A completely open web-based notebook that enables interactive data analytics
Apache Zeppelin is a new and incubating multi-purposed web-based notebook which brings data ingestion, data exploration, visualization, sharing and collaboration features to Hadoop and Spark.
What Zeppelin Does
Interactive browser-based notebooks enable data engineers, data analysts and data scientists to be more productive by developing, organizing, executing, and sharing data code and visualizing results without referring to the command line or needing the cluster details. Notebooks allow these users not only allow to execute but to interactively work with long workflows. There are a number of notebooks available with Spark. iPython remains a mature choice and great example of a data science notebook. The Hortonworks Gallery provides an Ambari stack definition to help our customers quickly set up iPython on their Hadoop clusters.
Apache Zeppelin is a new and upcoming web-based notebook which brings data exploration, visualization, sharing and collaboration features to Spark. It support Python, but also a growing list of programming languages such as Scala, Hive, SparkSQL, shell and markdown.
The various languages are supported via Zeppelin language interpreters.
Data discovery, exploration, reporting and visualization are key components of the data science workflow. Zeppelin provides a “Modern Data Science Studio” that supports Spark and Hive out of the box. Actually, Zeppelin supports multiple language backends which has support for a growing ecosystem of data sources. Zeppelin’s notebooks provides interactive snippet-at-time experience to data scientist. You can see a collection of Zeppelin notebooks in the Hortonworks Gallery.
Also when you are done with your notebook and found some insight you want to share, you can easily create a report out of it and either print it or send it out.
At Cloudera we believe that Spark & Hadoop are Perfect Together. And that Zeppelin is a key component to accelerate data science solutions.
Recent improvements to web-based notebooks
Even with notebooks the data wrangling process remains challenging. Often data scientists struggle with feature engineering, algorithm selection, tuning, sharing their work with others and deploying their work into production.
We are working to improve the Zeppelin notebook in the community. We have added Hive Interpreter to Zeppelin, and are working to improve the editor to make it more stable. We are deepening our involvement in the Zeppelin community to help deliver features such as security, summary statistics, context sensitive help to improve data development experience.