def test_logs_batch_query():
client = LogsQueryClient(_credential())
requests = [
LogsQueryRequest(query="AzureActivity | summarize count()",
timespan="PT1H",
workspace=os.environ['LOG_WORKSPACE_ID']),
LogsQueryRequest(query="""AppRequests | take 10 |
summarize avgRequestDuration=avg(DurationMs) by bin(TimeGenerated, 10m), _ResourceId""",
timespan="PT1H",
workspace=os.environ['LOG_WORKSPACE_ID']),
LogsQueryRequest(query="AppRequests | take 2",
workspace=os.environ['LOG_WORKSPACE_ID']),
]
response = client.batch_query(requests)
assert len(response.responses) == 3
"query": "AzureActivity | summarize count()",
"timespan": "PT1H"
},
"method": "POST",
"path": "/query",
"workspace": os.environ['LOG_WORKSPACE_ID']
},
{
"id": "2",
"headers": {
"Content-Type": "application/json"
},
"body": {
"query": "AzureActivity | summarize count()",
"timespan": "PT1H"
},
"method": "POST",
"path": "/fakePath",
"workspace": os.environ['LOG_WORKSPACE_ID']
}
]
response = client.batch_query(requests)
for response in response.responses:
body = response.body
if not body.tables:
print("Something is wrong")
else:
for table in body.tables:
df = pd.DataFrame(table.rows, columns=[col.name for col in table.columns])
print(df)