How to export the logs for your job run in databricks?it should automatically deliver the logs to DBFS.
To automate this process, you can set up your job so that it automatically delivers logs to DBFS through the Job API. Explained in method2
Method1: Manually you enable cluster logging through Azure Databricks UI
In the Azure portal navigate to Job > Configure Cluster. Under Advanced Options click Logging. Enter the following information.
Destination: Select DBFS.
CLuster Log Path: Enter dbfs:/cluster-logs.
Method2: Automate using Azure Databricks Job API
Using the /api/2.0/jobs/create specify the following in the request body.
{
"new_cluster": {
"cluster_log_conf": {
"dbfs": {
"destination": "dbfs:/cluster-logs"
}
}
}
}
For more information, see the NewCluster and ClusterLogConf fields in the Job Create API call.
Related
I am trying to save Apache Spark logs (the contents of Spark UI), not necessarily stderr, stdout and log4j files (although they might be useful too) to a file so that I can send it over to someone else to analyze.
I am following the manual described in the Apache Spark documentation here:
https://spark.apache.org/docs/latest/monitoring.html#viewing-after-the-fact
The problem is that I am running the code on Azure Databricks. Databricks saves the logs elsewhere and you can display them from the web UI but cannot export it.
When I ran the Spark job with spark.eventLog.dir set to a location in DBFS, the file was created but it was empty.
Is there a way to export the full Databricks job log so that anyone can open it without giving them the access to the workspace?
The simplest way of doing it as following:
You create a separate storage account + container in it or a separate container in existing storage account & give access to it to developers
You mount that container to the Databricks workspace
You configure clusters/jobs to write logs into mount location (you can enforce it for new objects using the cluster policies). This will create sub-directories with the cluster name, containing logs of driver & executors + result of execution of init scripts
(optional) you can setup retention policy on that container to automatically remove old logs.
I have an Azure Container Instance running a docker image of Coldfusion application.
I also configured this Container Instance to Log Analytics Workspace.
Now I need the Coldfusion logs to show at Log Analytics Workspace. I am unable to get those logs.
Is there a way to get those logs at Log Analytics Workspace.
Assuming you have integrated the log analytic workspace after creation of azure container instance.
If this is the case it won't works for you, for storing logs of container instance we have to create the log analytic workspace while creating the azure container instance.
So you will need to delete and recreate the container instance.
You can refer this microsoft document for detailed information of how to store the logs in log analytic workspace.
you can also refer this link. for custom log.
Creating the log analytics workspace first and then providing the workspace ID and workspace key at container group creation worked fine for me (no need to create them both "at the same time"). Note, that it does take up to 10 minutes (according to the docs) for the ContainerInstanceLog_CL table to populate with your container's console logs.
Various programmatic ways to specify this at container creation, pertinent bit of C# client code shown below.
var containerGroupData = new ContainerGroupData(location, new[] { container }, ContainerInstanceOperatingSystemType.Linux);
var logAnalyticsWorkspaceId = ConfigurationManager.AppSettings["LogAnalyticsWorkspaceId"];
var logAnalyticsWorkspaceKey = ConfigurationManager.AppSettings["LogAnalyticsWorkspaceKey"];
containerGroupData.DiagnosticsLogAnalytics = new ContainerGroupLogAnalytics(logAnalyticsWorkspaceId, logAnalyticsWorkspaceKey);
I am trying to implement DevOps on Azure Databricks.
I have completed devops implementation for databricks notebooks and dbfs files.
I do have many databricks jobs running on my cluster based on schedule.
Some of these jobs points to notebook files and few points to jar file in the dbfs location.
Is there any way to implement devops process on the azure databricks jobs so that any change in any of the jobs in DEV will invoke build pipeline and deploy the same in PROD databricks instance.
First of all I wanted to know whether it is possible to implement devops on azure databricks jobs.
Any Leads Appreciated!
To do this effectively, I would recommend to use Databricks Terraform provider for that - in this case the definition of the job could be stored in the Git or something like, and then it's easy to integrate with CI/CD systems, such as Azure DevOps, GitHub Actions, etc.
The differences between environments could be the coded as variables with different files with variables for different environments, etc., so you can re-use the main code between environments, like this:
provider "databricks" {
host = var.db_host
token = var.db_token
}
data "databricks_spark_version" "latest" {}
data "databricks_node_type" "smallest" {
local_disk = true
}
resource "databricks_job" "this" {
name = "Job"
new_cluster {
num_workers = 1
spark_version = data.databricks_spark_version.latest.id
node_type_id = data.databricks_node_type.smallest.id
}
notebook_task {
notebook_path = "path_to_notebook"
}
email_notifications {}
}
P.S. Theoretically, you can implement some periodic task that will pull the jobs definitions from your original environment, and check if the jobs definitions has changed, and apply the changes to another environment. You can even track changes to the jobs definitions via diagnostic logs, and use that as trigger.
But all of this is just hacks - it's better to use Terraform.
Databricks VMs are pointing to Default Log Analytics but I want to point them to another one
If I try to move VMs to antoher workpacks it tells me that its locked
Error: cannot perform delete operation because following scope(s) are locked
Unfortunately, you are not allowed to move Log Analytics for the Managed Resource Group created in Azure Databricks using Azure portal.
Reason: By default, you cannot perform any write operation on the managed resource group which created by Azure Databricks.
If you try to modify anything in the managed resource group, you will see this error message:
{"details":[{"code":"ScopeLocked","message":"The scope '/subscriptions/xxxxxxxxxxxxxxxx/resourceGroups/databricks-rg-chepra-d7ensl75cgiki' cannot perform write operation because following scope(s) are locked: '/subscriptions/xxxxxxxxxxxxxxxxxxxx/resourceGroups/databricks-rg-chepra-d7ensl75cgiki'. Please remove the lock and try again."}]}
Possible way: You can specify tags as key-value pairs when while creating/modifying clusters, and Azure Databricks will apply these tags to cloud resources.
Possible way: Configure your Azure Databricks cluster to use the monitoring library.
This article shows how to send application logs and metrics from Azure Databricks to a Log Analytics workspace. It uses the Azure Databricks Monitoring Library.
Hope this helps.
I am trying to copy a file from a accessible data lake to blob storage while spinning up the cluster.
I am using this command from Azure documentation
hadoop distcp adl://data_lake_store_account.azuredatalakestore.net:443/myfolder wasb://container_name#storage_account_name.blob.core.windows.net/example/data/gutenberg
Now, If I am trying to automate this instead of hardcoding, how do I use this in script action. To be specific how can I dynamically get the the container name and storage_account_name associated while spinning up the cluster.
First as below,
A Script Action is simply a Bash script that you provide a URI to, and parameters for. The script runs on nodes in the HDInsight cluster.
So you just need to refer to the offical tutorial Script action development with HDInsight to write your script action and know how to run it. Or you can call the REST API Run Script Actions on a running cluster (Linux cluster only) to run it automatically.
For how to dynamically get the container name & storage account, a way for any language is to call the REST API Get configurations and extract the property of you want from the core-site in the JSON response, or just to call Get configuration REST API with parameter core-site as {configuration Type} in the url and extract the property of you want from the JSON response.
Hope it helps.