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, resembling multi-core CPUs and DRAM capacities of a number of terabytes in line with server, enabled the creation of a innovative expertise: in-memory information administration. This expertise helps the versatile and very quick research of huge quantities of firm info. Professor Hasso Plattner and his examine team on the Hasso Plattner Institute in Potsdam, Germany, were investigating and educating the corresponding suggestions and their adoption within the software program for years.

This publication is predicated on an internet direction that used to be first introduced in autumn 2012 with greater than 13,000 enrolled scholars and marked the profitable start line of the openHPI e-learning platform. The path is especially designed for college kids of machine technological know-how, software program engineering, and IT similar topics, yet addresses enterprise specialists, software program builders, know-how specialists, and IT analysts alike. Plattner and his workforce specialize in exploring the internal mechanics of a column-oriented dictionary-encoded in-memory database. coated subject matters comprise - among others - actual info garage and entry, simple database operators, compression mechanisms, and parallel sign up for algorithms. past that, implications for destiny company functions and their improvement are mentioned. step-by-step, readers will comprehend the unconventional ameliorations and merits of the hot know-how over conventional row-oriented, disk-based databases.

In this thoroughly revised 2nd version, we include the suggestions of hundreds of thousands in fact contributors on openHPI and take note of most up-to-date developments in not easy- and software program. enhanced figures, causes, and examples extra ease the certainty of the options provided. We introduce complicated facts administration options reminiscent of obvious combination caches and supply new showcases that display the potential for 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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This assumption still holds true till today. 3 Cache Internals 25 Intel Multi-Core Core 0 Intel Multi-Core Core 1 Core N Core N TLB Core 1 Core 0 TLB L1 Cache Line L1 L1 L2 Cache Line L2 L2 L3 Cache Line Memory Page L3 Cache QPI Main Memory QPI L3 Cache Main Memory Fig. 1 Memory hierarchy on Intel Ivy Bridge-EX act as an intermediate layer to buffer frequent accesses to the slower main memory built of DRAM cells. This concept is commonly implemented in the form of multilevel caches where data needs to traverse the different levels of caches characterized by increasing speed and decreasing size to the CPU registers to be used as input for instructions.

G. to detect messages about a new product, competitor activities, or to prevent service abuses. g. sales campaigns or seasonal weather details, market trends for certain products or product classes can be derived. g. for marketing campaigns or even to control the manufacturing rate. Another example for extracting business relevant information from the Web is monitoring search terms. The search engine Google analyzes regional and global search trends. For example, searches for “influenza” and flu related terms can be interpreted as a indicator for a spread out of the influenza disease.

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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