How to Build Your Own Apache Spark
Replace Apache Spark with a custom build. Unified engine for large-scale data analytics
Build Difficulty: 5/5
Build a working replacement in a weekend with AI tools
Estimated Timeline
Based on 12 features at Weekend Project difficulty, expect about One weekend with AI-assisted development.
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Key Features to Replicate
Top features across 8 categories. See all 12 features
Analytics(2 features)
Use standard SQL syntax compatible with existing SQL knowledge
Execute fast, distributed ANSI SQL queries for dashboarding and ad-hoc reporting. Runs faster than most data warehouses
Data Processing(2 features)
Unify the processing of data in batches and real-time streaming using preferred languages: Python, SQL, Scala, Java or R
Spark SQL works on structured tables and unstructured data such as JSON or images
Data Science(1 features)
Perform Exploratory Data Analysis on petabyte-scale data without having to resort to downsampling
Deployment(1 features)
Official Docker images available for easy deployment and setup
Developer Experience(1 features)
Support for Python, SQL, Scala, Java and R programming languages
Engine(1 features)
Built on an advanced distributed SQL engine for large-scale data processing
Infrastructure(1 features)
Scale to fault-tolerant clusters of thousands of machines
Installation(1 features)
Easy installation via pip for Python users
Cost Calculator
Pricing data not available for Apache Spark. Check their website for current pricing.