[Monitor][Query] Add resource centric query support (#29365)

This regenerates with autorest and provides an API for
users to query Azure Monitor logs directly from a resource
instead of going through the context of a Log Analytics workspace.

Signed-off-by: Paul Van Eck <paulvaneck@microsoft.com>

sdk/monitor/azure-monitor-query/CHANGELOG.md

@@ -4,6 +4,8 @@
 
 ### Features Added
 
+- Add the `query_resource` method to `LogsQueryClient` to allow users to query Azure resources directly without the context of a workspace. ([#29365](https://github.com/Azure/azure-sdk-for-python/pull/29365))
+
 ### Breaking Changes
 
 ### Bugs Fixed

sdk/monitor/azure-monitor-query/README.md

@@ -92,6 +92,7 @@ Each set of metric values is a time series with the following characteristics:
   - [Specify timespan](#specify-timespan)
   - [Handle logs query response](#handle-logs-query-response)
 - [Batch logs query](#batch-logs-query)
+- [Resource logs query](#resource-logs-query)
 - [Advanced logs query scenarios](#advanced-logs-query-scenarios)
   - [Set logs query timeout](#set-logs-query-timeout)
   - [Query multiple workspaces](#query-multiple-workspaces)
@@ -103,7 +104,7 @@ Each set of metric values is a time series with the following characteristics:
 
 ### Logs query
 
-This example shows getting a logs query. To handle the response and view it in a tabular form, the [pandas](https://pypi.org/project/pandas/) library is used. See the [samples][samples] if you choose not to use pandas.
+This example shows how to query a Log Analytics workspace. To handle the response and view it in a tabular form, the [pandas](https://pypi.org/project/pandas/) library is used. See the [samples][samples] if you choose not to use pandas.
 
 #### Specify timespan
 
@@ -148,7 +149,7 @@ try:
         print(df)
 except HttpResponseError as err:
     print("something fatal happened")
-    print (err)
+    print(err)
 ```
 
 #### Handle logs query response
@@ -219,18 +220,18 @@ requests = [
     LogsBatchQuery(
         query="AzureActivity | summarize count()",
         timespan=timedelta(hours=1),
-        workspace_id= os.environ['LOG_WORKSPACE_ID']
+        workspace_id=os.environ['LOG_WORKSPACE_ID']
     ),
     LogsBatchQuery(
         query= """bad query""",
         timespan=timedelta(days=1),
-        workspace_id= os.environ['LOG_WORKSPACE_ID']
+        workspace_id=os.environ['LOG_WORKSPACE_ID']
     ),
     LogsBatchQuery(
         query= """let Weight = 92233720368547758;
         range x from 1 to 3 step 1
         | summarize percentilesw(x, Weight * 100, 50)""",
-        workspace_id= os.environ['LOG_WORKSPACE_ID'],
+        workspace_id=os.environ['LOG_WORKSPACE_ID'],
         timespan=(datetime(2021, 6, 2, tzinfo=timezone.utc), datetime(2021, 6, 5, tzinfo=timezone.utc)), # (start, end)
         include_statistics=True
     ),
@@ -255,6 +256,39 @@ for res in results:
 
 ```
 
+### Resource logs query
+
+The following example demonstrates how to query logs directly from an Azure resource without the use of a Log Analytics workspace. Here, the `query_resource` method is used instead of `query_workspace`, and instead of a workspace ID, an Azure resource identifier is passed in (e.g. `/subscriptions/{subscription-id}/resourceGroups/{resource-group-name}/providers/{resource-provider}/{resource-type}/{resource-name}`).
+
+```python
+import os
+import pandas as pd
+from datetime import timedelta
+from azure.monitor.query import LogsQueryClient, LogsQueryStatus
+from azure.core.exceptions import HttpResponseError
+from azure.identity import DefaultAzureCredential
+
+credential  = DefaultAzureCredential()
+client = LogsQueryClient(credential)
+
+query = """AzureActivity | take 5"""
+
+try:
+    response = client.query_resource(os.environ['LOGS_RESOURCE_ID'], query, timespan=timedelta(days=1))
+    if response.status == LogsQueryStatus.PARTIAL:
+        error = response.partial_error
+        data = response.partial_data
+        print(error)
+    elif response.status == LogsQueryStatus.SUCCESS:
+        data = response.tables
+    for table in data:
+        df = pd.DataFrame(data=table.rows, columns=table.columns)
+        print(df)
+except HttpResponseError as err:
+    print("something fatal happened")
+    print(err)
+```
+
 ### Advanced logs query scenarios
 
 #### Set logs query timeout

sdk/monitor/azure-monitor-query/assets.json

@@ -2,5 +2,5 @@
   "AssetsRepo": "Azure/azure-sdk-assets",
   "AssetsRepoPrefixPath": "python",
   "TagPrefix": "python/monitor/azure-monitor-query",
-  "Tag": "python/monitor/azure-monitor-query_86a8ec0380"
+  "Tag": "python/monitor/azure-monitor-query_8b3197a327"
 }