在sagemaker jupyter示例中-r kernal。
在spark\u read\u csv函数中,在我们将spark版本升级到3.0.1和hadoop版本升级到2.7之后,出现以下错误。
'/home/ec2-user/spark/spark-3.0.1-bin-hadoop2.7'
A data.frame: 4 × 3
spark hadoop dir
<chr> <chr> <chr>
2.4.3 2.7 /home/ec2-user/spark/spark-2.4.3-bin-hadoop2.7
2.4.7 2.7 /home/ec2-user/spark/spark-2.4.7-bin-hadoop2.7
3.0.1 2.7 /home/ec2-user/spark/spark-3.0.1-bin-hadoop2.7
3.0.1 3.2 /home/ec2-user/spark/spark-3.0.1-bin-hadoop3.2
getSC <-function ()
{
config<-spark_config()
config$sparklyr.defaultPackages <- c(
"com.databricks:spark-csv_2.10:1.5.0",
"com.amazonaws:aws-java-sdk-pom:1.10.34",
"org.apache.hadoop:hadoop-aws:2.7.3")
print(config)
options(sparklyr.log.console = TRUE)
sc <- spark_connect(master="local" )
ctx <- spark_context(sc)
jsc <- invoke_static(sc,
"org.apache.spark.api.java.JavaSparkContext",
"fromSparkContext",
ctx)
hconf <- jsc %>% invoke("hadoopConfiguration")
hconf %>% invoke("set", "com.amazonaws.services.s3a.enableV4", "true")
hconf %>% invoke("set", "fs.s3a.S3AFileSystem", "true")
hconf %>% invoke("set", "fs.s3a.fast.upload", "true")
hconf %>% invoke("set", "fs.s3a.impl", "org.apache.hadoop.fs.s3a.S3AFileSystem")
hconf %>% invoke("set","fs.s3a.access.key", "Xxxx")
hconf %>% invoke("set","fs.s3a.secret.key", "Xxxxx"
hconf %>% invoke("set","fs.s3a.endpoint", "xxxx")
return (sc)
}
sc <- getSC()
constituents<-spark_read_csv(sc,name = "constituents",null_value="NA", path=folder_files,infer_schema = TRUE,header = T,delimiter = "," , mode="overwrite")
print(3)
例外情况:
Error: java.util.ServiceConfigurationError: org.apache.spark.sql.sources.DataSourceRegister: Provider com.amazonaws.services.sagemaker.sparksdk.protobuf.SageMakerProtobufFileFormat could not be instantiated
at java.base/java.util.ServiceLoader.fail(ServiceLoader.java:581)
at java.base/java.util.ServiceLoader$ProviderImpl.newInstance(ServiceLoader.java:803)
at java.base/java.util.ServiceLoader$ProviderImpl.get(ServiceLoader.java:721)
at java.base/java.util.ServiceLoader$3.next(ServiceLoader.java:1394)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:44)
暂无答案!
目前还没有任何答案,快来回答吧!