HeavyDB, formerly known as OmniSciDB, is an open-source SQL-based relational columnar database engine. It shines in performance by efficiently processing multi-billion row datasets in mere milliseconds without the hassle of indexing, pre-aggregation, or downsampling. In this blog, we will guide you step-by-step on how to install and start using HeavyDB, and troubleshoot common issues you might encounter.

Installation Instructions

Before diving into the installation process, ensure that your system meets the required dependencies. HeavyDB can run on both CPU-only systems and hybrid CPU-GPU environments.

Supported Distributions

• CentOS (CPU/GPU): RPM for CPU | RPM for GPU
• Ubuntu (CPU/GPU): DEB for CPU | DEB for GPU

General Installation Steps

Perform the following steps to install HeavyDB on your system:

mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=release ..
make -j 4

Create a fresh build directory for the installation processes. The ‘make -j 4’ command allows compilation processes to be parallel, speeding up the installation.

Running HeavyDB

Once installed, you can start HeavyDB using the built-in startheavy script:

..startheavy

This script sets up the data storage directory, initializes the main server, and even offers to download a sample dataset for you to explore the capabilities of HeavyDB. If you prefer manual starting, you can run the following commands from the build directory:

mkdir data
.bin/initdb data
.bin/heavydb

Understanding HeavyDB’s Architecture

Think of HeavyDB as a high-speed train traversing a landscape of big data. Just as a train uses tracks (data paths) to quickly reach its destination (query results), HeavyDB utilizes modern CPU and GPU hardware to traverse vast datasets efficiently. By implementing a multi-tier caching system similar to a train’s multiple stops (storage, CPU memory, and GPU memory), HeavyDB can quickly access data from various locations while avoiding unnecessary delays (indexing and downsampling).

Troubleshooting Common Issues

If you encounter problems during installation or use, here are some troubleshooting tips:

• Dependency Issues: Make sure all required libraries and packages are installed. Refer to the product documentation for a full list of dependencies.
• Build Failures: Review error messages in the terminal to identify missing dependencies or incorrect configurations.
• Connecting to HeavyDB: Ensure that the server is running as expected; check the server logs for any connection errors.

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Conclusion

HeavyDB is designed to revolutionize the way we handle large datasets with speed and efficiency. By following this guide, you should be able to set up your environment and start querying data in no time. At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.