Here’s a breakdown of how to create tables in Databricks, along with explanations and standard methods:

Methods to Create a Table in Databricks

There are primarily three ways to do this:

1. CREATE TABLE [USING]… AS SELECT

This is the most versatile method for creating tables in Databricks SQL or from Python, Scala, or R notebooks.

Syntax:

SQL

CREATE TABLE [IF NOT EXISTS] [database_name.]table_name 

[USING data_source] — Options include DELTA, PARQUET, CSV, JSON, etc.

[LOCATION ‘path_to_data’] — Optional for external tables

[OPTIONS (key1 ‘value1’, key2 ‘value2’)] — Optional table properties

AS SELECT 

  * | column_list 

  FROM source_table | query

Example:

SQL

CREATE TABLE customer_data 

USING DELTA 

LOCATION ‘/mnt/data/customer_raw’

AS SELECT * FROM customer_staging;

2. CREATE TABLE LIKE

Create a new table with the same schema (structure) as an existing table without copying the data.

Syntax

SQL

CREATE TABLE [IF NOT EXISTS] [database_name.]new_table_name

LIKE [existing_database.]existing_table_name 

[LOCATION ‘path_to_data’] — Optional, especially for external tables

Example:

SQL

CREATE TABLE customer_data_archive

LIKE customer_data;

3. Databricks UI

Ideal for less technical users or when you want to upload a file and create a table quickly.

1. 1. Steps: Navigate to the Data tab in your Databricks workspace.
   2. Click Create Table.
   3. Select either “Upload File” or connect to other data sources.
   4. Follow the UI prompts to configure the table name, format, cluster, etc.

Important Considerations

• • Managed vs. External Tables:Managed: Databricks controls data storage and location. Tables are deleted when you drop them.
  • External: You specify the storage location. Data is not deleted with the table, which is ideal for data already residing in cloud storage.
• Data Formats:  Databricks supports various formats (Parquet, Delta Lake, CSV, JSON, etc.). Delta Lake is often preferred for its ACID transactions and performance.
• Data Sources: Tables can be created from other tables, queries, files, or external data sources.