By Hasso Plattner
-Presents the internal mechanics of an in-memory database
-Includes 34 studying devices with greater than a hundred self-tests and finished explanation
-Explains an important new develoment in firm computing
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 innovative expertise: in-memory information administration. This know-how helps the versatile and very quick research of big quantities of company info. Professor Hasso Plattner and his learn crew on the Hasso Plattner Institute in Potsdam, Germany, were investigating and instructing the corresponding recommendations and their adoption within the software program for years.
This e-book is predicated at the first on-line direction at the openHPI e-learning platform, which used to be introduced in autumn 2012 with greater than 13,000 inexperienced persons. The e-book is designed for college kids of machine technological know-how, software program engineering, and IT similar matters. although, it addresses company specialists, choice makers, software program builders, expertise specialists, and IT analysts alike. Plattner and his crew specialize in exploring the internal mechanics of a column-oriented dictionary-encoded in-memory database. coated themes 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 functions and their improvement are mentioned. Readers are bring about comprehend the unconventional changes and benefits of the recent expertise over conventional row-oriented disk-based databases.
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Extra resources for A Course in In-Memory Data Management
4 Self Test Questions 1. Lossless Compression For a column with few distinct values, how can dictionary encoding significantly reduce the required amount of memory without any loss of information? (a) By mapping values to integers using the smallest number of bits possible to represent the given number of distinct values (b) By converting everything into full text values. This allows for better compression techniques, because all values share the same data format. (c) By saving only every second value (d) By saving consecutive occurrences of the same value only once 2.
Here, the blocks only contain four elements for simplicity. 3 Cluster Encoding 47 Fig.
5 Prefetching Modern processors try to guess which data will be accessed next and initiate loads before the data is accessed in order to reduce the incurring access latencies. Good prefetching can completely hide the latencies so that the data is already in the cache when accessed. However, if data is loaded which is not accessed later it can also evict data which would be accessed later and thereby induce additional misses by loading this data again. Processors support software and hardware prefetching.
A Course in In-Memory Data Management by Hasso Plattner