Spark/databricks seems amazing?

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  • mack

    Delta Lake helper methods in PySpark

  • I was a Databricks user for 5 years and spent almost all my time inside the IntelliJ IDE developing code. I wrote almost all code in a text editor, unit tested all code (actually authored the popular Scala Spark / PySpark testing libraries: https://github.com/MrPowers/) and had everything up with CI/CD. Lots of OSS PySpark/Scala Spark work too. I only used Databricks notebooks for data exploration and for lightweight notebooks that would invoke functions (that were defined in Python Wheel / JAR files). I am on the Delta Lake team at Databricks now and still do all my work in text editors (see this project: https://github.com/MrPowers/mack) and create lots of examples in Jupyter Notebooks. So I definitely think it's possible to limit notebook exposure.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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