I am new to AWS Glue studio. I am trying to create a job involving multiple joins and custom code. Trying to read data from Glue catalog and writing the data into S3 bucket. It was working fine untill recently. I only increased more number of withColumn operations in custom transform block. Now when i try to save the job i am getting error as follows:
Failed to update job
[gluestudio-service.us-east-2.amazonaws.com] updateDag: InternalFailure: null
I tried cloning the job and doing changes on it. I also tried creating a new job from scratch.
Related
I've been using AWS Glue studio for Job creation. Till now I was using Job Legacy but recently Amazon has migrated to the new version Glue Job v_3.0 Where I am trying to create a job using Spark script editor.
Steps to be followed
Open Region-Code/console.aws.amazon.com/glue/home?region=Region-Code#/v2/home
Click Create Job link
Select Spark script editor
Make sure you selected the Create a new script with boilerplate code
Then click the Create button in the top right corner.
When I try to save the Job after fill all the required information, I'm getting an error like below
Failed to update job
[gluestudio-service.us-east-1.amazonaws.com] createJob: InternalServiceException: Failed to meet resource limits for operation
Screenshot
Note
I've tried the Legacy Job creation as well where I was getting an error like below
{"service":"AWSGlue","statusCode":400,"errorCode":"ResourceNumberLimitExceededException","requestId":"179c2de8-6920-4adf-8791-ece7cbbfbc63","errorMessage":"Failed to meet resource limits for operation","type":"AwsServiceError"}
Is this something related to Internal configuration issue?
As I was using client's provided account I don't have permission to see the Limitations and all
We're trying to use AWS Glue for ETL operations in our nodejs project. The workflow will be like below
user uploads csv file
data transformation from XYZ format to ABC format(mapping and changing field names)
download transformed csv file to local system
Note that, this flow should happen programmatically(creating crawlers, job triggers should be done programmatically not using the console). I don't know why documentation and other articles always show how to create crawlers, create jobs from glue console?
I believe that we have to create lambda functions and triggers. but not quite sure how to achieve this end to end flow. can anyone please help me. Thanks
I've got an SQS queue that will be filled with a json message when my S3 bucket has any CREATE event.
Message contains bucket and object name
Also have Docker image which contains python script that will read message from sqs. With help of that message, it will download respective object from S3. Finally script will read the object and put some values in dynamodb.
1.When submitting as single job to AWS batch, I can able achieve above use case. But it's time consuming because I have 80k object and average size of object 300 MB.
When submitting as multi-node Parallel Job. Job is getting stuck in Running state and master node goes to failed state.
Note: Object Type is MF4 (Measurement File) from vehicle logger. So need to download to local to read the object using asammdf.
Question 1: How to use AWS batch multi node parallel Job.
Question 2: Can I try any other services for achieving parallelism.
Answers with examples will be more helpful.
Thanks😊
I think you're looking for AWS Batch Array Jobs, not MNP Jobs. MNP jobs are for spreading one job across multiple hosts (MPI or NCCL).
Since I'm not allowed to ask my question in the same thread where another person have the same problem (but not using a template) I'm creating this new thread.
The problem: Im creating a dataflow job from a template in gcp to ingest data from pub/sub into BQ. This works fine until the job executes. The job gets "stuck" and does not write anything to BQ.
I cant do so much because I cant choose the beam version in the template. This is the error:
Processing stuck in step WriteSuccessfulRecords/StreamingInserts/StreamingWriteTables/StreamingWrite for at least 01h00m00s without outputting or completing in state finish
at sun.misc.Unsafe.park(Native Method)
at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
at java.util.concurrent.FutureTask.awaitDone(FutureTask.java:429)
at java.util.concurrent.FutureTask.get(FutureTask.java:191)
at org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$DatasetServiceImpl.insertAll(BigQueryServicesImpl.java:803)
at org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$DatasetServiceImpl.insertAll(BigQueryServicesImpl.java:867)
at org.apache.beam.sdk.io.gcp.bigquery.StreamingWriteFn.flushRows(StreamingWriteFn.java:140)
at org.apache.beam.sdk.io.gcp.bigquery.StreamingWriteFn.finishBundle(StreamingWriteFn.java:112)
at org.apache.beam.sdk.io.gcp.bigquery.StreamingWriteFn$DoFnInvoker.invokeFinishBundle(Unknown Source)
Any ideas how to get this to work?
The issue is coming from the step WriteSuccessfulRecords/StreamingInserts/StreamingWriteTables/StreamingWrite which suggest a problem while writing the data.
Your error can be replicated by (using either Pub/Sub Subscription to BigQuery or Pub/Sub Topic to BigQuery):
Configuring a template with a table that doesn't exist.
Starting the
template with a correct table and delete it during the job execution.
In both cases the stuckness message happens because the data is being read from Pubsub but it is waiting for the table availability to insert the data. The error is being reported each 5 minutes and it gets resolved when the table is created.
To verify the table configured in your template, see the property outputTableSpec in the PipelineOptions in the Dataflow UI.
I had the same issue before. The problem was that I used NestedValueProviders to evaluate the Pub/Sub topic/subscription and this is not supported in case of templated pipelines.
I was getting the same error and reason was that I created an empty BigQuery table without specifying an schema. Make sure to create a BQ table with a schema before you can load data via Dataflow.
I have CSV file in the GCP Bucket, which I need to move to the Google Cloud Datastore. The CSV Shape format is (60000, 6). Using cloud Dataflow I wrote a Pipeline and moved into the datastore. The Dataflow Job is Successfully Completed. But when I check the data in data store there are no entities. This is the Pipeline image for your reference.
and the pool node graph is here.
.
From the pipeline Graph, I came to know that it didn't do any job on creating an Entities and writing into the datastore**(0 secs)**.
To do this job, I have referred this tutorial Uploading CSV File to The Datastore.
It will be more helpful if I get to know where the pipeline went wrong?