Native store extension for SAP HANA
| Autor: | Kandiyanallur Vivek, Pushkar Khadilkar, Reza Sherkat, Colin Florendo, Adrian Dragusanu, Yanhong Wang, Chaitanya Gottipati, Sebastian Seifert, Dheren Gala, Mihnea Andrei, Santosh Pendap, Christian Lemke, Nirvik Basak, Rolando Blanco, Rajesh Almeida, Sarika Iyer, Prasanta Ghosh, Amit Pathak, Neeraj Kulkarni, Robert Schulze, Sasikanth Gottapu |
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| Rok vydání: | 2019 |
| Předmět: |
Instruction prefetch
050101 languages & linguistics Computer science 05 social sciences General Engineering 02 engineering and technology Disk buffer computer.software_genre Partition (database) Column (database) Data access SAP HANA Encoding (memory) 0202 electrical engineering electronic engineering information engineering Operating system Memory footprint 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences computer |
| Zdroj: | Proceedings of the VLDB Endowment. 12:2047-2058 |
| ISSN: | 2150-8097 |
| DOI: | 10.14778/3352063.3352123 |
| Popis: | We present an overview of SAP HANA's Native Store Extension (NSE). This extension substantially increases database capacity, allowing to scale far beyond available system memory. NSE is based on a hybrid in-memory and paged column store architecture composed from data access primitives. These primitives enable the processing of hybrid columns using the same algorithms optimized for traditional HANA's in-memory columns. Using only three key primitives, we fabricated byte-compatible counterparts for complex memory resident data structures (e.g. dictionary and hash-index), compressed schemes (e.g. sparse and run-length encoding), and exotic data types (e.g. geo-spatial). We developed a new buffer cache which optimizes the management of paged resources by smart strategies sensitive to page type and access patterns. The buffer cache integrates with HANA's new execution engine that issues pipelined prefetch requests to improve disk access patterns. A novel load unit configuration, along with a unified persistence format, allows the hybrid column store to dynamically switch between in-memory and paged data access to balance performance and storage economy according to application demands while reducing Total Cost of Ownership (TCO). A new partitioning scheme supports load unit specification at table, partition, and column level. Finally, a new advisor recommends optimal load unit configurations. Our experiments illustrate the performance and memory footprint improvements on typical customer scenarios. |
| Databáze: | OpenAIRE |
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