Here’s a step-by-step guide on how to create a temporary table in Databricks.
1. Set Up Your Databricks Environment
– Log in to your Databricks account.
– Create or select a Databricks workspace.
– Create a new notebook in your workspace.
2. Load Data into DataFrame
– You can load data from various sources (CSV, JSON, databases, etc.) into a DataFrame.
– For example, loading data from a CSV file:
[python]
df = spark.read.csv(‘/path/to/your/csvfile.csv’, header=True, inferSchema=True)
3. Create Temporary View from DataFrame
– Once you have your DataFrame, create a temporary view.
– A temporary view is only available within the session.
[python]
df.createOrReplaceTempView(“temp_table_name”)
4. Query the Temporary Table Using SQL
– You can now run SQL queries against your temporary table.
– Use the `spark.sql` method to run SQL queries.
[python]
result = spark.sql(“SELECT * FROM temp_table_name WHERE column_name = ‘some_value'”)
result.show()
Example Walkthrough
Let’s go through an example step-by-step.
Step 1: Set Up Environment
– Open your Databricks workspace and create a new notebook.
Step 2: Load Data into DataFrame
– Load data into a DataFrame. Here, we use a sample CSV file.
[python]
# Load data from a CSV file
df = spark.read.csv(‘/databricks-datasets/diamonds/diamonds.csv’, header=True, inferSchema=True)
Step 3: Create Temporary View
– Create a temporary view from the DataFrame.
[python]
# Create temporary view
df.createOrReplaceTempView(“diamonds_temp”)
Step 4: Query the Temporary Table
– Query the temporary table using SQL.
[python]
# Query the temporary table
result = spark.sql(“SELECT * FROM diamonds_temp WHERE color = ‘E'”)
result.show()
Additional Notes
– Temporary views are session-scoped. They disappear when the session ends.
– Use `createOrReplaceGlobalTempView` for global temporary views that are accessible across different sessions within the same application.
– To create a global temporary view:
[python]
df.createOrReplaceGlobalTempView(“global_temp_table_name”)
# Accessing a global temporary view
result = spark.sql(“SELECT * FROM global_temp.global_temp_table_name WHERE column_name = ‘some_value'”)
result.show()
This should help you create and use temporary tables in Databricks.