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stdb

Python module for creating Synapse External Tables from Databricks

Overview

stdb is a helper library designed to simplify the creation of Synapse SQL external tables from Databricks. Unlike Azure Synapse Studio, which defaults to varchar(4000) for string columns, this module uses spark to infers sane sizes for varchar columns, resulting in more efficient and accurate schema definitions.

Features

  • Automatically infers sensible sizes for varchar columns.
  • Seamless integration with Databricks and Azure Synapse.
  • Simplifies the process of creating external tables in Synapse from ADLS data using Databricks.

Usage

from stdb import Synapse

# Initialize the Synapse helper with necessary credentials and workspace name
# Parameters
# spark: Spark session object from Databricks.
# AZURE_TENANT_ID: Azure tenant ID for authentication.
# AZURE_CLIENT_ID: Azure client ID for authentication.
# AZURE_CLIENT_SECRET: Azure client secret for authentication.
# synapse_workspace: Name of the Synapse workspace.
synapse = Synapse(
    spark, 
    AZURE_TENANT_ID, 
    AZURE_CLIENT_ID, 
    AZURE_CLIENT_SECRET, 
    "synapse_workspace"
    )

# Create an external table in Synapse for ADLS tables
# Parameters
# adls_storage_account: Name of the ADLS storage account.
# container: Name of the container within the storage account.
# path: Path to the data within the container.
# synapse_database: Name of the target Synapse database.
synapse.create_external_table(
    'adls_storage_account', 
    'container', 
    'path/to/adls/database/', 
    'synapse_database'
    )

Under heavy development, APIs may change.