docs: Databricks support in Spark Integration (#500)

* docs: Spark Databricks

* chore: Add href https://www.databricks.com/

* chore: bump spark version
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Anush
2024-01-08 15:37:59 +01:00
committed by GitHub
parent 5a07840d85
commit 35472b2ea0
2 changed files with 9 additions and 1 deletions
@@ -33,7 +33,7 @@ For Java and Scala projects, you can also obtain the Qdrant-Spark Connector from
<dependency> <dependency>
<groupId>io.qdrant</groupId> <groupId>io.qdrant</groupId>
<artifactId>spark</artifactId> <artifactId>spark</artifactId>
<version>1.6</version> <version>1.12</version>
</dependency> </dependency>
``` ```
@@ -125,6 +125,14 @@ Here's how you can use the Qdrant-Spark Connector to upsert data:
.save(); .save();
``` ```
## Databricks
You can use the `qdrant-spark` connector as a library in [Databricks](https://www.databricks.com/) to ingest data into Qdrant.
- Go to the `Libraries` section in your cluster dashboard.
- Select `Install New` to open the library installation modal.
- Search for `io.qdrant:spark:1.12` in the Maven packages and click `Install`.
![Databricks](/documentation/frameworks/spark/databricks.png)
## Datatype Support ## Datatype Support
Qdrant supports all the Spark data types, and the appropriate data types are mapped based on the provided schema. Qdrant supports all the Spark data types, and the appropriate data types are mapped based on the provided schema.
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