Merge pull request #119147 from SharonZhang1/update0124

add method

Author: Court72

articles/synapse-analytics/spark/media/microsoft-spark-utilities/spark-utilities-run-notebook-list.png

@@ -1,12 +1,12 @@
 ---
 title: Introduction to Microsoft Spark utilities
 description: "Tutorial: MSSparkutils in Azure Synapse Analytics notebooks"
-author: ruixinxu
+author: JeneZhang
 ms.service: synapse-analytics
 ms.topic: reference
 ms.subservice: spark
 ms.date: 09/10/2020
-ms.author: ruxu
+ms.author: jingzh
 zone_pivot_groups: programming-languages-spark-all-minus-sql
 ms.custom: subject-rbac-steps, devx-track-python
 ---
@@ -390,6 +390,17 @@ mssparkutils.fs.cp('source file or directory', 'destination file or directory',
 ```
 ::: zone-end
 
+### Performant copy file
+
+This method provides a faster way of copying or moving files, especially large volumes of data.
+
+```python
+mssparkutils.fs.fastcp('source file or directory', 'destination file or directory', True) # Set the third parameter as True to copy all files and directories recursively
+```
+
+> [!NOTE]
+> The method only supports in Spark 3.3 and Spark 3.4.
+
 ### Preview file content
 
 Returns up to the first 'maxBytes' bytes of the given file as a String encoded in UTF-8.
@@ -605,6 +616,75 @@ After the run finished, you will see a snapshot link named '**View notebook run:
 
 ![Screenshot of a snap link python](./media/microsoft-spark-utilities/spark-utilities-run-notebook-snap-link-sample-python.png)
 
+### Reference run multiple notebooks in parallel
+
+The method `mssparkutils.notebook.runMultiple()` allows you to run multiple notebooks in parallel or with a predefined topological structure. The API is using a multi-thread implementation mechanism within a spark session, which means the compute resources are shared by the reference notebook runs.
+
+With `mssparkutils.notebook.runMultiple()`, you can:
+
+- Execute multiple notebooks simultaneously, without waiting for each one to finish.
+
+- Specify the dependencies and order of execution for your notebooks, using a simple JSON format.
+
+- Optimize the use of Spark compute resources and reduce the cost of your Synapse projects.
+
+- View the Snapshots of each notebook run record in the output, and debug/monitor your notebook tasks conveniently.
+
+- Get the exit value of each executive activity and use them in downstream tasks.
+
+You can also try to run the mssparkutils.notebook.help("runMultiple") to find the example and detailed usage.
+
+Here's a simple example of running a list of notebooks in parallel using this method:
+
+```python
+
+mssparkutils.notebook.runMultiple(["NotebookSimple", "NotebookSimple2"])
+
+```
+
+The execution result from the root notebook is as follows:
+
+:::image type="content" source="media\microsoft-spark-utilities\spark-utilities-run-notebook-list.png" alt-text="Screenshot of reference a list of notebooks." lightbox="media\microsoft-spark-utilities\spark-utilities-run-notebook-list.png":::
+
+The following is an example of running notebooks with topological structure using `mssparkutils.notebook.runMultiple()`. Use this method to easily orchestrate notebooks through a code experience.
+
+```python
+# run multiple notebooks with parameters
+DAG = {
+    "activities": [
+        {
+            "name": "NotebookSimple", # activity name, must be unique
+            "path": "NotebookSimple", # notebook path
+            "timeoutPerCellInSeconds": 90, # max timeout for each cell, default to 90 seconds
+            "args": {"p1": "changed value", "p2": 100}, # notebook parameters
+        },
+        {
+            "name": "NotebookSimple2",
+            "path": "NotebookSimple2",
+            "timeoutPerCellInSeconds": 120,
+            "args": {"p1": "changed value 2", "p2": 200}
+        },
+        {
+            "name": "NotebookSimple2.2",
+            "path": "NotebookSimple2",
+            "timeoutPerCellInSeconds": 120,
+            "args": {"p1": "changed value 3", "p2": 300},
+            "retry": 1,
+            "retryIntervalInSeconds": 10,
+            "dependencies": ["NotebookSimple"] # list of activity names that this activity depends on
+        }
+    ]
+}
+mssparkutils.notebook.runMultiple(DAG)
+
+```
+
+> [!NOTE]
+>
+> - The method only supports in Spark 3.3 and Spark 3.4.
+> - The parallelism degree of the multiple notebook run is restricted to the total available compute resource of a Spark session.
+
+
 ### Exit a notebook
 Exits a notebook with a value. You can run nesting function calls in a notebook interactively or in a pipeline.