update download and databricks doc for 21.06.2 (#3214)

Signed-off-by: Peixin Li <pxli@nyu.edu>

docs/download.md

@@ -73,6 +73,48 @@ New functionality and performance improvements for this release include:
 For a detailed list of changes, please refer to the
 [CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).
 
+## Release v21.06.2
+This is a patch release to address an issue with the plugin in the Databricks 8.2 ML runtime.
+
+Hardware Requirements:
+
+	GPU Architecture: NVIDIA V100, T4 or A10/A30/A100 GPUs
+
+Software Requirements:
+
+	OS: Ubuntu 18.04, Ubuntu 20.04 or CentOS 7, CentOS 8
+
+	CUDA & Nvidia Drivers*: 11.0 or 11.2 & v450.80.02+
+
+	Apache Spark 3.0.1, 3.0.2, 3.1.1, 3.1.2, Cloudera CDP 7.1.7, Databricks 7.3 ML LTS or 8.2 ML Runtime, and GCP Dataproc 2.0
+
+	Apache Hadoop 2.10+ or 3.1.1+ (3.1.1 for nvidia-docker version 2)
+
+	Python 3.6+, Scala 2.12, Java 8
+
+*Some hardware may have a minimum driver version greater than v450.80.02+.  Check the GPU spec sheet
+for your hardware's minimum driver version.
+
+### Download v21.06.2
+* Download the [RAPIDS
+  Accelerator for Apache Spark 21.06.2 jar](https://repo1.maven.org/maven2/com/nvidia/rapids-4-spark_2.12/21.06.2/rapids-4-spark_2.12-21.06.2.jar)
+* Download the [RAPIDS cuDF 21.06.1 jar](https://repo1.maven.org/maven2/ai/rapids/cudf/21.06.1/cudf-21.06.1-cuda11.jar)
+
+This package is built against CUDA 11.2 and has [CUDA forward
+compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/index.html) enabled.  It is tested
+on Tesla datacenter GPUs with CUDA 11.0 and 11.2.  For those using other types of GPUs which
+do not have CUDA forward compatibility (for example, GeForce), CUDA 11.2 is required. Users will
+need to ensure the minimum driver (450.80.02) and CUDA toolkit are installed on each Spark node.
+
+### Release Notes
+This release patches the plugin to address a backwards incompatible change to Parquet filters made
+by Databricks in the Databricks 8.2 ML runtime.  More information is in [issue
+3191](https://github.com/NVIDIA/spark-rapids/issues/3191) in the RAPIDS Spark repository.  See the
+[Release v21.06.0](#release-v21060) release notes for more detail about new features in 21.06.
+
+For a detailed list of changes, please refer to the
+[CHANGELOG](https://github.com/NVIDIA/spark-rapids/blob/main/CHANGELOG.md).
+
 ## Release v21.06.1
 This is a patch release to address an issue with the plugin in the Databricks 7.3 ML LTS runtime.
 
@@ -86,7 +128,7 @@ Software Requirements:
 
 	CUDA & Nvidia Drivers*: 11.0 or 11.2 & v450.80.02+
 
-	Apache Spark 3.0.1, 3.0.2, 3.1.1, 3.1.2, Cloudera CDP 7.1.7, Databricks 7.3 ML LTS or 8.2 ML Runtime, and GCP Dataproc 2.0
+	Apache Spark 3.0.1, 3.0.2, 3.1.1, 3.1.2, Cloudera CDP 7.1.7, and GCP Dataproc 2.0
 
 	Apache Hadoop 2.10+ or 3.1.1+ (3.1.1 for nvidia-docker version 2)
 

docs/get-started/getting-started-databricks.md

@@ -54,7 +54,7 @@ CUDA 11.0 toolkit on the cluster.  This can be done with the [generate-init-scri
 Spark plugin and the CUDA 11 toolkit. 
     - [Databricks 8.2
     ML](https://docs.databricks.com/release-notes/runtime/8.2ml.html#system-environment) has CUDA 11
-    installed.  In this case use
+    installed.  Users will need to use 21.06.2 or later on Databricks 8.2 ML. In this case use
     [generate-init-script.ipynb](../demo/Databricks/generate-init-script.ipynb) which will install
     the RAPIDS Spark plugin.
 2. Once you are in the notebook, click the “Run All” button.