I am trying to read a simple csv file Azure Data Lake Storage V2 with Spark 2.4 on my IntelliJ-IDE on mac
Code Below
package com.example
import org.apache.spark.SparkConf
import org.apache.spark.sql._
object Test extends App {
val appName: String = "DataExtract"
val master: String = "local[*]"
val sparkConf: SparkConf = new SparkConf()
.setAppName(appName)
.setMaster(master)
.set("spark.scheduler.mode", "FAIR")
.set("spark.sql.session.timeZone", "UTC")
.set("spark.sql.shuffle.partitions", "32")
.set("fs.defaultFS", "abfs://development@xyz.dfs.core.windows.net/")
.set("fs.azure.account.key.xyz.dfs.core.windows.net", "~~key~~")
val spark: SparkSession = SparkSession
.builder()
.config(sparkConf)
.getOrCreate()
spark.time(run(spark))
def run(spark: SparkSession): Unit = {
val df = spark.read.csv("abfs://development@xyz.dfs.core.windows.net/development/sales.csv")
df.show(10)
}
}
It's able to read, and throwing security exception
Exception in thread "main" java.lang.NullPointerException
at org.wildfly.openssl.CipherSuiteConverter.toJava(CipherSuiteConverter.java:284)
at org.wildfly.openssl.OpenSSLEngine.toJavaCipherSuite(OpenSSLEngine.java:1094)
at org.wildfly.openssl.OpenSSLEngine.getEnabledCipherSuites(OpenSSLEngine.java:729)
at org.wildfly.openssl.OpenSSLContextSPI.getCiphers(OpenSSLContextSPI.java:333)
at org.wildfly.openssl.OpenSSLContextSPI$1.getSupportedCipherSuites(OpenSSLContextSPI.java:365)
at org.apache.hadoop.fs.azurebfs.utils.SSLSocketFactoryEx.<init>(SSLSocketFactoryEx.java:105)
at org.apache.hadoop.fs.azurebfs.utils.SSLSocketFactoryEx.initializeDefaultFactory(SSLSocketFactoryEx.java:72)
at org.apache.hadoop.fs.azurebfs.services.AbfsClient.<init>(AbfsClient.java:79)
at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.initializeClient(AzureBlobFileSystemStore.java:817)
at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.<init>(AzureBlobFileSystemStore.java:149)
at org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.initialize(AzureBlobFileSystem.java:108)
Can anyone help me, what is the mistake?
As per my research, you will receive this error message when you have incompatible jar with the hadoop version.
I would request you to kindly go through the below issues: