By Hasso Plattner

Recent achievements in and software program improvement, akin to multi-core CPUs and DRAM capacities of a number of terabytes consistent with server, enabled the advent of a progressive expertise: in-memory information administration. This expertise helps the versatile and intensely quickly research of big quantities of firm facts. Professor Hasso Plattner and his study team on the Hasso Plattner Institute in Potsdam, Germany, were investigating and instructing the corresponding ideas and their adoption within the software program for years.

This ebook 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 place to begin of the openHPI e-learning platform. The path is principally designed for college students of computing device technological know-how, software program engineering, and IT similar topics, yet addresses enterprise specialists, software program builders, expertise specialists, and IT analysts alike. Plattner and his workforce concentrate on exploring the internal mechanics of a column-oriented dictionary-encoded in-memory database. coated issues comprise - among others - actual info garage and entry, easy database operators, compression mechanisms, and parallel sign up for algorithms. past that, implications for destiny firm functions and their improvement are mentioned. step-by-step, readers will comprehend the novel changes and benefits of the recent expertise over conventional row-oriented, disk-based databases.

In this thoroughly revised 2nd variation, we contain the suggestions of hundreds of thousands in fact contributors on openHPI and keep in mind most modern developments in challenging- and software program. more desirable figures, causes, and examples extra ease the knowledge of the recommendations offered. We introduce complex information administration strategies corresponding to obvious combination caches and supply new showcases that show the potential for in-memory databases for 2 different industries: retail and existence sciences.

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Additional info for A Course in In-Memory Data Management: The Inner Mechanics of In-Memory Databases

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Remote memory access on the other hand needs to be performed over a QPI (Quick Path Interconnect) controller coordinating the access. 3 Cache Internals Caches are organized in cache lines for management purposes. If the requested content cannot be located in any cache, it is loaded from main memory and transferred through the memory hierarchy to the registers. The smallest transferable unit between each level is one cache line. Caches where every cache line of level i is also present in level i C 1 are called inclusive caches.

For example, the HANA Oncolyzer, an application for physicians and researchers was designed for mobile devices. , the required patient data is available at any location on the hospital campus and the physician is no longer forced to go to a certain desktop computer for checking a certain aspect. In addition, if the required detail is not available in real-time for the physician, she/he will no longer use the application. Thus, all analyses performed by the in-memory database are running on a server landscape in the IT department while the mobile application is the remote user interface for it.

Information within these documents is typically identified via the document’s meta data. A detailed search within the content of these documents or the extraction of specific facts is however not possible by using the meta data. As a result, there is a need to harvest information buried within unstructured enterprise data. Searching any kind of data—structured or unstructured—needs to be equally flexible and fast. g. in hospitals, structured and unstructured data is generated. Examples of unstructured data are diagnosis reports, histologies, and tumor documentations.

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