WangGuangxin commented on a change in pull request #24043: [SPARK-11412][SQL] 
Support merge schema for ORC
URL: https://github.com/apache/spark/pull/24043#discussion_r293008942
 
 

 ##########
 File path: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SchemaMergeUtils.scala
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.execution.datasources
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileStatus, Path}
+
+import org.apache.spark.SparkException
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.SparkSession
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.util.SerializableConfiguration
+
+object SchemaMergeUtils extends Logging {
+  /**
+   * Figures out a merged Parquet/ORC schema with a distributed Spark job.
+   */
+  def mergeSchemasInParallel(
+    sparkSession: SparkSession,
+    files: Seq[FileStatus],
+    parallelSchemaReader: (Seq[FileStatus], Configuration, Boolean) => 
Seq[StructType])
+    : Option[StructType] = {
+    val serializedConf = new 
SerializableConfiguration(sparkSession.sessionState.newHadoopConf())
+
+    // !! HACK ALERT !!
+    //
+    // Parquet requires `FileStatus`es to read footers.  Here we try to send 
cached `FileStatus`es
+    // to executor side to avoid fetching them again.  However, `FileStatus` 
is not `Serializable`
+    // but only `Writable`.  What makes it worse, for some reason, 
`FileStatus` doesn't play well
+    // with `SerializableWritable[T]` and always causes a weird 
`IllegalStateException`.  These
+    // facts virtually prevents us to serialize `FileStatus`es.
+    //
+    // Since Parquet only relies on path and length information of those 
`FileStatus`es to read
+    // footers, here we just extract them (which can be easily serialized), 
send them to executor
+    // side, and resemble fake `FileStatus`es there.
+    val partialFileStatusInfo = files.map(f => (f.getPath.toString, f.getLen))
+
+    // Set the number of partitions to prevent following schema reads from 
generating many tasks
+    // in case of a small number of orc files.
+    val numParallelism = Math.min(Math.max(partialFileStatusInfo.size, 1),
+      sparkSession.sparkContext.defaultParallelism)
+
+    val ignoreCorruptFiles = sparkSession.sessionState.conf.ignoreCorruptFiles
+
+    // Issues a Spark job to read Parquet/ORC schema in parallel.
+    val partiallyMergedSchemas =
+      sparkSession
+        .sparkContext
+        .parallelize(partialFileStatusInfo, numParallelism)
+        .mapPartitions { iterator =>
+          // Resembles fake `FileStatus`es with serialized path and length 
information.
+          val fakeFileStatuses = iterator.map { case (path, length) =>
+            new FileStatus(length, false, 0, 0, 0, 0, null, null, null, new 
Path(path))
+          }.toSeq
+
+          // Reads schemas in multi-threaded manner within each task
 
 Review comment:
   Thanks for your comments. Good points. I'v updated there.

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