Cosmos Spark release - version bump for documentation (Azure#27044)

musabbir · Feb 11, 2022 · 8db33fd · 8db33fd
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diff --git a/sdk/cosmos/azure-cosmos-spark_3-1_2-12/README.md b/sdk/cosmos/azure-cosmos-spark_3-1_2-12/README.md
@@ -52,11 +52,11 @@ https://github.com/Azure/azure-sdk-for-java/issues/new
 ### Download
 
 You can use the maven coordinate of the jar to auto install the Spark Connector to your Databricks Runtime 8 from Maven:
-`com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.6.0`
+`com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.6.1`
 
 You can also integrate against Cosmos DB Spark Connector in your SBT project:
 ```scala
-libraryDependencies += "com.azure.cosmos.spark" % "azure-cosmos-spark_3-1_2-12" % "4.6.0"
+libraryDependencies += "com.azure.cosmos.spark" % "azure-cosmos-spark_3-1_2-12" % "4.6.1"
 ```
 
 Cosmos DB Spark Connector is available on [Maven Central Repo](https://search.maven.org/search?q=g:com.azure.cosmos.spark).

diff --git a/sdk/cosmos/azure-cosmos-spark_3-2_2-12/README.md b/sdk/cosmos/azure-cosmos-spark_3-2_2-12/README.md
@@ -52,11 +52,11 @@ https://github.com/Azure/azure-sdk-for-java/issues/new
 ### Download
 
 You can use the maven coordinate of the jar to auto install the Spark Connector to your Databricks Runtime 8 from Maven:
-`com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.6.0`
+`com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.6.1`
 
 You can also integrate against Cosmos DB Spark Connector in your SBT project:
 ```scala
-libraryDependencies += "com.azure.cosmos.spark" % "azure-cosmos-spark_3-2_2-12" % "4.6.0"
+libraryDependencies += "com.azure.cosmos.spark" % "azure-cosmos-spark_3-2_2-12" % "4.6.1"
 ```
 
 Cosmos DB Spark Connector is available on [Maven Central Repo](https://search.maven.org/search?q=g:com.azure.cosmos.spark).

diff --git a/sdk/cosmos/azure-cosmos-spark_3_2-12/docs/quick-start.md b/sdk/cosmos/azure-cosmos-spark_3_2-12/docs/quick-start.md
@@ -23,10 +23,10 @@ You can use any other Spark 3.1.1 spark offering as well, also you should be abl
 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.
 
 For Spark 3.1:
-- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.6.0](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-1_2-12/4.6.0/jar)
+- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-1_2-12:4.6.1](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-1_2-12/4.6.1/jar)
 
 For Spark 3.2:
-- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.6.0](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-2_2-12/4.6.0/jar)
+- Install Cosmos DB Spark Connector, in your spark Cluster [com.azure.cosmos.spark:azure-cosmos-spark_3-2_2-12:4.6.1](https://search.maven.org/artifact/com.azure.cosmos.spark/azure-cosmos-spark_3-2_2-12/4.6.1/jar)
 
 
 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.