By default, Hive uses a built-in Derby SQL server. It stores metadata for Hive tables (like their schema and location) and partitions in a relational database.Īll Hive implementations need a metastore service, where it stores metadata. Metastore is the central repository of Apache Hive metadata. # Hive Configuration Directory can be controlled by:Įxport HIVE_CONF_DIR=/usr/local/hive/conf # Set HADOOP_HOME to point to a specific hadoop install directory Open the hive-env file by running the following commandĪdd the following configurations to the end of the file (Change the paths according to your setup) Hdfs dfs -chmod g+w /bigdata/hive/warehouseĬhange the working directory to hive configurations location ![]() Hdfs dfs -mkdir -p /bigdata/hive/warehouse Now for the hive to save table or other miscellaneous data we need to create another directory. Now we need to create Hive directories within HDFS. Now, load the hive environment variables by running the following commands Let's work together! Contact Adding Hive Environment VariablesĪdding hive path to the environment is necessary, else you would have to move to the hive directory to run commands.Īdd the following lines to the end of the bashrc file cd /usr/localĮxtract the the hive file in same location. (Change the directory and download link according to your preference). To download the release of your choice use the following commands. lets begin the installation process of hive by downloading the latest stables release from ( ), for older versions visit ( ). Note: Prefer java 8, as newer versions no longer has URLClassLoader which is required for running hive. Environment used in this setup is ubuntu 18.04 and hive version is 3.1.2. If Hadoop is not configured on your system, you can follow the step by step installation instructions HEREīefore installing the Hive, make sure your Hadoop installation is fine and all the core services of Hadoop are up and running. Since Hive is built on top of Hadoop, Java and Hadoop needs to be installed in your system. With Hive query language, it is possible to take a MapReduce joins across Hive tables. Hive query language is similar to SQL wherein it supports subqueries. Hive has its own SQL-like query language called HiveQL (Hive Query Language). ![]() Apache Hive is a data warehouse infrastructure that facilitates querying and managing large data sets which resides in distributed storage system.
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