You are viewing a plain text version of this content. The canonical link for it is here.
Posted to dev@parquet.apache.org by "Vignesh Nageswaran (Jira)" <ji...@apache.org> on 2022/10/04 14:44:00 UTC
[jira] [Commented] (PARQUET-2193) Encrypting only one field in nested field prevents reading of other fields in nested field without keys
[ https://issues.apache.org/jira/browse/PARQUET-2193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17612636#comment-17612636 ]
Vignesh Nageswaran commented on PARQUET-2193:
---------------------------------------------
[~gershinsky] thanks sir, it worked.
> Encrypting only one field in nested field prevents reading of other fields in nested field without keys
> -------------------------------------------------------------------------------------------------------
>
> Key: PARQUET-2193
> URL: https://issues.apache.org/jira/browse/PARQUET-2193
> Project: Parquet
> Issue Type: New Feature
> Components: parquet-mr
> Affects Versions: 1.12.0
> Reporter: Vignesh Nageswaran
> Priority: Major
>
> Hi Team,
> While exploring parquet encryption, it is found that, if a field in nested column is encrypted , and If I want to read this parquet directory from other applications which does not have encryption keys to decrypt it, I cannot read the remaining fields of the nested column without keys.
> Example
> `
> {code:java}
> case class nestedItem(ic: Int = 0, sic : Double, pc: Int = 0)
> case class SquareItem(int_column: Int, square_int_column : Double, partitionCol: Int, nestedCol :nestedItem)
> `{code}
> In the case class `SquareItem` , `nestedCol` field is nested field and I want to encrypt a field `ic` within it.
>
> I also want the footer to be non encrypted , so that I can use the encrypted parquet file by legacy applications.
>
> Encryption is successful, however, when I query the parquet file using spark 3.3.0 without having any configuration for parquet encryption set up , I cannot non encrypted fields of `nestedCol` `sic`. I was expecting that only `nestedCol` `ic` field will not be querable.
>
>
> Reproducer.
> Spark 3.3.0 Using Spark-shell
> Downloaded the file [parquet-hadoop-1.12.0-tests.jar|https://repo1.maven.org/maven2/org/apache/parquet/parquet-hadoop/1.12.0/parquet-hadoop-1.12.0-tests.jar] and added it to spark-jars folder
> Code to create encrypted data. #
>
> {code:java}
> sc.hadoopConfiguration.set("parquet.crypto.factory.class" ,"org.apache.parquet.crypto.keytools.PropertiesDrivenCryptoFactory")
> sc.hadoopConfiguration.set("parquet.encryption.kms.client.class" ,"org.apache.parquet.crypto.keytools.mocks.InMemoryKMS")
> sc.hadoopConfiguration.set("parquet.encryption.key.list","key1a: BAECAwQFBgcICQoLDA0ODw==, key2a: BAECAAECAAECAAECAAECAA==, keyz: BAECAAECAAECAAECAAECAA==")
> sc.hadoopConfiguration.set("parquet.encryption.key.material.store.internally","false")
> val encryptedParquetPath = "/tmp/par_enc_footer_non_encrypted"
> valpartitionCol = 1
> case class nestedItem(ic: Int = 0, sic : Double, pc: Int = 0)
> case class SquareItem(int_column: Int, square_int_column : Double, partitionCol: Int, nestedCol :nestedItem)
> val dataRange = (1 to 100).toList
> val squares = sc.parallelize(dataRange.map(i => new SquareItem(i, scala.math.pow(i,2), partitionCol,nestedItem(i,i))))
> squares.toDS().show()
> squares.toDS().write.partitionBy("partitionCol").mode("overwrite").option("parquet.encryption.column.keys", "key1a:square_int_column,nestedCol.ic;").option("parquet.encryption.plaintext.footer",true).option("parquet.encryption.footer.key", "keyz").parquet(encryptedParquetPath)
> {code}
> Code to read the data trying to access non encrypted nested field by opening a new spark-shell
>
> {code:java}
> val encryptedParquetPath = "/tmp/par_enc_footer_non_encrypted"
> spark.sqlContext.read.parquet(encryptedParquetPath).createOrReplaceTempView("test")
> spark.sql("select nestedCol.sic from test").show(){code}
> As you can see that nestedCol.sic is not encrypted , I was expecting the results, but
> I get the below error
>
> {code:java}
> Caused by: org.apache.parquet.crypto.ParquetCryptoRuntimeException: [square_int_column]. Null File Decryptor
> at org.apache.parquet.hadoop.metadata.EncryptedColumnChunkMetaData.decryptIfNeeded(ColumnChunkMetaData.java:602)
> at org.apache.parquet.hadoop.metadata.ColumnChunkMetaData.getEncodings(ColumnChunkMetaData.java:348)
> at org.apache.parquet.hadoop.ParquetRecordReader.checkDeltaByteArrayProblem(ParquetRecordReader.java:191)
> at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:177)
> at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat.$anonfun$buildReaderWithPartitionValues$1(ParquetFileFormat.scala:375)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:209)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:270)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:116)
> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760)
> at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364)
> at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
> at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
> at org.apache.spark.scheduler.Task.run(Task.scala:136)
> at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
> at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
> at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
> at java.base/java.lang.Thread.run(Thread.java:833){code}
--
This message was sent by Atlassian Jira
(v8.20.10#820010)