Merge pull request #5865 from NVIDIA/branch-22.06

Merge remote tracking branch-22.06 to main [skip ci]

Author: NvTimLiu

CHANGELOG.md

@@ -1,5 +1,5 @@
 # Change log
-Generated on 2022-06-16
+Generated on 2022-06-17
 
 ## Release 22.06
 
@@ -143,6 +143,8 @@ Generated on 2022-06-16
 ### PRs
 |||
 |:---|:---|
+|[#5861](https://github.com/NVIDIA/spark-rapids/pull/5861)|[Doc]Add Spark3.3 support in doc for 22.06 branch[skip ci]|
+|[#5851](https://github.com/NVIDIA/spark-rapids/pull/5851)|Update 22.06 changelog to include new commits [skip ci]|
 |[#5848](https://github.com/NVIDIA/spark-rapids/pull/5848)|Update spark330shim to use released lib|
 |[#5840](https://github.com/NVIDIA/spark-rapids/pull/5840)|[DOC] Updated RapidsConf to reflect the default value of `spark.rapids.sql.improvedFloatOps.enabled` [skip ci]|
 |[#5816](https://github.com/NVIDIA/spark-rapids/pull/5816)|Update 22.06.0 changelog to latest [skip ci]|

docs/FAQ.md

@@ -10,7 +10,7 @@ nav_order: 12
 
 ### What versions of Apache Spark does the RAPIDS Accelerator for Apache Spark support?
 
-The RAPIDS Accelerator for Apache Spark requires version 3.1.1, 3.1.2, 3.1.3, 3.2.0, or 3.2.1 of
+The RAPIDS Accelerator for Apache Spark requires version 3.1.1, 3.1.2, 3.1.3, 3.2.0, 3.2.1 or 3.3.0 of
 Apache Spark. Because the plugin replaces parts of the physical plan that Apache Spark considers to
 be internal the code for those plans can change even between bug fix releases. As a part of our
 process, we try to stay on top of these changes and release updates as quickly as possible.

docs/dev/shims.md

@@ -7,7 +7,7 @@ parent: Developer Overview
 # Shim Development
 
 RAPIDS Accelerator For Apache Spark supports multiple feature version lines of 
-Apache Spark such as 3.1.x, 3.2.x, and a number of vendor releases that contain
+Apache Spark such as 3.1.x, 3.2.x, 3.3.0 and a number of vendor releases that contain
 a mix of patches from different upstream releases. These artifacts are generally 
 incompatible between each other, at both source code level and even more often 
 at the binary level. The role of the Shim layer is to hide these issues from the 

docs/download.md

@@ -31,7 +31,7 @@ Software Requirements:
 
 	CUDA & NVIDIA Drivers*: 11.x & v450.80.02+
 
-	Apache Spark 3.1.1, 3.1.2, 3.1.3, 3.2.0, 3.2.1, Databricks 9.1 ML LTS or 10.4 ML LTS Runtime and GCP Dataproc 2.0
+	Apache Spark 3.1.1, 3.1.2, 3.1.3, 3.2.0, 3.2.1, 3.3.0, Databricks 9.1 ML LTS or 10.4 ML LTS Runtime and GCP Dataproc 2.0
 
 	Python 3.6+, Scala 2.12, Java 8