- #Apache spark for mac how to#
- #Apache spark for mac install#
- #Apache spark for mac software#
- #Apache spark for mac code#
- #Apache spark for mac free#
Let’s see how you can perform Delta Lake operations, even without Spark. You’ll normally be using Delta Lake with Spark, but sometimes it’s convenient to work with Delta Lake outside of a Spark setting. You need to use the configure_spark_with_delta_pip function to properly initialize the SparkSession when working with Delta Lake. Spark = configure_spark_with_delta_pip(builder).getOrCreate()
#Apache spark for mac code#
Take a look at the following code snippet and pay close attention on how you need to initialize the SparkSession: import pyspark Here’s how the computations should look in your Jupyter notebook: You should now be able to run all the commands in this notebook. Then run jupyter lab to open up this project in your browser via Jupyter. Make sure you’ve changed into the delta-examples directory and have the mr-delta conda environment activated. Once the environment is activated, you’re ready to open a Jupyter notebook. Run conda activate mr-delta to activate the environment. When you run conda env list, you should see the “mr-delta” environment listed. You can clone the repo, cd into the project directory, and run conda create env -f envs/mr-delta.yml to create the conda environment. This conda environment file is also available in the delta-examples code repo. You want to explicitly set dependencies that are compatible rather than relying on conda to properly resolve the dependency versions.ĭelta-spark is installed via pip because it’s not uploaded to conda-forge. Notice how the Python, PySpark, and delta-spark dependencies are pinned to specific versions that are known to be compatible. Here’s an example YAML file with the required dependencies. For example, you can use Delta Lake 1.2 with PySpark 3.2, but cannot use Delta Lake 0.3.0 with PySpark 3.2. You can see the compatible versions here.
#Apache spark for mac software#
We’re going to create a conda software environment from a YAML file that’ll allow us to specify the exact versions of PySpark and Delta Lake that are known to be compatible. Now you’re ready to start creating a software environment with all the required dependencies.
#Apache spark for mac install#
The next step is to install Miniconda, so you can build a software environment with Delta Lake, Jupyter, and PySpark.Īfter Miniconda is installed, you should be able to run the conda info command. OpenJDK 64-Bit Server VM (Zulu 8.60.0.21-CA-macosx) (build 25.322-b06, mixed mode) Install conda
Run java -version and you should see output like this if the installation was successful: openjdk version "1.8.0_322" You may need to run a slightly different command as Java versions are updated frequently. You can run a command like sdk install java 8.0.322-zulu to install Java 8, a Java version that works well with different version of Spark.
Spark works well with the zulu Java vendor.
#Apache spark for mac how to#
See this blog post for a detailed description on how to work with SDKMAN.Īfter installing SDKMAN, you can run sdk list java to list all the Java versions that are available for installation. SDKMAN, short for the Software Development Kit Manager, makes it easy to install, and switch between, different Java versions. Installing Java can be difficult because there are different vendors and versions.
#Apache spark for mac free#
Feel free to skip this section if you’ve already installed Java. You need to install Java to run Spark code. This post will show you how to pin PySpark and Delta Lake versions when creating your environment, to ensure they are compatible.Ĭreating a local PySpark / Delta Lake / Jupyter setup can be a bit tricky, but you’ll find it easy by following the steps in this guide. You also need to pay close attention when setting your PySpark and Delta Lake versions, as they must be compatible. This guide will teach you how to install Java with a package manager that lets you easily switch between Java versions. In order to run PySpark, you need to install Java. This setup will let you easily run Delta Lake computations on your local machine in a Jupyter notebook for experimentation or to unit test your business logic. This blog post explains how to install PySpark, Delta Lake, and Jupyter Notebooks on a Mac.
0 kommentar(er)
