Databricks only provides cluster level logs in the UI or in the API. Is there a way to configure spark or log4j in databricks such that we get run/job level logs?
You can find a Guide on Monitoring Azure Databricks on the Azure Architecture Center, explaining the concepts used in this article - Monitoring And Logging In Azure Databricks With Azure Log Analytics And Grafana.
To provide full data collection, we combine the Spark monitoring library with a custom log4j.properties configuration. The build of the monitoring library for Spark 2.4 and the installation in Databricks is automated through the scripts referenced in the tutorial and available at https://github.com/algattik/databricks-monitoring-tutorial/.
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I have created a log analytics workspace which used the grab all metrics from a databricks cluster.
Actually, my query would be to get the times when the cluster were running more than 10 worker instances. Can I find this information through log analytics in azure for databricks?
any hint would be apprecited.
You can use the Log4j appender to send your Azure Databricks application logs to Azure Log Analytics.
Refer Send application logs using Log4j to know the steps to implement the same.
You can also visualize the Databricks resource metrics using Grafana and Virtual Machine. Check this official Microsoft documentation for the same. Use dashboards to visualize Azure Databricks metrics
I created notebooks in Azure databricks workspace and want to monitor my notebooks by using Log Analytics workspace but I could not see any log metrics for databricks notebook because databricks is a third-party tool. Like as we create log metrics monitoring for Azure SQL database by using log analytics with SQL analytics. After following few docs and blogs I got to know there is no inbuilt feature in log analytics for monitoring databricks notebook, I have to write custom code(using Python) for monitoring databricks notebook. Team, could you please help me here if anyone has implemented the same and have some idea. I followed this link:
https://learn.microsoft.com/en-us/azure/databricks/administration-guide/account-settings/azure-diagnostic-logs
Have you tried the steps mentioned in this document: “Diagnostic logging in Azure Databricks”?
By configuring Diagnostic setting, you can configure the collection of following data:
{ dbfs, clusters, accounts, jobs, notebook,ssh, workspace, secrets, sqlPermissions, instancePools}
STEP1: Make sure you have configured the diagnostic setting.
STEP2: After configuring the diagnostic setting, you can go to Log Analytics Workspace => Logs => Log Management => You will find Databricks Notebook => Run the below query to get the details about the notebook.
DatabricksNotebook
| where TimeGenerated > ago(24h)
| limit 10
STEP3: You can select any one from the results and check all the details regarding the notebook.
I have asked similar question but I would like to ask question if I can use Microsoft Azure to achieve my goal.
Is streaming input from external database (postgresql) supported in Apache Spark?
I have a database deployed on Microsoft Azure Postgresql. I have a table which I want to stream access from . Using Kafka connect , it seems that I could stream access the table, however, looking on online document , I could not find database(postgresql) as a datasource .
Does azure databricks suport stream reading postgresql table ? Or is it better to use
azure HDInsight with kafka and spark ?
I appreciate if I could get some help.
Best Regards,
Yu Watanabe
Unfortunately, Azure Databricks does not support stream reading of Azure postgresql database.
Azure HDInsight with Kafka and Spark will be the right choice for your requirement.
Managed Kafka and integration with other HDInsight offerings that can be used to make a complete data platform.
Azure also offers a range of other managed services needed in a data platform such as SQL Server, Postgre, Redis and Azure IoT Event Hub.
As per my research, I have found a third-party tool name "Panoply" which integrate Databricks and PostgreSQL using Panoply.
Hope this helps.
Has anyone tried using Azure data bricks as the spark cluster for CDAP job processing. CDAP documentation details how to add it to Azure HDInsight, but just wondering is there a way to configure CDAP to point to data bricks spark cluster, is it even possible? OR this kind of integration needs a specific data bricks client connector jar? If anyone has any insights that would be helpful.
There is no out of box support for Databricks spark on Azure. But, that said you can develop a new Cloud Runtime that is capable of submitting the jobs to Databricks spark cluster. Here is example of how to write a runtime extension for Cloud Dataproc and EMR.
Has bluemix removed apache spark service from its services ? I want to create one but did not find it in Data and Analytics section.
The Apache Spark service is still present in Bluemix and in that section. Here is the direct link to the Apache Spark service.