Parquet modular encryption in Hive - Amazon EMR
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Parquet modular encryption in Hive

Parquet modular encryption provides columnar level access control and encryption to enhance privacy and data integrity for data stored in Parquet file format. This feature is available in Amazon EMR Hive starting with release 6.6.0.

Previously supported solutions for security and integrity, which include encrypting files or encrypting the storage layer, are described in Encryption Options in the Amazon EMR Management Guide. These solutions can be used for Parquet files, but leveraging the new features of the integrated Parquet encryption mechanism provides granular access to the column level, as well as improvements in performance and security. Learn more about this feature on the Apache github page Parquet Modular Encryption.

Users pass configurations to Parquet readers and writers using Hadoop configurations. The detailed configurations for users to configure readers and writers to enable encryption as well as toggle advanced features are documented at PARQUET-1854: Properties-driven Interface to Parquet Encryption Management

Usage examples

The following example covers creating and writing to a Hive table using Amazon KMS for managing encryption keys.

  1. Implement a KmsClient for the Amazon KMS service as described in the document PARQUET-1373: Encryption Key Management Tools. The following sample shows an implementation snippet.

    package org.apache.parquet.crypto.keytools; import com.amazonaws.AmazonClientException; import com.amazonaws.AmazonServiceException; import com.amazonaws.regions.Regions; import; import; import; import; import com.amazonaws.util.Base64; import org.apache.hadoop.conf.Configuration; import org.apache.parquet.crypto.KeyAccessDeniedException; import org.apache.parquet.crypto.ParquetCryptoRuntimeException; import org.apache.parquet.crypto.keytools.KmsClient; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import java.nio.ByteBuffer; import java.nio.charset.Charset; import java.nio.charset.StandardCharsets; public class AwsKmsClient implements KmsClient { private static final AWSKMS AWSKMS_CLIENT = AWSKMSClientBuilder .standard() .withRegion(Regions.US_WEST_2) .build(); public static final Logger LOG = LoggerFactory.getLogger(AwsKmsClient.class); private String kmsToken; private Configuration hadoopConfiguration; @Override public void initialize(Configuration configuration, String kmsInstanceID, String kmsInstanceURL, String accessToken) throws KeyAccessDeniedException { hadoopConfiguration = configuration; kmsToken = accessToken; } @Override public String wrapKey(byte[] keyBytes, String masterKeyIdentifier) throws KeyAccessDeniedException { String value = null; try { ByteBuffer plaintext = ByteBuffer.wrap(keyBytes); EncryptRequest req = new EncryptRequest().withKeyId(masterKeyIdentifier).withPlaintext(plaintext); ByteBuffer ciphertext = AWSKMS_CLIENT.encrypt(req).getCiphertextBlob(); byte[] base64EncodedValue = Base64.encode(ciphertext.array()); value = new String(base64EncodedValue, Charset.forName("UTF-8")); } catch (AmazonClientException ae) { throw new KeyAccessDeniedException(ae.getMessage()); } return value; } @Override public byte[] unwrapKey(String wrappedKey, String masterKeyIdentifier) throws KeyAccessDeniedException { byte[] arr = null; try { ByteBuffer ciphertext = ByteBuffer.wrap(Base64.decode(wrappedKey.getBytes(StandardCharsets.UTF_8))); DecryptRequest request = new DecryptRequest().withKeyId(masterKeyIdentifier).withCiphertextBlob(ciphertext); ByteBuffer decipheredtext = AWSKMS_CLIENT.decrypt(request).getPlaintext(); arr = new byte[decipheredtext.remaining()]; decipheredtext.get(arr); } catch (AmazonClientException ae) { throw new KeyAccessDeniedException(ae.getMessage()); } return arr; } }
  2. Create your Amazon KMS encryption keys for the footer as well the columns with your IAM roles having access as described in Creating keys in the Amazon Key Management Service Developer Guide. The default IAM role is EMR_ECS_default.

  3. On the Hive application on an Amazon EMR cluster, add the client above using the ADD JAR statement, as described in the Apache Hive Resources documentation. The following is an example statement:

    ADD JAR 's3://location-to-custom-jar';

    An alternative method is to add the JAR to the auxlib of Hive using a bootstrap action. The following is an example line to be added to the boostrap action:

    aws s3 cp 's3://location-to-custom-jar' /usr/lib/hive/auxlib
  4. Set the following configurations:

    set parquet.crypto.factory.class=org.apache.parquet.crypto.keytools.PropertiesDrivenCryptoFactory; set parquet.encryption.kms.client.class=org.apache.parquet.crypto.keytools.AwsKmsClient;
  5. Create a Hive table with Parquet format and specify the Amazon KMS keys in SERDEPROPERTIES and insert some data to it:

    CREATE TABLE my_table(name STRING, credit_card STRING) ROW FORMAT SERDE '’ WITH SERDEPROPERTIES ( 'parquet.encryption.column.key’=<aws-kms-key-id-for-column-1>: credit_card’, 'parquet.encryption.footer.key’='<aws-kms-key-id-for-footer>’) STORED AS parquet LOCATION “s3://<bucket/<warehouse-location>/my_table”; INSERT INTO my_table SELECT java_method ('org.apache.commons.lang.RandomStringUtils','randomAlphabetic',5) as name, java_method ('org.apache.commons.lang.RandomStringUtils','randomAlphabetic',10) as credit_card from (select 1) x lateral view posexplode(split(space(100),' ')) pe as i,x; select * from my_table;
  6. Verify that when you create an external table at the same location with no access to Amazon KMS keys (for example, IAM role access denied), you cannot read the data.

    CREATE EXTERNAL TABLE ext_table (name STRING, credit_card STRING) ROW FORMAT SERDE '’ STORED AS parquet LOCATION “s3://<bucket>/<warehouse-location>/my_table”; SELECT * FROM ext_table;
  7. The last statement should throw the following exception:

    Failed with exception Footer key: access denied