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Core Features
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=============
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-------------
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The main functional advantage from the use of the toolkit is the built-in parallelization support of the produced generators. Our parallelization approach builds on the idea of mapping fix-sized chunks from an underlying pseudo-random number generator (PRNG) into pseudo-random stream of records. The horizontal partitioning parallel execution model implemented by the toolkit relies on the use use of efficient `skip-ahead` PRNG operations to advance to the starting position of the assigned record substreams in each generator node.
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Extensible Architecture
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=======================
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-----------------------
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The Myriad toolkit leverages the development of custom data generators through its extensible object-oriented architecture. Creating a generator for a custom data type can be as easy as defining the type as a _bean object_-style record class and pinning down the random generation logic for a single record instance through a set of reusable _record hydration_ components.
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First Steps
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===========
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-----------
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If you want to learn more about using Myriad, please read the [Getting Started Guide](/TU-Berlin-DIMA/myriad/wiki/GettingStarted) and the [Quick Tour](/TU-Berlin-DIMA/myriad/wiki/QuickTour).
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If you want to learn more about using Myriad, please read the [Getting Started Guide](/TU-Berlin-DIMA/myriad-toolkit/wiki/GettingStarted) and the [Quick Tour](/TU-Berlin-DIMA/myriad-toolkit/wiki/QuickTour).
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To get a running demo of a simple generator, please check the [myriad-demo](https://github.com/TU-Berlin-DIMA/myriad-demo) package.
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