A 2-3 tree is a type of self-balancing tree data structure that is used to efficiently store and retrieve data. It is similar to a binary search tree, but each node can have up to 3 keys and 4 children, which allows for more efficient storage and retrieval of data by reducing the number of nodes that need to be traversed to locate the data.
From a more technical perspective, a 2-3 tree is a self-balancing tree data structure that is similar to a binary search tree. Each node in the tree can have up to 3 keys and 4 children, which allows for more efficient storage and retrieval of data by reducing the number of nodes that need to be traversed to locate the data. The tree is organized in such a way that each node has either two children (if it has one key) or three children (if it has two keys). This allows for efficient search, insertion, and deletion operations, as the tree can be traversed starting from the root node to reach the desired node in logarithmic time complexity O(log n) where n is the number of nodes in the tree. Additionally, the tree is balanced by ensuring that the number of nodes in the left and right subtrees of any node is roughly equal, which ensures that the time complexity of the operations remains logarithmic as well.
A 2-3 tree is a type of self-balancing tree data structure that is used to efficiently store and retrieve data. It is similar to a binary search tree, but each node can have up to 3 keys and 4 children, which allows for more efficient storage and retrieval of data by reducing the number of nodes that need to be traversed to locate the data.
From a more technical perspective, a 2-3 tree is a self-balancing tree data structure that is similar to a binary search tree. Each node in the tree can have up to 3 keys and 4 children, which allows for more efficient storage and retrieval of data by reducing the number of nodes that need to be traversed to locate the data. The tree is organized in such a way that each node has either two children (if it has one key) or three children (if it has two keys). This allows for efficient search, insertion, and deletion operations, as the tree can be traversed starting from the root node to reach the desired node in logarithmic time complexity O(log n) where n is the number of nodes in the tree. Additionally, the tree is balanced by ensuring that the number of nodes in the left and right subtrees of any node is roughly equal, which ensures that the time complexity of the operations remains logarithmic as well.