From ab0c01a763f7e58eb7c20da5cab0139e6647f62c Mon Sep 17 00:00:00 2001
From: Utkarsh Raghav <43128146+mrNobody1618@users.noreply.github.com>
Date: Tue, 8 Jan 2019 23:07:32 +0530
Subject: [PATCH] Updated Punctuation marks on Line 8 (#26663)

---
 guide/english/algorithms/b-trees/index.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/guide/english/algorithms/b-trees/index.md b/guide/english/algorithms/b-trees/index.md
index 7fa7168b62..a506d2e799 100644
--- a/guide/english/algorithms/b-trees/index.md
+++ b/guide/english/algorithms/b-trees/index.md
@@ -5,7 +5,7 @@ title: B Trees
 
 # Introduction
 
-B-Tree is a self-balancing search tree. In most of the other self-balancing search trees (like AVL and Red Black Trees), it is assumed that everything is in main memory. To understand use of B-Trees, we must think of huge amount of data that cannot fit in main memory. When the number of keys is high, the data is read from disk in the form of blocks. Disk access time is very high compared to main memory access time. The main idea of using B-Trees is to reduce the number of disk accesses. Most of the tree operations (search, insert, delete, max, min, ..etc ) require O(h) disk accesses where h is height of the tree. B-tree is a fat tree. Height of B-Trees is kept low by putting maximum possible keys in a B-Tree node. Generally, a B-Tree node size is kept equal to the disk block size. Since h is low for B-Tree, total disk accesses for most of the operations are reduced significantly compared to balanced Binary Search Trees like AVL Tree, Red Black Tree, ..etc.
+B-Tree is a self-balancing search tree. In most of the other self-balancing search trees (like AVL and Red Black Trees), it is assumed that everything is in main memory. To understand use of B-Trees, we must think of huge amount of data that cannot fit in main memory. When the number of keys is high, the data is read from disk in the form of blocks. Disk access time is very high compared to main memory access time. The main idea of using B-Trees is to reduce the number of disk accesses. Most of the tree operations (search, insert, delete, max, min, etc) require O(h) disk accesses where h is height of the tree. B-tree is a fat tree. Height of B-Trees is kept low by putting maximum possible keys in a B-Tree node. Generally, a B-Tree node size is kept equal to the disk block size. Since h is low for B-Tree, total disk accesses for most of the operations are reduced significantly compared to balanced Binary Search Trees like AVL Tree, Red Black Tree, etc.
 
 Properties of B-Tree:
 1) All leaf nodes are at same level.