Martin Kleppmann's Designing Data-Intensive Applications: The Big Ideas Behind PDF

By Martin Kleppmann

ISBN-10: 1449373321

ISBN-13: 9781449373320

This ebook examines the main rules, algorithms, and trade-offs of information platforms, utilizing the internals of assorted renowned software program programs and frameworks as examples. You’ll be certain what sort of instrument is acceptable for which function, and the way sure instruments may be mixed to shape the root of an outstanding software structure. You’ll easy methods to enhance an instinct for what your platforms are doing, in order that you’re greater in a position to music down any difficulties that come up. utilizing hundreds and hundreds of illustrations and a sublime intuitive modeling language, the authors current a strategy that absolutely exploits the conceptual modeling technique of software program engineering, from thought to software. Readers will research not just the way to harness the layout applied sciences of relational databases to be used on the internet, but in addition tips on how to rework their conceptual designs of data-intensive net functions into powerful software program elements.

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Extra info for Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Example text

If the user interface has free-text fields for entering the region and the industry, it makes sense to store them as plain strings. g. if there are several cities with the same name,  The name is stored only in one place, so it is easy to update across the board if it ever needs to be changed (for example, change of a city name due to political events),  When the site is translated into other languages, the standardized lists can be localized, and so the region and industry can be displayed in the viewer’s language,  Better search—for example, a search for philanthropists in the state of Washington can match this profile, because the list of regions can include the fact that Seattle is in Washington.

You can read a particular row by designating some columns as a key, and matching on those. [40] In a relational database, the query optimizer automatically decides which parts of the query to execute in which order, and which indexes to use. Those choices are effectively the “access path”, but the big difference is that they are made automatically the query optimizer, not by the application developer, so we rarely need to think about them. If you want to query your data in new ways, you can just declare a new index, and queries will automatically use whichever indexes are most appropriate.

Query Languages for Data When the relational model was introduced, it included a new way of querying data: it used a declarative query language, whereas IMS and CODASYL queried the database using imperative code. What does that mean? Many commonly-used programming languages are imperative. push(animals[i]); } } return sharks; } In the relational algebra, you would instead write: sharks = σfamily = “Lamniformes” (animals) 45 where σ (the Greek letter sigma) is the selection operator, returning only those animals that match the condition family = “Lamniformes”.

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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann


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