Jupyter Spark Server

A notebook server built for any operator looking to leverage advanced analytics provided by Apache Spark.

Jupyter Python Libraries

Pandas

Pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

Jupyter Kernels Available

IPython Kernel (Python)

The Jupyter team maintains the IPython kernel since the Jupyter notebook server depends on the IPython kernel functionality. Many other languages, in addition to Python, may be used in the notebook.

PySpark Kernel (Python)

A python Kernel to enable Apache Spark for python. Writing PySpark Applications is really no different than writing normal Python applications or packages. It’s quite similar to writing command-line applications in particular. Spark doesn’t have a build concept, just Python scripts, so to run an application, you simply execute the script against the cluster.

Syplon Kernel (Scala/Python)

A Scala kernel for Apache Spark that uses metakernel in combination with py4j.

R Kernel (R)

An R kernel for Apache SparkR. SparkR is an R package that provides a light-weight frontend to use Apache Spark from R. In Spark 2.4.1, SparkR provides a distributed data frame implementation that supports operations like selection, filtering, aggregation etc. (similar to R data frames, dplyr) but on large datasets. SparkR also supports distributed machine learning using MLlib.