Cache-friendly binary search
High-speed memory caches present in modern computer architectures favor data structures with good locality of reference, i.e. the property by which elements accessed in sequence are located in memory addresses close to each other. This is the rationale behind classes such as Boost.Container flat associative containers, that emulate the functionality of standard C++ node-based associative container
Performance comparison: linear search vs binary search.
While working on an implementation of merge sort promised in the previous article, I realized that I’d like to use one neat little thing, which is worth its own post. It is a simple strategy for sorting or doing comparison-based tasks, which works wonderfully when input data is small enough. Suppose that we have a very small array and we want to sort it as fast as possible. Indeed, applying some f
キャッシュフレンドリーな二分探索 ー データ構造を再考する | POSTD
現代のコンピュータのアーキテクチャに搭載されている高速のキャッシュメモリは、 参照の局所性 に優れた(＝一連のものとしてアクセスした要素が、互いに近いメモリのアドレスに配置されている)データ構造を好みます。これは、 Boost.Containerの平坦な（ツリー状ではない）連想コンテナ のようなクラスを陰で支えている理論的根拠です。要素を連続的に（かつ順序だてて）保存すると同時に、標準的なC++ノードベースの連想コンテナの機能性をエミュレートします。以下にあるのは、要素が0から30の範囲の時、 boost::container::flat_set の中で 二分探索 がどのように行われるのかを示した例です。 探索で目的の値を絞り込むにつれて、アクセスされる要素は次第に近くなっていきます。そのため、最初のうちは大きな距離を飛び越えていくような感じであっても、参照の局所性は このプロセスの最後の
Roaring Bitmaps
A better compressed bitset Roaring bitmaps are compressed bitmaps. They can be hundreds of times faster. Grab one of our research papers Roaring Bitmaps on GitHub Widely used Roaring is found in Google Procella: YouTube’s SQL Engine, Apache Lucene and derivative systems such as Solr and Elasticsearch, Apache Druid, Apache Spark, Apache Hive, Apache Tez, Apache Zeppelin, Apache Doris, Apache Carbon
sortdb - static key value database
As dataset sizes grow, you need to buy larger/faster database machines, or shard data across multiple machines. sortdb is a database server we have written to help fill a specific need for performant access to static data. One observation about many datasets is that there is often a small dataset that is heavily updated, and a larger older related dataset that does not change. It is this second ca
B+Trees and why I love them, part I - Ayende @ Rahien
One of the things that I enjoy about learning new things is the way it changes the way I look at the stuff that I already knows. Reading the LMDB codebase, and implementing a persistent B+Tree has given me a new depth of understanding about how relational databases (and Esent, too), work. I am going to go back to level zero and assume that you have never heard about this. You probably know what a
What are the underlying data structures used for Redis?
I'm trying to answer two questions in a definitive list: What are the underlying data structures used for Redis? And what are the main advantages/disadvantages/use cases for each type? So, I've read the Redis lists are actually implemented with linked lists. But for other types, I'm not able to dig up any information. Also, if someone were to stumble upon this question and not have a high level su
SNA Projects Blog : Tech Talk: Michael Deerkoski (Flickr) — “Continuous Deployment at Flickr”
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Binary Search *eliminates* Branch Mispredictions
War Story: Speeding up Block-based Table Lookup
GitHub - oho-sugu/BzBinSearch: BzBinSearch
Official Google Research Blog: Extra, Extra - Read All About It: Nearly All Binary Searches and Mergesorts are Broken
Fingerprint Inverted Index and Fast Multiple Set Intersection
Programming Interview Questions: How do you find out intersection between two arrays - when they are sorted / when they are not sorted.?
http://www.tbray.org/ongoing/When/200x/2003/03/22/Binary
dictd - a dictionary database server
GitHub - client9/bgrep: grep using binary search on sorted files
gist:408391
Big-O Isn't Everything, Part 2
GitHub - alexkasko/unsafe-tools: Tools to work with off-heap memory using sun.misc.Unsafe