Powerful Solution for Big Data Projects: Apache Ozone

What is Apache Ozone?
Apache Ozone is an object storage solution designed for big data applications. Big data workloads are significantly different from standard workloads, and Ozone is born out of experiences gained from running Hadoop on thousands of clusters. Managing and analyzing massive datasets has become central to technology today. In this context, Ozone, with its features in data storage and management, offers a powerful and scalable solution for large-scale data projects, reshaping the future of data engineering.
Understanding the Needs of Big Data Environments
When selecting a storage system for a big data ecosystem, the following criteria are paramount:
Performance: The system must efficiently handle high-volume data loads.
Scalability: It should be capable of expanding to hundreds of petabytes of data, thousands of nodes, and billions of objects.
API Compatibility: Seamless operation with APIs like S3 and modern architectures (cloud, container, etc.) is essential.
Let’s delve into how Apache Ozone meets these expectations.
Ozone: Object Storage Optimized for Big Data Workloads
Apache Ozone is a highly scalable, redundant, and distributed object storage technology optimized for big data workloads.
Key features include:
S3 and FS Interfaces: Supports both S3 API and file system-like interfaces.
Designed for Big Data Workloads: Optimized for big data analytics and processing.
Billions of Objects: Capable of storing a massive number of files (objects).
YARN or Kubernetes Compatibility: Can be easily used in container-based environments.
Scales to Thousands of Nodes: Expand your system horizontally to store much more data.
Low Cost: Offers the ability to store more data with less hardware compared to HDFS.
Figure 1: Ozone Architecture
Fundamental Storage Elements of Ozone: Volume, Bucket, and Key
Volume: Similar to user accounts or tenant concepts. Each volume can contain one or more buckets.
Bucket: Functions similarly to a bucket in the Amazon S3 world. A bucket can hold an unlimited number of keys.
Key: Similar to files. Each key belongs to a specific bucket, and each bucket belongs to a specific volume.
Two Management Components: Ozone Manager (OM) and Storage Container Manager (SCM)
The Ozone architecture features two critical components responsible for management tasks:
Ozone Manager (OM): Manages namespaces. When you want to write a key (file), OM gives you a block and remembers which volume/bucket this block is in. In other words, OM manages the metadata of volumes, buckets, and keys.
Storage Container Manager (SCM): Creates and manages containers, which Ozone uses as replication units. While HDFS replicates at the block level, Ozone replicates at the container level, offering significant advantages, especially as scale increases.
DataNodes
These are the nodes where all the data is stored. The client sends data in blocks, and these blocks are stored inside a storage container by the datanodes.
Recon Server
Recon is a monitoring service that tracks metadata stored by different components, such as OM and SCM, in the Ozone cluster, providing information about this data.
Ozone is a multi-protocol storage that supports the following interfaces:
– s3: Amazon’s Storage Service (S3) protocol. With the S3 Gateway, you can use S3 clients and S3 SDK-based applications on Ozone without making any changes to Ozone.
– o3: An object storage interface accessible from the Ozone shell.
– ofs: A Hadoop-compatible file system that allows any application expecting an HDFS-compatible interface to run on Ozone without API changes.
Advantages of Ozone
Better Performance:
Queries run faster, data processing speeds up.
4x Storage Capacity:
Scalability up to 384 TB per node allows you to manage massive amounts of data on data-intensive nodes simultaneously.
10x Scalability:
Ability to store up to 10 billion objects, exceeding HDFS’s 400 million file limit, provides a critical advantage for large-scale data projects.
Easier Management:
Linear scalability, fast recovery, and low maintenance costs offer a more comfortable experience for administrators.
Lower Cost per TB:
More efficient use of hardware resources, requiring less physical storage for the same data volume.
Ozone vs HDFS
Why Cloudera Chose Ozone?
Cloudera continuously evaluates solutions supporting object storage in the big data world. Apache Ozone stands out as a powerful and scalable object storage system designed to replace HDFS, while also being suitable for large-scale data projects. Additionally, HDFS and Ozone can coexist within the same cluster in Cloudera.
Key reasons for Cloudera choosing Ozone:
Compatibility with Hadoop Ecosystem:
Ozone seamlessly integrates with the existing data infrastructure as it is designed as a natural part of the Hadoop ecosystem. It simplifies data analytics and processing processes while providing a modern object storage layer.
High Performance and Scalability:
It offers significant performance improvements in data writing and reading operations in big data workloads and provides the ability to scale to billions of objects.
Distributed and Highly Available:
By storing data in a distributed structure, the risk of data loss is minimized even if a node fails, and access continues uninterrupted.
Figure 2: Ozone-HDFS Performance
Benchmark Results: Ozone Outperformed HDFS
Cloudera compared HDFS and Ozone using a widely adopted benchmark test like TPC-DS. They ran a total of 99 queries on two separate clusters, each consisting of 12 storage and compute nodes with 100 GB and 1 TB datasets, respectively, alongside key Hadoop ecosystem components like Hive, Tez, and YARN.
The results showed that Ozone outperformed HDFS by an average of 3.5% in terms of query completion time for both dataset sizes, demonstrating a performance advantage.
For a more detailed analysis, refer to: Benchmarking Ozone – Cloudera Blog
Conclusion
In summary, the high performance, exceptional scalability, and multi-protocol support offered by Apache Ozone make it a powerful and future-proof solution for big data projects. Cloudera’s adoption of Ozone and the benchmark tests conducted clearly demonstrate that this technology will rapidly spread across the industry.
If you are looking for a platform that will take your big data infrastructure to the future and simplify your data storage and management processes, Apache Ozone should definitely be on your radar.
Mehmet Can Yılmaz, Data Engineer