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Copy file name to clipboardExpand all lines: sdk/cosmos/azure-cosmos-spark_3_2-12/docs/quick-start.md
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@@ -23,10 +23,10 @@ You can use any other Spark 3.1.1 spark offering as well, also you should be abl
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SLF4J is only needed if you plan to use logging, please also download an SLF4J binding which will link the SLF4J API with the logging implementation of your choice. See the [SLF4J user manual](https://www.slf4j.org/manual.html) for more information.
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For Spark 3.1:
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- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.6.2](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-1_2-12/4.6.2/jar)
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- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.10.0](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-1_2-12/4.10.0/jar)
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For Spark 3.2:
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- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.6.2](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-2_2-12/4.6.2/jar)
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- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.10.0](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-2_2-12/4.10.0/jar)
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The getting started guide is based on PySpark however you can use the equivalent scala version as well, and you can run the following code snippet in an Azure Databricks PySpark notebook.
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