I am new to AWS Glue. I have created a job that uses two Data Catalog tables and runs simple SparkSQL query on top of them. The job fails on the Transform step with Exception
pyspark.sql.utils.AnalysisException: 'java.lang.RuntimeException: com.amazonaws.SdkClientException: Unable to execute HTTP request: Connect to glue.us-east-1.amazonaws.com:443 [blah] failed: connect timed out;'
JDBC source (Redshift) VPC security group has both inbound and outbound rules configured.
I have seen another post on SO about configuring VPC endpoint for Glue itself, but I don't quite understand what it should look like? Should it be and interface to glue.us-east-1.amazonaws.com:443 or something else? I am confused.
UPD: Autogenerated pyspark script
## @params: [TempDir, JOB_NAME]
args = getResolvedOptions(sys.argv, ['TempDir','JOB_NAME'])
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
## @type: DataSource
## @args: [database = "redshift_catalog", redshift_tmp_dir = TempDir, table_name = "analytics_mongo_raw_conversations", transformation_ctx = "DataSource0"]
## @return: DataSource0
## @inputs: []
DataSource0 = glueContext.create_dynamic_frame.from_catalog(database = "redshift_catalog", redshift_tmp_dir = args["TempDir"], table_name = "analytics_mongo_raw_conversations", transformation_ctx = "DataSource0")
## @type: DataSource
## @args: [database = "redshift_catalog", redshift_tmp_dir = TempDir, table_name = "analytics_mongo_raw_messages", transformation_ctx = "DataSource1"]
## @return: DataSource1
## @inputs: []
DataSource1 = glueContext.create_dynamic_frame.from_catalog(database = "redshift_catalog", redshift_tmp_dir = args["TempDir"], table_name = "analytics_mongo_raw_messages", transformation_ctx = "DataSource1")
## @type: SqlCode
## @args: [sqlAliases = {"messages": DataSource1, "conversations": DataSource0}, sqlName = SqlQuery0, transformation_ctx = "Transform0"]
## @return: Transform0
## @inputs: [dfc = DataSource1,DataSource0]
Transform0 = sparkSqlQuery(glueContext, query = SqlQuery0, mapping = {"messages": DataSource1, "conversations": DataSource0}, transformation_ctx = "Transform0")
job.commit()
I was able to resolve this issue, indeed there has to be a VPC endpoint. In addition to that connection should use a private subnet with NAT gateway. My initial subnet didn't have NAT.
Example of the VPC endpoint configuration in Terraform:
resource "aws_vpc_endpoint" "glue" {
vpc_id = var.vpc_id
service_name = var.glue_vpc_service_name
vpc_endpoint_type = "Interface"
security_group_ids = var.security_group_ids
subnet_ids = var.subnet_ids
tags = { mytag = "mytag"}
}
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