By Hasso Plattner
Recent achievements in and software program improvement, comparable to multi-core CPUs and DRAM capacities of a number of terabytes consistent with server, enabled the creation of a innovative expertise: in-memory facts administration. This expertise helps the versatile and very speedy research of big quantities of firm info. Professor Hasso Plattner and his study crew on the Hasso Plattner Institute in Potsdam, Germany, were investigating and educating the corresponding recommendations and their adoption within the software program for years.
This publication is predicated at the first on-line path at the openHPI e-learning platform, which was once introduced in autumn 2012 with greater than 13,000 novices. The booklet is designed for college students of machine technology, software program engineering, and IT similar matters. despite the fact that, it addresses company specialists, determination makers, software program builders, expertise specialists, and IT analysts alike. Plattner and his staff specialize in exploring the interior mechanics of a column-oriented dictionary-encoded in-memory database. coated issues contain - among others - actual facts garage and entry, easy database operators, compression mechanisms, and parallel sign up for algorithms. past that, implications for destiny company purposes and their improvement are mentioned. Readers are bring about comprehend the unconventional ameliorations and merits of the hot expertise over conventional row-oriented disk-based databases.
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Extra resources for A Course in In-Memory Data Management: The Inner Mechanics of In-Memory Databases
Sample text
This can be easily done by comparing the tags of the Ai cache lines in the set in parallel. 4 Address Translation The operating system provides each process a dedicated continuous address space, containing an address range from 0 to 2x . This has several advantages as the process can address the memory through virtual addresses and does not have to bother about the physical fragmentation. Additionally, memory protection mechanisms can control the access to memory, restricting programs to access memory which was not allocated by them.
In our tiny example, the value ‘‘John’’ can be found twice in the column ‘‘fname’’, namely on position 39 and 42. Using dictionary encoding, the long text value (we assume 49 Byte per entry in the first name column) is represented by the short integer value (23 bit are needed to encode the 5 million different first names we assume to exist in the world). The more often identical values appear, the greater the benefits. As we noted in Sect. 6, enterprise data has low entropy. For this, dictionary encoding is well suited and grants a good compression ratio.
5 Architecture Overview The architecture shown in Fig. 1 grants an overview of the components of SanssouciDB. SanssouciDB is split in three different logical layers fulfilling specific tasks inside the database system. The ‘‘Distribution Layer’’ handles the communication to applications, creates query execution plans, stores meta data contains the logic for database transactions. Inside the main memory of a specific machine the main working set of SanssouciDB is located. That working set is accessed during query execution and is stored either in row, column or hybrid-oriented data layout, depending on the specific type of queries sends to the database tables.