Principle diagram of Python implementation of B-tree insertion algorithm

B tree is a highly balanced binary search tree. To perform an insertion operation, you must first obtain the position of the inserted node. Follow the node to be larger than the left subtree and smaller than the right subtree, and split the node when necessary.

Understand the operation principle of B-tree insertion in one picture

B-tree insertion algorithm

<code>BreeInsertion(T, k)r  root[T]if n[r] = 2t - 1<br/>    s = AllocateNode()<br/>    root[T] = s<br/>    leaf[s] = FALSE<br/>    n[s] <- 0<br/>    c1[s] <- r<br/>    BtreeSplitChild(s, 1, r)<br/>    BtreeInsertNonFull(s, k)else BtreeInsertNonFull(r, k)BtreeInsertNonFull(x, k)i = n[x]if leaf[x]<br/>    while i ≥ 1 and k < keyi[x]<br/>        keyi+1 [x] = keyi[x]<br/>        i = i - 1<br/>    keyi+1[x] = k<br/>    n[x] = n[x] + 1else while i ≥ 1 and k < keyi[x]<br/>        i = i - 1<br/>    i = i + 1<br/>    if n[ci[x]] == 2t - 1<br/>        BtreeSplitChild(x, i, ci[x])<br/>        if k &rt; keyi[x]<br/>            i = i + 1<br/>    BtreeInsertNonFull(ci[x], k)BtreeSplitChild(x, i)BtreeSplitChild(x, i, y)z = AllocateNode()leaf[z] = leaf[y]n[z] = t - 1for j = 1 to t - 1<br/>    keyj[z] = keyj+t[y]if not leaf [y]<br/>    for j = 1 to t<br/>        cj[z] = cj + t[y]n[y] = t - 1for j = n[x] + 1 to i + 1<br/>    cj+1[x] = cj[x]ci+1[x] = zfor j = n[x] to i<br/>    keyj+1[x] = keyj[x]keyi[x] = keyt[y]n[x] = n[x] + 1</code>

Use Python to implement B-tree insertion algorithm

<code>class BTreeNode:<br/>    def __init__(self, leaf=False):<br/>        self.leaf = leaf<br/>        self.keys = []<br/>        self.child = []<br/> <br/>class BTree:<br/>    def __init__(self, t):<br/>        self.root = BTreeNode(True)<br/>        self.t = t<br/> <br/>    def insert(self, k):<br/>        root = self.root<br/>        if len(root.keys) == (2 * self.t) - 1:<br/>            temp = BTreeNode()<br/>            self.root = temp<br/>            temp.child.insert(0, root)<br/>            self.split_child(temp, 0)<br/>            self.insert_non_full(temp, k)<br/>        else:<br/>            self.insert_non_full(root, k)<br/> <br/>    def insert_non_full(self, x, k):<br/>        i = len(x.keys) - 1<br/>        if x.leaf:<br/>            x.keys.append((None, None))<br/>            while i >= 0 and k[0] < x.keys[i][0]:<br/>                x.keys[i + 1] = x.keys[i]<br/>                i -= 1<br/>            x.keys[i + 1] = k<br/>        else:<br/>            while i >= 0 and k[0] < x.keys[i][0]:<br/>                i -= 1<br/>            i += 1<br/>            if len(x.child[i].keys) == (2 * self.t) - 1:<br/>                self.split_child(x, i)<br/>                if k[0] > x.keys[i][0]:<br/>                    i += 1<br/>            self.insert_non_full(x.child[i], k)<br/> <br/>    def split_child(self, x, i):<br/>        t = self.t<br/>        y = x.child[i]<br/>        z = BTreeNode(y.leaf)<br/>        x.child.insert(i + 1, z)<br/>        x.keys.insert(i, y.keys[t - 1])<br/>        z.keys = y.keys[t: (2 * t) - 1]<br/>        y.keys = y.keys[0: t - 1]<br/>        if not y.leaf:<br/>            z.child = y.child[t: 2 * t]<br/>            y.child = y.child[0: t - 1]<br/> <br/>    def print_tree(self, x, l=0):<br/>        print("Level ", l, " ", len(x.keys), end=":")<br/>        for i in x.keys:<br/>            print(i, end=" ")<br/>        print()<br/>        l += 1<br/>        if len(x.child) > 0:<br/>            for i in x.child:<br/>                self.print_tree(i, l)<br/> <br/>def main():<br/>    B = BTree(3)<br/> <br/>    for i in range(10):<br/>        B.insert((i, 2 * i))<br/> <br/>    B.print_tree(B.root)<br/> <br/>if __name__ == &#x27;__main__&#x27;:<br/>    main()</code>

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