A Merkle tree is a data structure used for efficiently summarizing and verifying the integrity of large sets of data.
Merkle trees are binary trees containing cryptographic hashes. They are used in many blockchain systems like bitcoin and ethereum. In this short article, we will take a look at the basic concept of merkle trees, how they work and how they can be used to prove that a specific element belongs to a set of elements.
Basic concept
A Merkle tree is a binary tree that represents a set of hash values. It is called merkle tree because it is named after Ralph Merkle who patented the concept in 1979.
Internal nodes are generated by hashing their child nodes together using some hash function like SHA256. The root node contains the hash of all elements in the set. All leaf nodes contain hashes of elements in the set, usually some random data or file content.
There are many different data structures that are used in distributed computing and blockchains. One of these is the Merkle Tree, also known as a hash tree. While hashes and trees might be more commonly found in computer science, they can be useful to understand when you need to verify the integrity of data.
A Merkle Tree is a type of hash-based data structure that is used to store and verify small pieces of data. The main idea behind this structure is that it allows for hashing of large amounts of data at once, thereby reducing the amount of space needed to store the hashes.
It consists of a sequence of nodes with parent nodes, children nodes and leaves, as seen below:
Merkle Tree Example
The lowermost layer consists of the data that we want to hash — also known as “leaf nodes” — each containing their own unique hash. Then each node above them (level 1) contains the hash of its child node, these are called “parent nodes”. This continues until all hashes are hashed again and stored in the root node — also known as the Merkle Root — at the top level.
A Merkle Tree is simply a binary tree constructed by hashing paired data (the leaves), then pairing and hashing the results until a single hash remains, the Merkle Root. This can be extended to work on any amount data.
Merkle trees are used to verify that large sets of data are consistent — that is, no data has been tampered with. This is done by including a small portion of the tree in the transaction block header. When miners verify the transactions included in their block candidate, they also verify that this partial tree’s root matches the one recorded in the block header. If not, transactions are rejected.
Merkle Trees are used for many purposes in cryptocurrency. The most common use is for verifying transactions within a block have not been tampered with before being added to the blockchain. In other words, it provides a means to detect if someone has tried to change any part of any transaction after it went into a block.
Merkle trees can also be used for file verification and light client synchronization, as well as other uses where you may want to check that your files or data match those of another node or server without having to download everything they have.
A Merkle tree is a hash based data structure that is a generalization of the hash list. A hash list is a linked list where each node contains the hash of its children. In a binary hash tree, each non-leaf node has two children nodes, and each leaf node is the hash of some data block.
Merkle trees are used to summarize all the data in a large data structure. In this particular case, they are used to summarize all the transactions within a block. This summary is useful because it means that rather than sending an entire large block over the network, it only needs to send the small merkle tree root and then send a proof of membership for any given transaction.
Merkle trees, named after Ralph Merkle who patented them in 1979, are used for efficient and secure verification of contents in a large data structure. As the name suggests, it’s a tree with one root node (the top node) and many leaf nodes (the bottom nodes). These trees make for very efficient data storage because each leaf node contains a hash of some data (for example, a transaction from Bitcoin), and each parent node contains the hash of its two children. This means that if we want to check if a particular transaction or piece of data is in the tree, we only need to download a few hashes to verify it.
A Merkle Tree is a data structure that hashes related data into a compact representation to allow for efficient and secure verification of contents. It was invented by Ralph Merkle in 1979.
The Merkle Tree is the foundation of how Bitcoin works. It allows for efficient transmission of transactions among all nodes in the network, as well as their efficient storage on disk.
Let’s take a look at how it works.
Imagine we have an array of data, like this:
We want to create a checksum, or hash, of the entire array so we can quickly validate its contents later.