Code Reduction: Updatable DocValues Under the Hood



Code Reduction: Updatable DocValues Under the Hood
DocValues have been around since Lucene 4.0, and while they have gone through several changes and improvements since then, the basic concept remained the same – they let you record a value per-document per-field in each segment, and allow for very efficient random-access retrieval of those values. Lucene offers several doc-values types: numeric for single-valued numeric fields (date, ratings, counters), sorted/sortedset for single/multi-valued string (mostly, but can be any BytesRef) fields used for sorting, facetinggrouping etc., and binary fields for storing arbitrary byte[] per-document.
Also, Lucene provides several implementations for writing and reading DocValues: Lucene45 (the current default) stores the values on disk, but keeps some information in-memory for fast lookups.Memory loads the values into compressed arrays, while Direct loads the values into uncompressed arrays (faster lookups, but higher memory consumption). If your application runs in a resource constrained environment, you can use Disk which keeps absolutely everything on disk, at the cost of slower lookups.
DocValues record a value for every document in every field and segment even when a document has no value associated with a field. In most cases this is acceptable because you usually store a value for most, if not all, documents in a field (e.g. scoring factors, facets). But even if you index very sparse doc-values fields, the default encoding is very efficient at indexing blocks of "missing" values


Read full article from Code Reduction: Updatable DocValues Under the Hood

No comments:

Post a Comment

Labels

Algorithm (219) Lucene (130) LeetCode (97) Database (36) Data Structure (33) text mining (28) Solr (27) java (27) Mathematical Algorithm (26) Difficult Algorithm (25) Logic Thinking (23) Puzzles (23) Bit Algorithms (22) Math (21) List (20) Dynamic Programming (19) Linux (19) Tree (18) Machine Learning (15) EPI (11) Queue (11) Smart Algorithm (11) Operating System (9) Java Basic (8) Recursive Algorithm (8) Stack (8) Eclipse (7) Scala (7) Tika (7) J2EE (6) Monitoring (6) Trie (6) Concurrency (5) Geometry Algorithm (5) Greedy Algorithm (5) Mahout (5) MySQL (5) xpost (5) C (4) Interview (4) Vi (4) regular expression (4) to-do (4) C++ (3) Chrome (3) Divide and Conquer (3) Graph Algorithm (3) Permutation (3) Powershell (3) Random (3) Segment Tree (3) UIMA (3) Union-Find (3) Video (3) Virtualization (3) Windows (3) XML (3) Advanced Data Structure (2) Android (2) Bash (2) Classic Algorithm (2) Debugging (2) Design Pattern (2) Google (2) Hadoop (2) Java Collections (2) Markov Chains (2) Probabilities (2) Shell (2) Site (2) Web Development (2) Workplace (2) angularjs (2) .Net (1) Amazon Interview (1) Android Studio (1) Array (1) Boilerpipe (1) Book Notes (1) ChromeOS (1) Chromebook (1) Codility (1) Desgin (1) Design (1) Divide and Conqure (1) GAE (1) Google Interview (1) Great Stuff (1) Hash (1) High Tech Companies (1) Improving (1) LifeTips (1) Maven (1) Network (1) Performance (1) Programming (1) Resources (1) Sampling (1) Sed (1) Smart Thinking (1) Sort (1) Spark (1) Stanford NLP (1) System Design (1) Trove (1) VIP (1) tools (1)

Popular Posts