LearnViz CompSci
Home / Learn / Distributed Systems & Cloud / Distributed File Systems

Intermediate Topic 32 of 51 Distributed Systems & Cloud

Distributed File Systems

File storage spread across machines like GFS and HDFS.

How it works

A distributed file system stores files across many machines while presenting a unified namespace. Designs include the Google File System and HDFS, where a metadata master tracks file-to-chunk mapping and many chunk servers store large blocks, typically 64 to 256 MB, replicated three times for fault tolerance. Others, such as Ceph and Lustre, distribute metadata too, and network file systems such as NFS and SMB share a single server's storage. Clients read directly from chunk servers for high aggregate throughput.

Where it is used

Big-data processing with Hadoop and Spark, machine-learning training data, high-performance computing, media storage and log archives use distributed file systems.

Common pitfall

Metadata servers can bottleneck or be single points of failure unless replicated. They are optimized for large sequential reads and appends, with poor performance for many small files and random writes. Consistency semantics are relaxed compared with local file systems. Replication consumes capacity, and rebalancing creates traffic. Choose block sizes and replication for the workload.

Where it fits in the course

Distributed File Systems is topic 32 of 51 in Distributed Systems & Cloud, rated Intermediate. It follows Byzantine Fault Tolerance. The next topic is MapReduce.

Practice and explore

How to study this topic

  1. Read the explanation above and restate the definition in your own words.
  2. Open the interactive lesson and answer its mini quiz.
  3. Read the common pitfall, then write a short example that avoids it.
  4. Check your understanding in the Distributed Systems & Cloud quiz, and revisit the topic if you miss a question.

Frequently asked questions

What is Distributed File Systems?
File storage spread across machines like GFS and HDFS. It belongs to Distributed Systems & Cloud and is an intermediate-level topic.
Where do people use Distributed File Systems?
Big-data processing with Hadoop and Spark, machine-learning training data, high-performance computing, media storage and log archives use distributed file systems.
What is the most common mistake with Distributed File Systems?
Metadata servers can bottleneck or be single points of failure unless replicated.
What should I learn before this topic?
Start with Byzantine Fault Tolerance, the topic just before it in Distributed Systems & Cloud.
How can I practice it?
Answer the mini quiz in the interactive lesson, then take the Distributed Systems & Cloud quiz.
Is Distributed File Systems hard to learn?
It is an Intermediate topic. Be comfortable with the Beginner topics in this area first, then read the common pitfall carefully, since it is where most mistakes happen.
How long does it take to learn Distributed File Systems?
Most learners can read the explanation and finish the interactive lesson in under an hour. Fluency comes from applying the idea, so plan a few short practice sessions with the quiz.
Which topics are related to Distributed File Systems?
Byzantine Fault Tolerance, MapReduce, Failure Detectors are closely connected. The full list is in the related topics section of this page.
What should I study after Distributed File Systems?
Continue with MapReduce, the next topic in Distributed Systems & Cloud.

Related topics