Пытаюсь прочитать данные JDBC из базы данных SAP HANA с помощью Spark JDBC и записать то же самое, что и паркет в s3.Ниже приведены детали программы и ошибки.Код просто пытается извлечь данные из базы данных SAP Hana и записывает в s3
import sys
import boto3
import json
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.dynamicframe import DynamicFrame
from awsglue.job import Job
sc = SparkContext()
glueContext = GlueContext(sc)
spark = glueContext.spark_session
db_username = "XXXXXXX"
db_password = "XXXXXXX"
db_url = "jdbc:sap://10.6.71.40:30015"
jdbc_driver_name = "com.sap.db.jdbc.Driver"
table_name = "\"_SYS_BIC\".\"DataLakeV2.MTC_Utilities.Customer/BPRelations_v1\""
s3_output = "s3://aws-glue-temporary-112027068953-us-east-1/BPRelations_v1/"
df_delta = spark.read.format("jdbc").option("driver", jdbc_driver_name).option("url", db_url).option("user", db_username).option("password", db_password).option("dbtable", table_name).load()
df_delta.write.mode("overwrite").parquet(s3_output)
Ниже приведено сообщение об ошибке.Задание не выполняется точно на последнем этапе при записи данных в паркет.
Container: container_1552941975871_0001_01_000001 on ip-10-16-41-115.ec2.internal_8041
LogType:stdout
Log Upload Time:Mon Mar 18 20:56:12 +0000 2019
LogLength:8682
Log Contents:
Traceback (most recent call last):
File "script_2019-03-18-20-54-13.py", line 23, in <module>
df_delta.write.mode("overwrite").parquet(s3_output)
File "/mnt/yarn/usercache/root/appcache/application_1552941975871_0001/container_1552941975871_0001_01_000001/pyspark.zip/pyspark/sql/readwriter.py", line 691, in parquet
File "/mnt/yarn/usercache/root/appcache/application_1552941975871_0001/container_1552941975871_0001_01_000001/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/mnt/yarn/usercache/root/appcache/application_1552941975871_0001/container_1552941975871_0001_01_000001/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
File "/mnt/yarn/usercache/root/appcache/application_1552941975871_0001/container_1552941975871_0001_01_000001/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o73.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply$mcV$sp(FileFormatWriter.scala:213)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:166)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:166)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:166)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:145)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92)
at org.apache.spark.sql.execution.datasources.DataSource.writeInFileFormat(DataSource.scala:435)
at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:471)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:50)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:609)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:233)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:217)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:508)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, ip-10-16-41-115.ec2.internal, executor 1): org.apache.spark.SparkException: Task failed while writing rows