aws-glue - Py4JJavaError：调用 o67.getDynamicFrame 时出错。java.lang.reflect.InvocationTargetException

Question

在使用 DynamicFrame 处理数据结构类型的嵌套 json 文件时。当我运行作业时出现此错误

Py4JJavaError：调用 o67.getDynamicFrame 时出错。java.lang.reflect.InvocationTargetException.让我知道我在哪里犯错了关于这个的任何想法

以下是我在 GLUE JOB 中的代码

import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.dynamicframe import DynamicFrame, DynamicFrameReader,             
DynamicFrameWriter, DynamicFrameCollection
from pyspark.sql.functions import lit
from awsglue.job import Job

## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv, ['JOB_NAME'])

sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
## @type: DataSource
## @args: [database = "experimentdb", table_name = "experiment",         
transformation_ctx = "datasource0"]
## @return: datasource0
## @inputs: []
datasource0 = glueContext.create_dynamic_frame.from_catalog(database =     
"experimentdb", table_name = "experiment", transformation_ctx = 
"datasource0")
## @type: ApplyMapping
## @args: [mapping = [("id", "string", "id", "string"), ("identifier", 
"string", "identifier", "string"), ("session_count", "long", 
"session_count", "long"), ("language", "string", "language", "string"),     
("timezone", "long", "timezone", "long"), ("game_version", "string", 
"game_version", "string"), ("device_os", "string", "device_os", "string"), 
("device_type", "long", "device_type", "long"), ("device_model", "string", 
"device_model", "string"), ("ad_id", "string", "ad_id", "string"), 
("tags.phone_number", "string", "`tags.phone_number`", "string"), 
("tags.real_name", "string", "`tags.real_name`", "string"), ("tags.email",     
"string", "`tags.email`", "string"), ("tags.onboardingStatus", "string", 
"`tags.onboardingStatus`", "string"), ("tags.dfuStatus", "string", 
"`tags.dfuStatus`", "string"), ("tags.activityStatus", "string", 
"`tags.activityStatus`", "string"), ("tags.lastOperationPerformed", 
"string", "`tags.lastOperationPerformed`", "string"), ("last_active", 
"string", "last_active", "string"), ("playtime", "long", "playtime", 
"long"), ("amount_spent", "double", "amount_spent", "double"), 
("created_at", "string", "created_at", "string"), ("invalid_identifier", 
"string", "invalid_identifier", "string"), ("badge_count", "long", 
"badge_count", "long")], transformation_ctx = "applymapping1"]
## @return: applymapping1
## @inputs: [frame = datasource0]
applymapping1 = ApplyMapping.apply(frame = datasource0, mappings = [("id", 
"string", "id", "string"), ("identifier", "string", "identifier", 
"string"), ("session_count", "long", "session_count", "long"), ("language", 
"string", "language", "string"), ("timezone", "long", "timezone", "long"), 
("game_version", "string", "game_version", "string"), ("device_os", 
"string", "device_os", "string"), ("device_type", "long", "device_type", 
"long"), ("device_model", "string", "device_model", "string"), ("ad_id", 
"string", "ad_id", "string"), ("tags.phone_number", "string", 
"`tags.phone_number`", "string"), ("tags.real_name", "string", 
"`tags.real_name`", "string"), ("tags.email", "string", "`tags.email`", 
"string"), ("tags.onboardingStatus", "string", "`tags.onboardingStatus`", 
"string"), ("tags.dfuStatus", "string", "`tags.dfuStatus`", "string"),     
("tags.activityStatus", "string", "`tags.activityStatus`", "string"), 
("tags.lastOperationPerformed", "string", "`tags.lastOperationPerformed`", 
"string"), ("last_active", "string", "last_active", "string"), ("playtime", 
"long", "playtime", "long"), ("amount_spent", "double", "amount_spent", 
"double"), ("created_at", "string", "created_at", "string"), 
("invalid_identifier", "string", "invalid_identifier", "string"), 
("badge_count", "long", "badge_count", "long")], transformation_ctx = 
"applymapping1")
## @type: DataSink
## @args: [connection_type = "s3", connection_options = {"path": 
"s3://output_data"}, format = "csv", transformation_ctx 
= "datasink2"]
## @return: datasink2
## @inputs: [frame = applymapping1]
datasink2 = glueContext.write_dynamic_frame.from_options(frame = 
applymapping1, connection_type = "s3", connection_options = {"path": 
"s3://output_data"}, format = "csv", transformation_ctx 
= "datasink2")
job.commit()

错误日志 错误日志1

标签： aws-glue

Answer 1

您似乎遇到了连接错误。由于 S3 是您使用的唯一数据源，而且您没有创建 VPC S3 终端节点，我怀疑这就是问题所在。

不幸的是，Glue 错误日志并不能提供真正的信息，因此只能假设。我会要求您创建一个VPC S3 端点并再试一次。