Set up Apache Arrow and MinIO on arm64

Set up Apache Arrow environment and MinIO

In this section, you prepare a SUSE Linux Enterprise Server (SLES) arm64 virtual machine and install the core components for high-performance analytics using Apache Arrow. You also deploy MinIO, an S3-compatible object storage service, to store analytical datasets in later sections.

This foundation ensures all analytics libraries are natively optimized for arm64 (Axion).

Architecture overview

This architecture represents a single-node analytics environment that mirrors how modern cloud analytics stacks operate: compute and memory-local processing with object storage–backed datasets.

    

        
        
SUSE Linux Enterprise Server (arm64)
        |
        v
Python 3.11 Virtual Environment
        |
        v
Apache Arrow Libraries
        |
        v
MinIO (S3-Compatible Object Storage)

    

Install system dependencies on SUSE

Install Python, build tools, and system libraries required by Apache Arrow and its ecosystem.

    

        
        
sudo zypper refresh ; \
sudo zypper install -y \
  python311 python311-devel python311-pip \
  gcc gcc-c++ make \
  libopenssl-devel \
  libuuid-devel \
  curl git

    

Verify Python installation

    

        
        
python3.11 --version

    

The output is similar to:

    

        
        Python 3.11.10

        
    

Why this matters:

• Python 3.11 provides better performance and memory efficiency
• Apache Arrow wheels are fully supported on arm64 for Python 3.11
• Ensures compatibility with modern analytics libraries

Create a Python virtual environment

Create an isolated Python environment for Arrow and analytics libraries.

    

        
        
python3.11 -m venv arrow-venv
source arrow-venv/bin/activate

    

Upgrade core packaging tools

    

        
        
pip install --upgrade pip setuptools wheel

    

Why this matters:

• Avoids conflicts with the system Python
• Ensures reproducible analytics environments
• Recommended for production-grade data workloads

Install Apache Arrow and required libraries

Install Apache Arrow and supporting analytics libraries.

    

        
        
pip install \
  pyarrow \
  pandas \
  numpy \
  s3fs \
  grpcio \
  grpcio-tools \
  fastparquet \
  pyorc

    

Verify Arrow installation

    

        
        
python - <<EOF
import pyarrow as pa
print(pa.__version__)
EOF

    

The output is similar to:

    

        
        23.0.1

        
    

This confirms Apache Arrow is correctly installed on arm64.

Install and start MinIO (S3-compatible storage)

MinIO provides high-performance, S3-compatible object storage, which is widely used in modern analytics architectures.

Download MinIO for arm64:

    

        
        
curl -LO https://dl.min.io/server/minio/release/linux-arm64/minio
chmod +x minio
sudo mv minio /usr/local/bin/

    

Start MinIO server

    

        
        
mkdir -p ~/minio-data

export MINIO_ROOT_USER=minioadmin
export MINIO_ROOT_PASSWORD=minioadmin

minio server ~/minio-data --console-address :9001

    

MinIO endpoints:

• S3 API: Port 9000
• Web Console: Port 9001

Leave this process running.

The output is similar to:

    

        
        MinIO Object Storage Server
API: http://127.0.0.1:9000
WebUI: http://127.0.0.1:9001

        
    

Create a MinIO bucket

Once logged in to the MinIO console, create a bucket that will store analytics datasets.

Open this URL in your browser:

http://<VM-IP>:9001

Login credentials:

• Username: minioadmin
• Password: minioadmin

MinIO Web UI displaying buckets and stored Parquet/ORC objects

Create a bucket named

arrow-data

MinIO Web UI displaying the arrow-data bucket

MinIO Bucket View

This bucket will be used to store:

• Parquet datasets
• ORC datasets
• Analytics output files

Configure S3 credentials for Python

In another terminal (same VM, virtual environment active), export S3 credentials so Python libraries can access MinIO.

    

        
        
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
export AWS_DEFAULT_REGION=us-east-1

    

Verify:

    

        
        
env | grep AWS

    

The output is similar to:

    

        
        AWS_SECRET_ACCESS_KEY=minioadmin
AWS_DEFAULT_REGION=us-east-1
AWS_ACCESS_KEY_ID=minioadmin

        
    

What this enables:

• pyarrow
• s3fs
• pandas
• Other S3-compatible analytics libraries

to communicate with MinIO exactly like Amazon S3.

What you’ve learned and what’s next

• Prepared a SUSE arm64 analytics environment
• Installed Apache Arrow and dependencies
• Deployed MinIO as S3-compatible object storage
• Configured secure access for analytics workloads

In the next section, you will use Apache Arrow to write and read Parquet and ORC datasets from MinIO using vectorized analytics APIs.