Getting Authentication Error while accessing Azure Blob table (wasb) URL using PySpark

[vivek_sinha]

I am trying to access the Azure Blob table using Pyspark but getting an Authentication Error. Here I am passing SAS token (HTTP and HTTPS enabled) but it's working only with WASBS (HTTPS) URL, not with WASB (HTTP) URL.

Even I tried with Account key as well but didn't work.

The other way is working fine if I try to load the parquet file by passing the WASB URL, but this method is very slow and takes too much time to access the data.

Please help me understand why PySpark-Azure showing such behaviour.

We had a meeting with the Azure support team as well but they also couldn't find any issue from their end

Sample Code:

from pyspark.sql import SparkSession
 
    spark = SparkSession.builder.getOrCreate()
 
    spark.conf.set("fs.azure.sas.<container-name>.<storage-account>.blob.core.windows.net","<
 
SAS Token>")
 

Error Details:

Py4JJavaError: An error occurred while calling o146.table.
 
: java.util.concurrent.ExecutionException: org.apache.hadoop.fs.azure.AzureException: com.microsoft.azure.storage.StorageException: Cannot use HTTP with credentials that only support HTTPS.
 
    at org.sparkproject.guava.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:306)
 
    at org.sparkproject.guava.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:293)
 
    at org.sparkproject.guava.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
 
    at org.sparkproject.guava.util.concurrent.Uninterruptibles.getUninterruptibly(Uninterruptibles.java:135)
 
    at org.sparkproject.guava.cache.LocalCache$Segment.getAndRecordStats(LocalCache.java:2410)
 
    at org.sparkproject.guava.cache.LocalCache$Segment.loadSync(LocalCache.java:2380)
 
    at org.sparkproject.guava.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342)
 
    at org.sparkproject.guava.cache.LocalCache$Segment.get(LocalCache.java:2257)
 
    at org.sparkproject.guava.cache.LocalCache.get(LocalCache.java:4000)
 
    at org.sparkproject.guava.cache.LocalCache$LocalManualCache.get(LocalCache.java:4789)
 
    at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getCachedPlan(SessionCatalog.scala:155)
 
    at org.apache.spark.sql.execution.datasources.FindDataSourceTable.org$apache$spark$sql$execution$datasources$FindDataSourceTable$$readDataSourceTable(DataSourceStrategy.scala:249)
 
    at org.apache.spark.sql.execution.datasources.FindDataSourceTable$$anonfun$apply$2.applyOrElse(DataSourceStrategy.scala:288)
 
    at org.apache.spark.sql.execution.datasources.FindDataSourceTable$$anonfun$apply$2.applyOrElse(DataSourceStrategy.scala:278)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$2(AnalysisHelper.scala:108)
 
    at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:74)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$1(AnalysisHelper.scala:108)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:221)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown(AnalysisHelper.scala:106)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown$(AnalysisHelper.scala:104)
 
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$4(AnalysisHelper.scala:113)
 
    at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:408)
 
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:244)
 
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:406)
 
    at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:359)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsDown$1(AnalysisHelper.scala:113)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.allowInvokingTransformsInAnalyzer(AnalysisHelper.scala:221)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown(AnalysisHelper.scala:106)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperatorsDown$(AnalysisHelper.scala:104)
 
    at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperatorsDown(LogicalPlan.scala:29)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperators(AnalysisHelper.scala:73)
 
    at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.resolveOperators$(AnalysisHelper.scala:72)
 
    at 

[User16764241763]

Based on your error you have enabled Secure transfer enabled on the storage account.

You can disable the below setting and try again with WASB/HTTP

https://docs.microsoft.com/en-us/azure/storage/common/storage-require-secure-transfer

[vivek_sinha]

Hi @Arvind Ravish​  Thanks for the response but the given config is already disabled.

And I am able to query data from Presto but using Pysaprk I am getting this error.

[vivek_sinha · Accepted solution]

Hi @Arvind Ravish​ 

The issue got fixed after passing HTTP and HTTPS enabled token to spark executors.

Thanks again for your help