McObject has added support for the KD-Tree, a database index with uses in spatial and pattern-matching applications, to its Perst open source, object-oriented embedded database system available for the Android mobile development platform.
The new k-dimensional tree or KD-Tree index adds a structure in Perst that stores and manipulates point objects in a k-dimensional space by partitioning that space. Practical uses include computer graphics, geographical information systems and biometric applications such as fingerprint matching. In addition to their efficiency in handling multi-dimensional data, KD-trees are useful in “normal” applications in which query predicates contain various combinations of object fields. For example, KD-Trees are used to construct Query-By-Example (QBE) features in which the user selects fields and values, and the application builds database queries based on these selections.
While many Java databases offer limited index support, Perst implements rich options for data access, including specialized collection classes optimized for different data layouts and access patterns, including:
- Classic B-Tree implementation;
- R-tree indexes for spatially-oriented applications such as GIS and navigation;
- Main-memory database containers, based on T-Tree indexes, optimized for real-time memory-only access;
- Patricia Trie index, which speeds searches in networking and telephony applications;
- TimeSeries class to efficiently deal with small fixed-size objects;
- Specialized versions of collections for thick indices (indices with many duplicates), and bit indices (keys with a restricted number of possible values);
- KD-Tree indexes
For McObject’s announcement of KD-Tree support see http://www.mcobject.com/pressroom.php?step=3&article=93.
For general information about Perst for Android, including links to the open source, complete Perst database source code, and to McObject’s Android-ready TestIndex database benchmark, go to http://www.mcobject.com/android/.
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