[SPARK-39308][BUILD][SQL] Upgrade parquet to 1.12.3

dev/deps/spark-deps-hadoop-2-hive-2.3

@@ -225,12 +225,12 @@ orc-shims/1.7.4//orc-shims-1.7.4.jar
 oro/2.0.8//oro-2.0.8.jar
 osgi-resource-locator/1.0.3//osgi-resource-locator-1.0.3.jar
 paranamer/2.8//paranamer-2.8.jar
-parquet-column/1.12.2//parquet-column-1.12.2.jar
-parquet-common/1.12.2//parquet-common-1.12.2.jar
-parquet-encoding/1.12.2//parquet-encoding-1.12.2.jar
-parquet-format-structures/1.12.2//parquet-format-structures-1.12.2.jar
-parquet-hadoop/1.12.2//parquet-hadoop-1.12.2.jar
-parquet-jackson/1.12.2//parquet-jackson-1.12.2.jar
+parquet-column/1.12.3//parquet-column-1.12.3.jar
+parquet-common/1.12.3//parquet-common-1.12.3.jar
+parquet-encoding/1.12.3//parquet-encoding-1.12.3.jar
+parquet-format-structures/1.12.3//parquet-format-structures-1.12.3.jar
+parquet-hadoop/1.12.3//parquet-hadoop-1.12.3.jar
+parquet-jackson/1.12.3//parquet-jackson-1.12.3.jar
 pickle/1.2//pickle-1.2.jar
 protobuf-java/2.5.0//protobuf-java-2.5.0.jar
 py4j/0.10.9.5//py4j-0.10.9.5.jar

dev/deps/spark-deps-hadoop-3-hive-2.3

@@ -214,12 +214,12 @@ orc-shims/1.7.4//orc-shims-1.7.4.jar
 oro/2.0.8//oro-2.0.8.jar
 osgi-resource-locator/1.0.3//osgi-resource-locator-1.0.3.jar
 paranamer/2.8//paranamer-2.8.jar
-parquet-column/1.12.2//parquet-column-1.12.2.jar
-parquet-common/1.12.2//parquet-common-1.12.2.jar
-parquet-encoding/1.12.2//parquet-encoding-1.12.2.jar
-parquet-format-structures/1.12.2//parquet-format-structures-1.12.2.jar
-parquet-hadoop/1.12.2//parquet-hadoop-1.12.2.jar
-parquet-jackson/1.12.2//parquet-jackson-1.12.2.jar
+parquet-column/1.12.3//parquet-column-1.12.3.jar
+parquet-common/1.12.3//parquet-common-1.12.3.jar
+parquet-encoding/1.12.3//parquet-encoding-1.12.3.jar
+parquet-format-structures/1.12.3//parquet-format-structures-1.12.3.jar
+parquet-hadoop/1.12.3//parquet-hadoop-1.12.3.jar
+parquet-jackson/1.12.3//parquet-jackson-1.12.3.jar
 pickle/1.2//pickle-1.2.jar
 protobuf-java/2.5.0//protobuf-java-2.5.0.jar
 py4j/0.10.9.5//py4j-0.10.9.5.jar

docs/sql-data-sources-parquet.md

@@ -257,7 +257,7 @@ REFRESH TABLE my_table;
 
 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. The 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):
+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. The Parquet Maven [repository](https://repo1.maven.org/maven2/org/apache/parquet/parquet-hadoop/1.12.3/) 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 class="codetabs">
 
@@ -349,7 +349,7 @@ df2 = spark.read.parquet("/path/to/table.parquet.encrypted")
 
 #### 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,
+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/1.12.3/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 %}

pom.xml

@@ -131,7 +131,7 @@
     <kafka.version>3.2.0</kafka.version>
     <!-- After 10.15.1.3, the minimum required version is JDK9 -->
     <derby.version>10.14.2.0</derby.version>
-    <parquet.version>1.12.2</parquet.version>
+    <parquet.version>1.12.3</parquet.version>
     <orc.version>1.7.4</orc.version>
     <jetty.version>9.4.46.v20220331</jetty.version>
     <jakartaservlet.version>4.0.3</jakartaservlet.version>
@@ -2357,7 +2357,7 @@
             <groupId>${hive.group}</groupId>
             <artifactId>hive-service-rpc</artifactId>
           </exclusion>
-          <!-- parquet-hadoop-bundle:1.8.1 conflict with 1.12.0 -->
+          <!-- parquet-hadoop-bundle:1.8.1 conflict with 1.12.3 -->
           <exclusion>
             <groupId>org.apache.parquet</groupId>
             <artifactId>parquet-hadoop-bundle</artifactId>

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala

@@ -28,7 +28,7 @@ import scala.reflect.runtime.universe.TypeTag
 import org.apache.hadoop.fs.Path
 import org.apache.parquet.filter2.predicate.{FilterApi, FilterPredicate, Operators}
 import org.apache.parquet.filter2.predicate.FilterApi._
-import org.apache.parquet.filter2.predicate.Operators.{Column => _, _}
+import org.apache.parquet.filter2.predicate.Operators.{Column => _, Eq, Gt, GtEq, Lt, LtEq, NotEq, UserDefinedByInstance}
 import org.apache.parquet.hadoop.{ParquetFileReader, ParquetInputFormat, ParquetOutputFormat}
 import org.apache.parquet.hadoop.util.HadoopInputFile
 import org.apache.parquet.schema.MessageType