diff --git a/doc/amazon_sagemaker_processing.rst b/doc/amazon_sagemaker_processing.rst
index ac168578cd..81294ff60a 100644
--- a/doc/amazon_sagemaker_processing.rst
+++ b/doc/amazon_sagemaker_processing.rst
@@ -83,7 +83,7 @@ First you need to create a :class:`PySparkProcessor` object
 
 .. code:: python
 
-    from sagemaker.processing import PySparkProcessor, ProcessingInput
+    from sagemaker.spark.processing import PySparkProcessor
 
     spark_processor = PySparkProcessor(
         base_job_name="sm-spark",
@@ -157,11 +157,14 @@ To successfully run the history server, first you need to make sure ``docker`` i
 SparkJarProcessor
 ---------------------
 
-Supposed that you have the jar file "preprocessing.jar" stored in the same directory as you are now, and the java package is ``com.path.to.your.class.PreProcessing.java``
-Here's an example of using PySparkProcessor.
+Suppose that you have the jar file "preprocessing.jar" stored in the same directory as you are now, and the java package is ``com.path.to.your.class.PreProcessing.java``.
+
+Here's an example of using SparkJarProcessor.
 
 .. code:: python
 
+    from sagemaker.spark.processing import SparkJarProcessor
+
     spark = SparkJarProcessor(
         base_job_name="sm-spark-java",
         image_uri=beta_image_uri,