Troubleshooting the Neptune export process
The Amazon Neptune export process uses AWS Batch
to provision the compute and storage resources necessary to export your Neptune data.
When an export is running, you can use the link in the logs
field to access
the CloudWatch logs for the export job.
However, the CloudWatch logs for the AWS Batch job that performs the export are only available
when the AWS Batch job is running. If Neptune export reports that an export is in a pending
state, there won’t be a logs link through which you can access CloudWatch logs. If an export job
remains in the pending
state for more than a few minutes, there may be a
problem provisioning the underlying AWS Batch resources.
When the export job leaves the pending state, you can check its status as follows:
To check the status of a AWS Batch job
Open the AWS Batch console at https://console.aws.amazon.com/batch/
. Select the neptune-export job queue.
Look for the job whose name matches the
jobName
returned by Neptune export when you started the export.
If the job remains stuck in a RUNNABLE
state, it may be because
networking or security issues are preventing the container instance from joining
the underlying Amazon Elastic Container Service (Amazon ECS) cluster. See the section about verifying network and security
settings of the compute environment in this
support article
Another thing you can check is for problems with auto-scaling:
To check the Amazon EC2 auto-scaling group for the AWS Batch compute environment
Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/
. Select the Auto Scaling group for the neptune-export compute environment.
Open the Activity tab and check the activity history for unsuccessful events.
Neptune Export common errors
org.eclipse.rdf4j.query.QueryEvaluationException: Tag mismatch!
If an export-rdf
job is regularly failing with a Tag mismatch!
QueryEvaluationException
, the Neptune instance is undersized for the large,
long-running queries used by Neptune Export.
You can avoid getting this error by scaling up to a larger Neptune instance or by configuring the job to export from a large cloned cluster, like this:
'{ "command": "export-rdf", "outputS3Path": "s3://
(your Amazon S3 bucket)
/neptune-export", "params": { "endpoint": "(your Neptune endpoint DNS name)
", "cloneCluster": True, "cloneClusterInstanceType" : "r5.24xlarge" } }'