Databricks documentation archive

Important

This documentation has been retired and might not be updated. The products, services, or technologies mentioned in this content are no longer supported.

In this archive, you can find earlier versions of documentation for Databricks products, features, APIs, and workflows.

Administration

• Workspace-level SCIM provisioning

Compute

• Create cluster UI (legacy)
• Cluster UI preview
• Compute policies best practices

Dev tools

• Manage libraries with %conda commands (legacy)
• Explore and create tables in DBFS
• Transactional writes to cloud storage with DBIO
• Browse files in DBFS
• FileStore
• Hive table (legacy)
• Koalas
• Skew join optimization using skew hints
• Legacy UniForm IcebergCompatV1
• Workspace libraries (legacy)
• What is dbx by Databricks Labs?
• dbutils.library
• VScode with Git folders
• VSCode workspace directory

Governance

• External metastores (legacy)

Machine learning and AI

• Load data using Petastorm
• MLeap ML model export
• Train a PySpark model and save in MLeap format
• Distributed training with TensorFlow 2
• Horovod
• Model inference using Hugging Face Transformers for NLP
• Deploy MLeap model on SageMaker
• Apache Spark MLlib and automated MLflow tracking
• Model serving (legacy)

Release notes

• Databricks runtime release notes (end-of-support)
• Unity Catalog GA release note

Storage

• Neo4j
• Read and write XML data using the spark-xml library
• Accessing Azure Data Lake Storage Gen1 from Databricks
• Configure Delta storage credentials
• Connect to Azure Blob Storage with WASB (legacy)
• Azure Blob storage file source with Azure Queue Storage (legacy)
• Azure Cosmos DB
• Structured Streaming writes to Azure Synapse
• Connecting Databricks and Azure Synapse with PolyBase (legacy)