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Nowadays we often have to process large files and collect various data. For example, on a popular website, daily server logs alone can be hundreds of gigabytes. When working with files in the gigabyte or terabyte range, it can be seen that the storage capacity or computing power of a single machine is not enough.
A machine either does not have enough hard disk space, and even if there is space in the hard disk, it is seen that there is not enough space in the RAM, loading the entire file into the RAM and processing is not possible. The function of “distributed file system” is to divide a file into many small parts and store it on different machines.
Today we will learn about file systems and look at the architecture of a “distributed file system”. After reading this text you will know about various topics of distributed systems like data replication, leader-follower architecture etc.
How To Create Signup Page Design – Login Registration Form Design HTML CSS Tutorial
file system
If you’ve ever setup Linux/Windows on your computer or partitioned/formatted a hard disk, you might be familiar with the terms FAT32, NTFS, EXT, etc. These are different types of file systems. The function of the file system is to control how the files of your computer will be arranged on the hard disk, which memory block will contain the data, how the old data will be accessed.
You can compare it to organizing your files and documents at home. You may have organized different types of documents in different drawers so that the documents can be easily found, you can also call it a kind of file system.
When you format a hard disk to erase all data, its file system is also erased. So while formatting we are given the option to choose a file system. After formatting, a new file system is just initialized on the hard disk so that you can store the new data there.
FAT32, NTFS are disk file systems, their job is to work with a hard disk. If you have multiple hard disks in your computer, each hard disk controls a different file system, not one. If you want to share a file across multiple computers, you need a distributed file system.
Distributed file system
We will now look at the architecture design of a distributed file system.
If you’re an experienced engineer, you might want to think about how a distributed file system might be designed before reading the rest. Things to keep in mind are how a file is fragmented, who decides what data goes to which machine in the cluster, what happens to the data if a machine crashes, etc.
Distributed file system machines reside within the same local network and can communicate with each other. But usually the files uploaded to this type of file system cannot be edited, storing daily work Word/Excel files is not the purpose of this type of file system, our purpose is to store large files which will be analyzed later offline.
First we need some machines where the data will be stored. We will call these machines data nodes.
Each data node in the image is an individual machine. Each has an operating system (usually Linux) installed, a hard disk, and RAM. You can access machines with ssh tools if you have access permissions and know the IP address.
We will partition our large files and store them on data nodes. But the problem is which machine has empty space, who will tell which data is in which machine? For that we need a leader node. The leader node is the master of this entire file system, he will decide where the data will be kept, if someone wants to read the data, he will tell where the data is.
How To Create Signup Page Design – Login Registration Form Design HTML CSS Tutorial
Another name for leader node in the context of distributed file system is Name Node. The reason for saying name node is probably that the leader has the name-location information for all the data nodes, but I prefer the leader node name. The information about the data held by the leader is called meta data. The definition of meta data is “data that provides information about other data”, in this case file name, location, number of replicas are meta data. The data is usually loaded into the leader node’s memory.
Now we have a fairly mobile file system, but how to upload or read files? For such operations the client needs to download a library. Clients can upload or read files by authenticating themselves using APIs provided by that library.
The client library contains interfaces for uploading files, reading files, browsing folders. When reading the client library name node, it finds out which data node the file is in, then contacts that data node and reads the data. While reading the client will feel like it is reading data stored on a machine, the distribution is handled by the client library and the namenode. Since the size of the files is very large, there is an option to read partial data.
Same process while writing data. The user client uses the file upload interface of the library. The upload function contacts the name node to find out which data nodes have free space. Then the file is divided into multiple blocks and each block is sent to each data node.
The image above shows how two files are split and stored on multiple data nodes.
Now we have a new problem. What if one of the data nodes is down for some time? This can happen due to various reasons including software updates, electrical disturbances. The solution is to keep multiple copies of each part of the data in different data nodes. This is called replication. This will require a little more storage space but High Availability can be ensured. Nowadays storage space is a cheap thing, so that’s not a problem.
In the image file, 1 of each part is additionally copied. The client can increase or decrease the number of replicas by updating the configuration file if desired, but usually at least 3 copies are stored. The data node is responsible for creating replicas, but the leader or name node dictates when data should be copied to which node.
Another interesting optimization here is called Rack Awareness. In a data center, machines are arranged in different racks, as shown in the figure below:
Machines in the same rack typically share the same cable for different types of connections. All the machines in the same rack are likely to shut down in case of an electrical disturbance. If the leader node knows which machine is in which rack, what does it do when creating a replica? It is wise to send each replica to a separate rack.
How does the leader node know which data node is down? The leader pings the data nodes every few seconds, and the data node replies that it is alive. This is sometimes called a heartbeat check.
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