cloud development environment

Apache Spark online coding platform

Run large-scale data processing jobs in a cloud workspace.

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about Apache Spark

Apache Spark in the cloud, ready in under a minute.

Apache Spark is an open-source data processing engine built for large-scale analytics. Written in Scala, it also supports Python, Java, and R. Spark processes data in parallel and provides high-level APIs for transformations, machine learning, and stream processing. On RunCode, a Spark workspace spins up in under a minute.

Open a Apache Spark workspace →
analysis.py

Fast, parallel data processing across industries

Spark is widely used in finance, healthcare, and e-commerce for data ingestion, cleansing, transformation, and analysis. Its speed makes it a practical choice for large-scale tasks that would be too slow or resource-intensive with traditional processing tools. The engine also includes MLlib for machine learning, GraphX for graph processing, and Structured Streaming for real-time data pipelines.

Using Apache Spark on RunCode

  1. Create a workspace with Python or Scala selected
  2. Install PySpark via pip or use the preinstalled Spark environment
  3. Start an interactive session with pyspark or spark-shell
  4. Load data using the DataFrame API
  5. Run transformations and actions, then collect results
  6. Submit batch jobs with spark-submit

What you get on RunCode for Apache Spark

  • Python, Java, and Scala runtimes in a Linux workspace
  • VS Code in the browser for editing Spark jobs
  • A terminal for pyspark, spark-shell, and spark-submit
  • Git integration with GitHub, GitLab, and Bitbucket
  • A workspace ready in under a minute
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