Dedicated Servers for Apache Spark

In this article

• The OpenMetal XL V2.1 Server Advantage
• Exclusive Support and Features with OpenMetal
• Strategic Data Center Locations for Your Spark Cluster

In the world of big data, Apache Spark has emerged as the top tool for in memory processing. The foundation for maximizing Spark’s capabilities lies in the infrastructure. OpenMetal’s XL V2.1 servers offer a solution that marries high performance with cost-effectiveness for Spark clusters.  This option may also be good for a full pipeline, see our deployment guide for Delta Lake, Spark, and MLFlow.

The OpenMetal XL V2.1 Server Advantage

Your Apache Spark Servers CPU Capabilities

Central to the XL V2.1 servers are 2 Xeon Scalable 6338 CPUs. Though clock speed is relatively low, these processors are effective at managing demanding data tasks, making them suitable for Spark’s in-memory processing. This ensures analyses and insights from large datasets are generated swiftly.

We also recommend the new Large V4 with its higher clock speed, if needed.

Optimized Memory for In-Memory Computing

Spark’s efficiency in handling big data is significantly enhanced by its in-memory computing feature, which relies heavily on available RAM. The XL V2.1 servers, equipped with 1TB of RAM, are specifically designed to support the high memory demands of Spark applications, enabling faster data processing without the latency associated with disk-based storage.

Note, JVMs (Java Virtual Machines) generally should be less than 200GB of RAM.  When using bare metal servers, you should spin up multiple worker nodes and not try to run really large nodes.  When running in your hosted private cloud, it is common to run smaller VMs with just a single JVM inside.

Advanced Storage Capacity

Big data analytics require not just substantial storage, but also rapid access to this storage. The inclusion of up to 6 6.4TB Micron 7450 MAX NVMe drives in our servers provides more than the typical recommend 4 drives necessary for Spark’s intermediate data storage and shuffle operations.

High Private Network Connectivity

With 20gbits of connectivity per server, data exchange between nodes in a Spark cluster is fast.  High-bandwidth network infrastructure supports the demanding data throughput required for optimal performance. Deploying 4 or more servers simultaneously enhances the capability to process large datasets efficiently.

Exclusive Support and Features with OpenMetal

Support Services

Choosing OpenMetal for Apache Spark clusters brings more than just powerful servers; it provides peace of mind through a suite of support services designed to maximize your servers uptime and performance. Rapid hardware availability ensures that your Spark clusters are operational without unnecessary delays. In the event of hardware issues, rapid maintenance or replacement services are at your disposal to minimize any potential downtime, keeping your data processing workflows uninterrupted.

Direct Engineer-to-Engineer Support

Navigating the complexities of Spark can require direct, expert assistance. OpenMetal offers Engineer to Engineer support via Slack, facilitating immediate access to experienced professionals who can offer guidance, troubleshoot issues, and help optimize your Spark cluster configurations. This direct line to expertise ensures that any challenges are swiftly addressed, allowing you to focus on deriving value from your data.

Cutting-Edge Infrastructure Features

• Remote Management with IPMI – Each XL V2.1 server is equipped with Integrated Platform Management Interface (IPMI), enabling remote server management. This capability allows for out-of-band management of hardware, including monitoring, troubleshooting, and recovery operations, putting you in control and ensuring your Spark clusters are always running the way you want.
• High-Capacity Public Networks – The backbone of any data-intensive operation is its network infrastructure. OpenMetal’s 200gbps+ public networks ensure that your Spark clusters have the bandwidth necessary to handle massive data transfers both internally and externally, facilitating swift data analytics and insights.
• Flexible Cluster Configuration – Adaptability in cluster configuration is key to optimizing performance and redundancy. With OpenMetal, you have the flexibility to select cluster members located in different racks, enhancing fault tolerance and reducing the risk of simultaneous failures affecting your Spark operations.
• Economical Bandwidth Pricing – Managing costs is crucial for any organization leveraging big data. OpenMetal offers low-cost or fixed-cost egress bandwidth fees, ensuring that data transfer costs are predictable and manageable, allowing you to scale your Spark clusters without the worry of endless network fees.

Strategic Data Center Locations for Your Spark Cluster

Your choice of data center location can significantly impact the performance and reliability of your Spark clusters. OpenMetal provides hosting options in Los Angeles, Ashburn, and Amsterdam, offering strategic geographical placement that reduces latency, ensures data sovereignty compliance, and offers redundancy to support global operations. These locations are equipped with the latest in security and connectivity, ensuring your Spark clusters are hosted in environments designed for high availability and performance.