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In computer science, a dancing tree is a tree data structure similar to B+ trees. It was invented by Hans Reiser, for use by the Reiser4 file system. As opposed to self-balancing binary search trees that attempt to keep their nodes balanced at all times, dancing trees only balance their nodes when flushing data to a disk (either because of memory constraints or because a transaction has completed). [1]
The idea behind this is to speed up file system operations by delaying optimization of the tree and only writing to disk when necessary, as writing to disk is thousands of times slower than writing to memory. Also, because this optimization is done less often than with other tree data structures, the optimization can be more extensive.
In some sense, this can be considered to be a self-balancing binary search tree that is optimized for storage on a slow medium, in that the on-disc form will always be balanced but will get no mid-transaction writes; doing so eases the difficulty of adding and removing nodes during a transaction. Instead, these slow rebalancing operations are performed at the same time as the much slower write to the storage medium.
However, a negative side effect of this behavior manifests in cases of unexpected shutdown, incomplete data writes, and other occurrences that may prevent the final balanced transaction from completing. In general, dancing trees pose greater difficulty than conventional trees for data recovery from incomplete transactions, though this can be addressed by more thoroughly accounting for transacted data.
In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree. The time complexity of operations on the binary search tree is linear with respect to the height of the tree.
In computer science, a B-tree is a self-balancing tree data structure that maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree generalizes the binary search tree, allowing for nodes with more than two children. Unlike other self-balancing binary search trees, the B-tree is well suited for storage systems that read and write relatively large blocks of data, such as databases and file systems.
Computer data storage or digital data storage is a technology consisting of computer components and recording media that are used to retain digital data. It is a core function and fundamental component of computers.
ext3, or third extended filesystem, is a journaled file system that is commonly used by the Linux kernel. It used to be the default file system for many popular Linux distributions. Stephen Tweedie first revealed that he was working on extending ext2 in Journaling the Linux ext2fs Filesystem in a 1998 paper, and later in a February 1999 kernel mailing list posting. The filesystem was merged with the mainline Linux kernel in November 2001 from 2.4.15 onward. Its main advantage over ext2 is journaling, which improves reliability and eliminates the need to check the file system after an unclean shutdown. Its successor is ext4.
In database systems, durability is the ACID property that guarantees that the effects of transactions that have been committed will survive permanently, even in case of failures, including incidents and catastrophic events. For example, if a flight booking reports that a seat has successfully been booked, then the seat will remain booked even if the system crashes.
Indexed Sequential Access Method (ISAM) is a method for creating, maintaining, and manipulating computer files of data so that records can be retrieved sequentially or randomly by one or more keys. Indexes of key fields are maintained to achieve fast retrieval of required file records in indexed files. IBM originally developed ISAM for mainframe computers, but implementations are available for most computer systems.
In computer science, a self-balancing binary search tree (BST) is any node-based binary search tree that automatically keeps its height small in the face of arbitrary item insertions and deletions. These operations when designed for a self-balancing binary search tree, contain precautionary measures against boundlessly increasing tree height, so that these abstract data structures receive the attribute "self-balancing".
Reiser4 is a computer file system, successor to the ReiserFS file system, developed from scratch by Namesys and sponsored by DARPA as well as Linspire. Reiser4 was named after its former lead developer Hans Reiser. As of 2021, the Reiser4 patch set is still being maintained, but according to Phoronix, it is unlikely to be merged into mainline Linux without corporate backing.
In computing, a file system or filesystem governs file organization and access. A local file system is a capability of an operating system that services the applications running on the same computer. A distributed file system is a protocol that provides file access between networked computers.
The Write Anywhere File Layout (WAFL) is a proprietary file system that supports large, high-performance RAID arrays, quick restarts without lengthy consistency checks in the event of a crash or power failure, and growing the filesystems size quickly. It was designed by NetApp for use in its storage appliances like NetApp FAS, AFF, Cloud Volumes ONTAP and ONTAP Select.
In computer science a T-tree is a type of binary tree data structure that is used by main-memory databases, such as Datablitz, eXtremeDB, MySQL Cluster, Oracle TimesTen and MobileLite.
An in-memory database is a database management system that primarily relies on main memory for computer data storage. It is contrasted with database management systems that employ a disk storage mechanism. In-memory databases are faster than disk-optimized databases because disk access is slower than memory access and the internal optimization algorithms are simpler and execute fewer CPU instructions. Accessing data in memory eliminates seek time when querying the data, which provides faster and more predictable performance than disk.
In computer science, data is any sequence of one or more symbols; datum is a single symbol of data. Data requires interpretation to become information. Digital data is data that is represented using the binary number system of ones (1) and zeros (0), instead of analog representation. In modern (post-1960) computer systems, all data is digital.
Replication in computing involves sharing information so as to ensure consistency between redundant resources, such as software or hardware components, to improve reliability, fault-tolerance, or accessibility.
Data inconsistency refers to whether the same data kept at different places do or do not match.
In computing, file system fragmentation, sometimes called file system aging, is the tendency of a file system to lay out the contents of files non-continuously to allow in-place modification of their contents. It is a special case of data fragmentation. File system fragmentation negatively impacts seek time in spinning storage media, which is known to hinder throughput. Fragmentation can be remedied by re-organizing files and free space back into contiguous areas, a process called defragmentation.
Btrfs is a computer storage format that combines a file system based on the copy-on-write (COW) principle with a logical volume manager, developed together. It was created by Chris Mason in 2007 for use in Linux, and since November 2013, the file system's on-disk format has been declared stable in the Linux kernel.
SingleStore is a proprietary, cloud-native database designed for data-intensive applications. A distributed, relational, SQL database management system (RDBMS) that features ANSI SQL support, it is known for speed in data ingest, transaction processing, and query processing.
In computer science, the log-structured merge-tree 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.