Sometimes you need a full IDE to create more complex code, and PySpark isn’t on sys.path by default, but that doesn’t mean it can’t be used as a regular library. The result: Running PySpark in your favorite IDE To check if your notebook is initialized with SparkContext, you could try the following codes in your notebook:ĭots = sc.parallelize().cache() The PySpark context can be sc = SparkContext.getOrCreate() Create a new notebook by clicking on ‘New’ > ‘Notebooks Python ’. This command should start a Jupyter Notebook in your web browser. Restart (our just source) your terminal and launch PySpark: $ pyspark Your ~/.bash_profile file may look like this: Just add these lines to your ~/.bash_profile file: export PYSPARK_DRIVER_PYTHON=jupyterĮxport PYSPARK_DRIVER_PYTHON_OPTS='notebook' Now to run PySpark in Jupyter you’ll need to update the PySpark driver environment variables. # For python 3, You have to add the line below or you will get an error To do so, edit your bash file: $ nano ~/.bash_profileĬonfigure your $PATH variables by adding the following lines to your ~/.bash_profile file: export SPARK_HOME=/opt/spark To find what shell you are using, type: $ echo $SHELL Lrwxr-xr-x 1 root wheel 16 Dec 26 15:08 /opt/spark̀ -> /opt/spark-2.4.0įinally, tell your bash where to find Spark. The contents of a symbolic link are the address of the actual file or folder that is being linked to.Ĭreate a symbolic link (this will let you have multiple spark versions): $ sudo ln -s /opt/spark-2.4.0 /opt/spark̀Ĭheck that the link was indeed created $ ls -l /opt/spark̀ $ sudo mv spark-2.4.0-bin-hadoop2.7 /opt/spark-2.4.0Ī symbolic link is like a shortcut from one file to another. Unzip it and move it to your /opt folder: $ tar -xzf spark-2.4.0-bin-hadoop2.7.tgz Select the latest Spark release, a prebuilt package for Hadoop, and download it directly. Make sure you have Java 8 or higher installed on your computer and visit the Spark download page Time taken: 0.Install Jupyter notebook $ pip3 install jupyter Install PySpark hive -service metastore & Run HiveĮnter the hive command directly in the terminal hive> show databases Schematool -initSchema -dbType mysql Start Metastore service. Initialize the metadata database cd /usr/local/Cellar/hive/3.1.2_3/libexec/bin Hdfs://localhost:9000/user/hive/warehouse Jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true ![]() Users/apache-hive-3.1.2-bin/log/hive.log Please note this file does not exist and needs to be created manually. Unzip -> Place the jar “mysql-connector-java-8.0.19.jar” into the /usr/local/Cellar/hive/3.1.2_3/libexec/lib directoryĬreate a file named “hive-site.xml” in the following locations /usr/local/Cellar/hive/3.1.2_3/libexec/conf directory.Select Platform Independent -> Download to your machine.Modify user permissions: $ GRANT ALL PRIVILEGES ON *.* to Refresh privileges: FLUSH PRIVILEGES.CREATE a new user: $ CREATE user identified by ‘password123’.$ Source /usr/local/Cellar/hive/3.1.2_3/libexec/scripts/metastore/upgrade/mysql/hive-schema-3.1.0.mysql.sql.Create a database: CREATE database metastore.After installing the Mysql follow the next steps to initialize the metadata database. # HIVE env variablesĮxport HIVE_HOME=/usr/local/Cellar/hive/3.1.2_3/libexecĮxport PATH=$PATH:/usr/local/mysql-8.0.12-macos10.13-x86_64/bin Setup Mysql databaseĭownload Mysql database by going to the following Mysql site. Install Hive with below command $ brew install hive Setup Hive & Mysql Environment VariablesĮnter vim ~/.bash_profile in the terminal to configure the hive path statement in the blank line. ![]() Setup Mysql / Derby database: Hive need this database (called Metastore) to store the Hive metadata.Setup Hive & Mysql Environment Variables.Please follow the steps to perform the installation. HDFS (Hadoop) setup : This step is need to completed first place before Hive installation.The installation of Hadoop is divided into these steps: In this article, I will take you through how to Install Hive on Mac with Homebrew using Terminal. ![]() This is a mechanism that can store, query, and analyze large-scale data stored in Hadoop. Hive is a data warehouse tool based on Hadoop for data extraction, transformation, and loading.
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