Magnitude faster than other possible implementation of a set (e.g., as a hash set) When the bitset approach is applicable, it can be orders of More complicated set functions can also be implemented as bitwise operations. Intersections, unions and differences can then be implementedĪs bitwise AND, OR and ANDNOT operations. [0,n): the ith bit is set to one if integer i is present in the set.Ĭommodity processors use words of W=32 or W=64 bits. We can represent any set made of the integers from the range Of integers, a particularly appealing strategy is theīitmap (also called bitset or bit vector). To compute the intersection, the union, the difference between sets, and so on. Besides adding or removingĮlements from the set, we need fast functions Of all documents or rows (represented by numerical identifier) For example, we may need to maintain a set In databases and search engines, sets are often an integral Ways, as hash sets, as trees, and so forth.
Eclipse memory monitor bitmap code#
This code is licensed under Apache License, Version 2.0 (AL2.0). We have interoperable C/C++, Java and Go implementations. There is a serialized format specification for interoperability between implementations. You find Roaring bitmaps in InfluxDB, Bleve, Cloud Torrent, and so forth. Other platforms such as Whoosh, Microsoft Visual Studio Team Services (VSTS) and Pilosa also use Roaring bitmaps with their own implementations. Derivatives of Lucene such as Solr and Elastic also use Roaring bitmaps. Apache Lucene uses Roaring bitmaps, though they have their own independent implementation. The YouTube SQL Engine, Google Procella, uses Roaring bitmaps for indexing.
Eclipse memory monitor bitmap software#
Kudos for making something that makes my software run 5x faster (Charles Parker from BigML) Do not use other bitmap compression methods ( Wang et al., SIGMOD 2017) Use Roaring for bitmap compression whenever possible. Roaring bitmaps are found to work well in many important applications: They can even be faster than uncompressed bitmaps. In some instances, roaring bitmaps canīe hundreds of times faster and they often offer significantly better compression. Roaring bitmaps are compressed bitmaps which tend to outperform conventionalĬompressed bitmaps such as WAH, EWAH or Concise. Unfortunately, they can use too much memory.
Bitsets, also called bitmaps, are commonly used as fast data structures.
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