Download A Course in In-Memory Data Management: The Inner Mechanics by Hasso Plattner PDF

By Hasso Plattner

Recent achievements in and software program improvement, reminiscent of multi-core CPUs and DRAM capacities of a number of terabytes consistent with server, enabled the advent of a progressive know-how: in-memory information administration. This expertise helps the versatile and intensely quick research of huge quantities of firm facts. Professor Hasso Plattner and his examine staff on the Hasso Plattner Institute in Potsdam, Germany, were investigating and educating the corresponding innovations and their adoption within the software program for years.

This publication is predicated on an internet path that was once first introduced in autumn 2012 with greater than 13,000 enrolled scholars and marked the winning start line of the openHPI e-learning platform. The path is especially designed for college students of machine technological know-how, software program engineering, and IT comparable topics, yet addresses enterprise specialists, software program builders, know-how specialists, and IT analysts alike. Plattner and his team specialize in exploring the internal mechanics of a column-oriented dictionary-encoded in-memory database. lined subject matters contain - among others - actual info garage and entry, easy database operators, compression mechanisms, and parallel sign up for algorithms. past that, implications for destiny firm purposes and their improvement are mentioned. step-by-step, readers will comprehend the unconventional alterations and merits of the recent know-how over conventional row-oriented, disk-based databases.

In this thoroughly revised 2nd version, we comprise the suggestions of millions in fact members on openHPI and have in mind most up-to-date developments in difficult- and software program. more suitable figures, causes, and examples extra ease the knowledge of the recommendations offered. We introduce complicated facts administration ideas equivalent to obvious mixture caches and supply new showcases that show the opportunity of in-memory databases for 2 assorted industries: retail and existence sciences.

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Extra resources for A Course in In-Memory Data Management: The Inner Mechanics of In-Memory Databases

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Mudge, High-performance DRAMs in workstation environments. IEEE Trans. Comput. 50(11), 1133–1153 (2001) [Dre07] U. pdf [HP03] J. Hennessy, D. A. R. T. J. Hosseini, A novel zero-aware four-transistor SRAM cell for high density and low power cache application, in International Conference on Advanced Computer Theory and Engineering, 2008, ICACTE ’08, 2008, pp. 571–575 [Moo65] G. Moore, Cramming more components onto integrated circuits. Electronics 38, 114 ff. (1965) [SKP12] D. Schwalb, J. Krueger, H.

To identify signals in the proteome for cancer, multiple samples from different cohorts derived in clinical studies have to be compared, which adds selection and join operations to access cohort data from clinical information systems to the pipeline. Depending on the approach, the analysis pipeline for proteomics mass spectrum data represents a data-flow program, where each step applies mathematical transformations on the data flowing through the pipeline. g. different algorithms for minimization problems can be applied, or different model types for classifications can be embedded into the pipeline.

Current discount prices. In-memory database technology is used to conduct in-game trade promotions and, at the same time, conduct A/B testing. To this end, the gamers are divided into two segments. The promotion is applied to one group. Since the feedback of the users is analyzed in real-time, the decision to roll-out a huge promotion can be taken within seconds after the small test group accepted the promotion. Furthermore, in-memory technology improves discovery of target groups and testing of beta features, real-time prediction, and evaluation of advert placement.

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