About: Log-structured merge-tree     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : dbo:Building, within Data Space : el.dbpedia.org associated with source document(s)

In computer science, the log-structured merge-tree (also known as LSM tree, or LSMT) is a data structure with performance characteristics that make it attractive for providing indexed access to files with high insert volume, such as transactional log data. LSM trees, like other search trees, maintain key-value pairs. LSM trees maintain data in two or more separate structures, each of which is optimized for its respective underlying storage medium; data is synchronized between the two structures efficiently, in batches.

AttributesValues
rdf:type
rdfs:label
  • Log-structured merge-tree (en)
rdfs:comment
  • In computer science, the log-structured merge-tree (also known as LSM tree, or LSMT) is a data structure with performance characteristics that make it attractive for providing indexed access to files with high insert volume, such as transactional log data. LSM trees, like other search trees, maintain key-value pairs. LSM trees maintain data in two or more separate structures, each of which is optimized for its respective underlying storage medium; data is synchronized between the two structures efficiently, in batches. (en)
sameAs
dbp:wikiPageUsesTemplate
Subject
gold:hypernym
prov:wasDerivedFrom
Wikipage page ID
page length (characters) of wiki page
Wikipage revision ID
Link from a Wikipage to another Wikipage
has abstract
  • In computer science, the log-structured merge-tree (also known as LSM tree, or LSMT) is a data structure with performance characteristics that make it attractive for providing indexed access to files with high insert volume, such as transactional log data. LSM trees, like other search trees, maintain key-value pairs. LSM trees maintain data in two or more separate structures, each of which is optimized for its respective underlying storage medium; data is synchronized between the two structures efficiently, in batches. One simple version of the LSM tree is a two-level LSM tree.As described by Patrick O'Neil, a two-level LSM tree comprises two tree-like structures, called C0 and C1. C0 is smaller and entirely resident in memory, whereas C1 is resident on disk. New records are inserted into the memory-resident C0 component. If the insertion causes the C0 component to exceed a certain size threshold, a contiguous segment of entries is removed from C0 and merged into C1 on disk. The performance characteristics of LSM trees stem from the fact that each component is tuned to the characteristics of its underlying storage medium, and that data is efficiently migrated across media in rolling batches, using an algorithm reminiscent of merge sort. Most LSM trees used in practice employ multiple levels. Level 0 is kept in main memory, and might be represented using a tree. The on-disk data is organized into sorted runs of data. Each run contains data sorted by the index key. A run can be represented on disk as a single file, or alternatively as a collection of files with non-overlapping key ranges. To perform a query on a particular key to get its associated value, one must search in the Level 0 tree and also each run. A particular key may appear in several runs, and what that means for a query depends on the application. Some applications simply want the newest key-value pair with a given key. Some applications must combine the values in some way to get the proper aggregate value to return. For example, in Apache Cassandra, each value represents a row in a database, and different versions of the row may have different sets of columns. In order to keep down the cost of queries, the system must avoid a situation where there are too many runs. Extensions to the 'leveled' method to incorporate B+ tree structures have been suggested, for example bLSM and Diff-Index. LSM trees are used in data stores such as Apache AsterixDB, Bigtable, HBase, LevelDB, SQLite4, Tarantool,RocksDB, WiredTiger, Apache Cassandra, InfluxDB and ScyllaDB. (en)
foaf:isPrimaryTopicOf
is differentFrom of
is Wikipage redirect of
is Link from a Wikipage to another Wikipage of
is known for of
is foaf:primaryTopic of
Faceted Search & Find service v1.17_git151 as of Feb 20 2025


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Nov 11 2024, on Linux (x86_64-ubuntu_focal-linux-gnu), Single-Server Edition (82 GB total memory, 2 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software