-side JavaScript applications–that is tightly integrated into the query processing and application lifecycle management. As a result, the HANA platform offers more concise models and code for working with the HANA platform and provides superior runtime performance.This paper describes how these specific capabilities of the HANA platform can be consumed and gives a holistic overview of the HANA platform starting from query modeling, to the deployment, and efficient execution. As a distinctive feature, the HANA platform integrates most steps of the application lifecycle, and thus makes sure that all relevant artifacts stay consistent whenever they are modified. The HANA platform also covers transport facilities to deploy and undeploy applications in a complex system landscape.
- TextdokumentPrecise, Compact, and Fast Data Access Counters for Automated Physical Database Design(BTW 2021, 2021) Brendle, Michael; Weber, Nick; Valiyev, Mahammad; May, Norman; Schulze, Robert; Böhm, Alexander; Moerkotte, Guido; Grossniklaus, MichaelToday's database management systems offer numerous tuning knobs that allow an adaptation of the database behavior to specific customer needs
- KonferenzbeitragSAP HANA – The Evolution of an In-Memory DBMS from Pure OLAP Processing Towards Mixed Workloads(Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) May, Norman; Böhm, Alexander; Lehner, WolfgangThe journey of SAP HANA started as an in-memory appliance for complex, analytical applications. The success of the system quickly motivated SAP to broaden the scope from the OLAP workloads the system was initially architected for to also handle transactional workloads, in particular to support its Business Suite flagship product. In this paper, we highlight some of the core design changes to evolve an in-memory column store system towards handling OLTP workloads. We also discuss the challenges of running mixed workloads with low-latency OLTP queries and complex analytical queries in the context of the same database management system and give an outlook on the future database interaction patterns of modern business applications we see emerging currently.
- KonferenzbeitragSQLScript: efficiently analyzing big enterprise data in SAP HANA(Datenbanksysteme für Business, Technologie und Web (BTW) 2035, 2013) Binnig, Carsten; May, Norman; Mindnich, TobiasToday, not only Internet companies such as Google, Facebook or Twitter do have Big Data but also Enterprise Information Systems store an ever growing amount of data (called Big Enterprise Data in this paper). In a classical SAP system landscape a central data warehouse (SAP BW) is used to integrate and analyze all enterprise data. In SAP BW most of the business logic required for complex analytical tasks (e.g., a complex currency conversion) is implemented in the application layer on top of a standard relational database. While being independent from the underlying database when using such an architecture, this architecture has two major drawbacks when analyzing Big Enterprise Data: (1) algorithms in ABAP do not scale with the amount of data and (2) data shipping is required. To this end, we present a novel programming language called SQLScript to efficiently support complex and scalable analytical tasks inside SAP's new main-memory database HANA. SQLScript provides two major extensions to the SQL dialect of SAP HANA: A functional and a procedural extension. While the functional extension allows the definition of scalable analytical tasks on Big Enterprise Data, the procedural extension provides imperative constructs to orchestrate the analytical tasks. The major contributions of this paper are two novel functional extensions: First, an extended version of the MapReduce programming model for supporting parallelizable user-defined functions (UDFs). Second, compared to recursion in the SQL standard, a generalized version of recursion to support graph analytics as well as machine learning tasks.