Next Steps
Congratulations! If you have completed each section of the Getting Started Guide, you are now well on your way to becoming an Apache Spark power user. As a good next step, visit the Qubole Developers page for more examples and helpful resources.
We also recommend that you download the O’Reilly Creating a Data-Driven Enterprise with DataOps eBook. The book covers important characteristics of data-driven organizations and where the big data industry has evolved with cloud and emerging Data Science technologies. Authored by Qubole co-founder’s Ashish Thusoo and JoyDeep Sen Sarma, the book also includes stories from Engineering leaders at Facebook, Linkedin, Uber, Ebay, and Twitter with steps your organization should consider when scaling out modern data platforms.
As a company founded out of open-source technologies, coming from the creators of Apache Hive, Qubole is constantly focused on contributing OSS tools back to the community to help build and scale Apache Spark applications in the cloud. Join our GitHub and check out other highlight Open-Source projects!
Qubole Test Drive contains a wealth of additional big data engine examples (Presto, Hive, Airflow, and more). You can also visit the Qubole website for a wealth of additional resources:
Training
Access free Self-Service Spark Training, with self-paced courses for Users and Engineers, or live Instructor-Led Training every week.
Social
Stay up to date with the latest improvements in big data analytics, AI, and ML in the cloud. Follow Qubole on Linkedin, Twitter, and Youtube!
Notebooks
Check out more Spark Notebook examples as well as other big data engines.
Highlight Notebooks:
- Advanced Analytics for Retail
- Visualizing and Mapping Earthquakes with Notebooks
- Predicting Customer Churn (ML Training & Selection)
- Financial Time Series Analysis
Documentation
- Spark Quickstart Guides to help run commands with Apache Spark in the Qubole Workbench and Notebooks.
- Download the PySpark Cheat Sheet, for useful commands and shortcuts when developing in Python with Apache Spark.
- Use your favorite Python and R packages, or add your own, with Qubole Environments for Spark.
Blogs
Stay up to date with the latest releases and examples in the Apache Spark Engineering blog.
Highlight Blogs:
Data Science & Analytics
- How to Increase Your Big Data Value with Apache Spark and Qubole
- Model Training, Evaluation, and Real-Time Scoring with XGBoost, Apache Spark, and Flask
- Using RStudio To Train ML Models With Qubole on Spark At Production Scale
- Using The H2O Framework With Apache Spark Clusters On Qubole
- Distributed Deep Learning on Keras with Apache Spark
- Embrace Big Data Choice: Curate And Analyze Data With Hive, Spark, And Presto
Data Engineering & Ops
- The Key To Building Data Pipelines For Machine Learning: Support For Multiple Engines
- Getting Started with Machine Learning and Snowflake Data Warehouse
- Spark Streaming: IoT With Amazon Kinesis And Visualizing With Qubole Notebooks
- Processing Hierarchical Data Using Spark Graphx Pregel API
Qubole Engineering & Product
- Package Management for Apache Spark
- Open Source Optimizer (SparkLens) for Apache Spark
- Dashboards for Spark Notebooks
- Apache Spark on AWS Lambda
- Connecting Jupyter to Spark on Qubole
