Accelerate Hadoop Without the Migration
Boost processing performance for faster job completion.
Shrink clusters and cut resource costs.
Plug Flarion into AWS EMR, Azure HDInsight, GCP Dataproc, Cloudera, and On-Prem.
Hadoop vs. Flarion-Powered Hadoop
Core Capabilities
Upgrade Hadoop’s engine for unmatched speed and efficiency combining the best of both.
Automatic fallback to Hadoop API for stability when native optimization isn’t available.
Works with Databricks, AWS EMR, GCP Dataproc, Azure HDInsight, Cloudera, and on-prem enviorments.
Agentless design protects data with minimal permissions.
Scales with cluster growth, enhancing performance.
How Flarion’s Accelerator Works
Standard Hadoop distributes tasks across machines but is constrained by the inefficiencies of Java MapReduce execution, leading to:
- Higher Resource Usage
- Slower Processing
- Limited optimization of map and reduce operations
Flarion-powered Hadoop replaces Hadoop's Java MapReduce execution engine with Flarion's Polars and Arrow-based engine for acceleration of map and reduce operations - no code changes needed.
Hadoop processes data using MapReduce jobs across multiple nodes, but its Java-based execution engine limits performance on complex computations and large-scale data processing.
Flarion replaces the standard Java execution engine with our Polars and Arrow-powered engine, compiling MapReduce jobs into optimized Rust code to accelerate CPU-bound tasks like filtering, grouping, and joining—no code changes, no disruptions.
Seamless Engine Replacement for Powerful Hadoop Execution
Flarion Accelerator integrates with Hadoop by replacing the default execution components with our high-performance engine. Hadoop continues to manage job scheduling and resource allocation, delivering faster and more efficient processing.
Integration Across
All Platforms
Deployed via parcels or packages for seamless integration.
Deployed as a bootstrap action.
Configured with initialization actions.
Integrated via script actions for enhanced performance.
Integrated via script actions for enhanced performance.
Install on Hadoop nodes using tools like Ansible or Chef, optimizing MapReduce operations.
Plug & Play in Seconds
–libjars flarion-data-engine.jar \
–Dmapreduce.job.maps=10 \
–Dmapreduce.job.reduces=5 \
[other options] \
[input] [output]
3x Faster Processing And 60% Cost Savings
Minimal Effort
No code changes or tuning needed for immediate performance boosts.
Stability
Smaller, more stable clusters reduce node failures for resilient operations.
Resource Usage
Lower infrastructure demands, enabling efficient data processing.
