.. _pysparkling_azure: Running PySparkling on Databricks Azure Cluster ----------------------------------------------- Sparkling Water, PySparkling and RSparkling can be used on top of Databricks Azure Cluster. This tutorial is the **PySparkling**. For Scala Sparkling Water, please visit :ref:`sw_azure` and for RSparkling, please visit :ref:`rsparkling_azure`. To start Sparkling Water ``H2OContext`` on Databricks Azure, the steps are: 1. Login into Microsoft Azure Portal 2. Create Databricks Azure Environment In order to connect to Databricks from Azure, please make sure you have created user inside Azure Active Directory and using that user for the Databricks Login. 3. Add PySparkling dependency In order to create the Python library in Databricks, go to **Libraries**, select **PiPy** as the library source and type in: ``h2o_pysparkling_SUBST_SPARK_MAJOR_VERSION`` for the latest PySparkling for Spark SUBST_SPARK_MAJOR_VERSION. The advantage of adding the library from PiPy, instead of uploading manually, is that the latest version is always selected and also, the dependencies are automatically resolved. .. figure:: ../images/databricks_pysparkling_pipy.png :alt: Uploading PySparkling Library You can configure each cluster manually and select which libraries should be attached or you can configure the library to be attached to all future clusters. It is advised to restart the cluster in case you attached the library to already running cluster to ensure the clean environment. 4. Create the cluster - Make sure the library is attached to the cluster - Select Spark SUBST_SPARK_VERSION .. figure:: ../images/databricks_cluster_creation.png :alt: Example of configured cluster ready to be started 5. Create Python notebook and attach it to the created cluster. To start ``H2OContext``, the init part of the notebook should be: .. code:: python from pysparkling import * hc = H2OContext.getOrCreate(spark) 6. And voila, we should have ``H2OContext`` running .. figure:: ../images/databricks_sw_h2o_context_running.png :alt: Running H2O Context Please note that accessing H2O Flow is not currently supported on Azure Databricks.