ggershinsky commented on a change in pull request #32895:
URL: https://github.com/apache/spark/pull/32895#discussion_r669693709



##########
File path: docs/sql-data-sources-parquet.md
##########
@@ -252,6 +252,71 @@ REFRESH TABLE my_table;
 
 </div>
 
+## Columnar Encryption
+
+
+Since Spark 3.2, columnar encryption is supported for Parquet tables with 
Apache Parquet 1.12+.
+
+Parquet uses the envelope encryption practice, where file parts are encrypted 
with "data encryption keys" (DEKs), and the DEKs are encrypted with "master 
encryption keys" (MEKs). The DEKs are randomly generated by Parquet for each 
encrypted file/column. The MEKs are generated, stored and managed in a Key 
Management Service (KMS) of user’s choice. Parquet maven [repository]( 
https://repo1.maven.org/maven2/org/apache/parquet/parquet-hadoop/1.12.0/) has a 
jar with a mock KMS implementation that allows to run column encryption and 
decryption using a spark-shell only, without deploying a KMS server (download 
the `parquet-hadoop-tests.jar` file and place it in the Spark `jars` folder):
+
+<div data-lang="scala"  markdown="1">
+{% highlight scala %}
+
+sc.hadoopConfiguration.set("parquet.encryption.kms.client.class" ,
+                           
"org.apache.parquet.crypto.keytools.mocks.InMemoryKMS")
+
+// Explicit master keys (base64 encoded) - required only for mock InMemoryKMS
+sc.hadoopConfiguration.set("parquet.encryption.key.list" ,
+                   "keyA:AAECAwQFBgcICQoLDA0ODw== ,  
keyB:AAECAAECAAECAAECAAECAA==")
+
+// Activate Parquet encryption, driven by Hadoop properties
+sc.hadoopConfiguration.set("parquet.crypto.factory.class" ,
+                   
"org.apache.parquet.crypto.keytools.PropertiesDrivenCryptoFactory")
+
+// Write encrypted dataframe files. 
+// Column "square" will be protected with master key "keyA".
+// Parquet file footers will be protected with master key "keyB"
+squaresDF.write.
+   option("parquet.encryption.column.keys" , "keyA:square").
+   option("parquet.encryption.footer.key" , "keyB").
+parquet("/path/to/table.parquet.encrypted")
+
+// Read encrypted dataframe files
+val df2 = spark.read.parquet("/path/to/table.parquet.encrypted")
+
+{% endhighlight %}
+
+</div>
+
+
+#### KMS Client
+
+The InMemoryKMS class is provided only for illustration and simple 
demonstration of Parquet encryption functionality. **It should not be used in a 
real deployment**. The master encryption keys must be kept and managed in a 
production-grade KMS system, deployed in user's organization. Rollout of Spark 
with Parquet encryption requires implementation of a client class for the KMS 
server. Parquet provides a plug-in 
[interface](https://github.com/apache/parquet-mr/blob/apache-parquet-1.12.0/parquet-hadoop/src/main/java/org/apache/parquet/crypto/keytools/KmsClient.java)
 for development of such classes,
+
+<div data-lang="java"  markdown="1">
+{% highlight java %}
+
+public interface KmsClient {
+  // Wraps a key - encrypts it with the master key.
+  public String wrapKey(byte[] keyBytes, String masterKeyIdentifier);
+
+  // Decrypts (unwraps) a key with the master key. 
+  public byte[] unwrapKey(String wrappedKey, String masterKeyIdentifier);
+
+  // Use of initialization parameters is optional.
+  public void initialize(Configuration configuration, String kmsInstanceID, 
+                         String kmsInstanceURL, String accessToken);
+}
+
+{% endhighlight %}
+
+</div>
+
+An 
[example](https://github.com/apache/parquet-mr/blob/apache-parquet-1.12.0/parquet-hadoop/src/test/java/org/apache/parquet/crypto/keytools/samples/VaultClient.java)
 of such class for an open source 
[KMS](https://www.vaultproject.io/api/secret/transit) can be found in the 
parquet-mr repository. The production KMS client should be designed in 
cooperation with organization's security administrators, and built by 
developers with an experience in access control management. Once such class is 
created, it can be passed to applications via the 
`parquet.encryption.kms.client.class` parameter and leveraged by general Spark 
users as shown in the encrypted dataframe write/read sample above.

Review comment:
       Looks like I've misunderstood. I thought you refer to these hyperlinks :
   
   - 
https://github.com/apache/parquet-mr/blob/apache-parquet-1.12.0/parquet-hadoop/src/test/java/org/apache/parquet/crypto/keytools/samples/VaultClient.java
   For the latest version, this can be replaced with a link to the master 
branch:
   
https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/src/test/java/org/apache/parquet/crypto/keytools/samples/VaultClient.java
   
   - https://www.vaultproject.io/api/secret/transit
   I think this is their latest version
   
   As for adding this information in  
https://parquet.apache.org/documentation/latest/ - there are a number of 
problems with it: this page doesn't keep this kind of technical details, on 
encryption or other Parquet features; this page is a few years old and doesn't 
mention the recent Parquet features; I don't have edit rights to it - updating 
this page (if possible at all) will be a long project in the community, without 
a chance to be on time for Spark 3.2.0 release.
   
   This is about hyperlinks to a sample KMS client/server. Another option would 
be simply to remove the URLs, and leave only the names (Hashicorp Vault; 
Parquet VaultClient); this should be enough for developers to find them.




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