Github user cloud-fan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19943#discussion_r158756552
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
 ---
    @@ -0,0 +1,432 @@
    +/*
    + * 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.orc
    +
    +import org.apache.hadoop.mapreduce.{InputSplit, RecordReader, 
TaskAttemptContext}
    +import org.apache.hadoop.mapreduce.lib.input.FileSplit
    +import org.apache.orc._
    +import org.apache.orc.mapred.OrcInputFormat
    +import org.apache.orc.storage.ql.exec.vector._
    +import org.apache.orc.storage.serde2.io.HiveDecimalWritable
    +
    +import org.apache.spark.internal.Logging
    +import org.apache.spark.memory.MemoryMode
    +import org.apache.spark.sql.catalyst.InternalRow
    +import org.apache.spark.sql.execution.vectorized._
    +import org.apache.spark.sql.types._
    +
    +
    +/**
    + * To support vectorization in WholeStageCodeGen, this reader returns 
ColumnarBatch.
    + */
    +private[orc] class OrcColumnarBatchReader extends RecordReader[Void, 
ColumnarBatch] with Logging {
    --- End diff --
    
    I think it's fine to follow parquet and write data to Spark column vector 
now. Later we can try the wrapper approach and compare.


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