How to create an external partitioned table in Hive?

To create an external partitioned table, the following steps need to be executed:

  1. Firstly, you need to make sure that you have already created a database in Hive. If you have not created the database yet, you can use the following command to create a new database:
  2. Make a database called database_name.
  3. Before creating an external partitioned table, you need to create a directory in the Hadoop file system to store the table data. You can use the following command to create the directory:
  4. Create a directory called “table_data” in the specified path.
  5. Next, you can use the CREATE EXTERNAL TABLE statement to create an external partitioned table. Here is the syntax for creating an external partitioned table:
  6. Create an external table in the specified database and table name, with designated columns and a partition column, and store the data in the specified location.
  7. In the above syntax, database_name refers to the name of the database you created, table_name is the name of the table to be created, column1, column2, etc. are the column names and corresponding data types of the table. partition_column is the name of the column used for partitioning, and data_type is the data type of the partition column. The LOCATION option specifies the directory path where the table data is stored.
  8. Finally, you can use the following command to load partition data for the table:
  9. Add a partition to the specified database table using the given column value.
  10. In the above command, database_name refers to the name of the database you have created, table_name refers to the name of the table you have created, partition_column is the column used for partitioning, and value is the value of the partition column. You can execute this command repeatedly to load data for multiple partitions as needed.

By following the steps above, you can create an external partitioned table in Hive. It’s important to note that an external partitioned table simply organizes the data stored in the Hadoop file system in a logical manner within Hive, without actually moving or copying the data files to Hive’s data warehouse.

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