In Hive, you can create a table using the STORED AS clause to specify the file format in which the table data will be stored. Here are the steps to create a table using the STORED AS clause in Hive: you could store the table data in ORC format by specifying STORED AS ORC. In …
Section 8:74.Creating Table using orc File Format – Order_items Read More »
Let us use NYSE data and see how we can create tables in Hive. Data Location (Local): /data/nyse-all/nyse-data Create a database with the name – YOUR_OS_USER_NAME_nyse Table Name: nyse_eod File Format: TEXTFILE (default) Review the files by running Linux commands before using data sets. Data is compressed and we can load the files as is. …
In Apache Hive, there are two ways to delete a table: truncating and dropping the table. Here’s an overview of each method: Truncating a table: When you truncate a table in Hive, all the data in the table is deleted, but the table metadata and structure remain intact. Truncating a table is a faster operation …
Section 7:71. Truncating and Dropping the table in Hive Read More »
RDBMS Tables are Schema on Write. For each and every write operation there will be validations such as Data Types. Scale, Precision, Check Constraints, Null Constraints. Unique Constraints performed. RDBMS Tables are fine tuned for best of the for transactions (POS. Bank Transfers etc) whereas Hive is meant for heavy weight batch data processing. where …
In Apache Hive, the STORED AS clause is used to specify the file format for data storage when creating tables. The choice of file format can have an impact on the performance, storage, and compatibility of the data in Hive. Here’s an overview of some of the file formats that can be specified using the …
Section 7:69. Overview of File Formats – Stored As Clause Read More »
When you drop an external table in Hive, only the metadata associated with the table is deleted from the Hive metastore. The underlying data in the external storage system that the table was pointing to is not affected by the drop operation. This is because external tables in Hive are just pointers to data stored …
