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https://issues.apache.org/jira/browse/SPARK-22634?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16269308#comment-16269308
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Lior Regev commented on SPARK-22634:
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Well, mainly there are 2 issues:
# The included package in the spark installation, when one downloads spark from 
the official website, one gets BC 1.51, which could be easily changed to 1.58 
since it should be completely backwards compatible.
# When searching for bouncycastle in the spark repository, one gets result for 
dependencies in the streaming package of kafka and flume. These should be 
updated merely to avoid collisions.

Like I stated, I opened an issue with jets3t, but the BC dependency there is in 
compile scope so (as far as I understand) it is not included in the JAR. 
Therefore, Spark could simply provide an updated version.

> Update Bouncy castle dependency
> -------------------------------
>
>                 Key: SPARK-22634
>                 URL: https://issues.apache.org/jira/browse/SPARK-22634
>             Project: Spark
>          Issue Type: Task
>          Components: Spark Core, SQL, Structured Streaming
>    Affects Versions: 2.2.0
>            Reporter: Lior Regev
>            Priority: Minor
>
> Spark's usage of jets3t library as well as Spark's own Flume and Kafka 
> streaming uses bouncy castle version 1.51
> This is an outdated version as the latest one is 1.58
> This, in turn renders packages such as 
> [spark-hadoopcryptoledger-ds|https://github.com/ZuInnoTe/spark-hadoopcryptoledger-ds]
>  unusable since these require 1.58 and spark's distributions come along with 
> 1.51
> My own attempt was to run on EMR, and since I automatically get all of 
> spark's dependecies (bouncy castle 1.51 being one of them) into the 
> classpath, using the library to parse blockchain data failed due to missing 
> functionality.
> I have also opened an 
> [issue|https://bitbucket.org/jmurty/jets3t/issues/242/bouncycastle-dependency]
>  with jets3t to update their dependecy as well, but along with that Spark 
> would have to update it's own or at least be packaged with a newer version



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