Data sources
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This section describes the Apache Spark data sources you can use in Azure Databricks. Many include a notebook that demonstrates how to use the data source to read and write data.
The following data sources are either directly supported in Databricks Runtime or require simple shell commands to enable access:
- Avro file
- Binary file
- CSV file
- Hive table
- Image
- JSON file
- LZO compressed file
- MLflow experiment
- Parquet file
- XML file
- Zip files
For more information about Apache Spark data sources, see Generic Load/Save Functions and Generic File Source Options.
The following storage data sources require you to configure the connection to storage. Some also require that you create an Azure Databricks library and install it in a cluster: