[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-09-08 Thread dongjoon-hyun 
Github user dongjoon-hyun closed the pull request at:

https://github.com/apache/spark/pull/17924


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread viirya 
Github user viirya commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115650693
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala ---
@@ -0,0 +1,415 @@
+/*
+ * 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.hive.orc
+
+import java.io.File
+
+import scala.util.Try
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.io.IntWritable
+import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType}
+import org.apache.hadoop.mapreduce.lib.input.FileSplit
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+import org.apache.orc.OrcFile
+import org.apache.orc.mapred.OrcStruct
+import org.apache.orc.mapreduce.OrcInputFormat
+import org.apache.orc.storage.ql.exec.vector.{BytesColumnVector, 
LongColumnVector}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.SparkSession
+import 
org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase
+import org.apache.spark.unsafe.types.UTF8String
+import org.apache.spark.util.{Benchmark, Utils}
+
+
+/**
+ * Benchmark to measure orc read performance.
+ *
+ * This is in `sql/hive` module in order to compare `sql/core` and 
`sql/hive` ORC data sources.
+ * After removing `sql/hive` ORC data sources, we need to move this into 
`sql/core` module
+ * like the other ORC test suites.
+ */
+object OrcReadBenchmark {
+  val conf = new SparkConf()
+  conf.set("orc.compression", "snappy")
+
+  private val spark = SparkSession.builder()
+.master("local[1]")
+.appName("OrcReadBenchmark")
+.config(conf)
+.getOrCreate()
+
+  // Set default configs. Individual cases will change them if necessary.
+  spark.conf.set(SQLConf.ORC_VECTORIZED_READER_ENABLED.key, "true")
+  spark.conf.set(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key, "true")
+  spark.conf.set(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key, "true")
+
+  def withTempPath(f: File => Unit): Unit = {
+val path = Utils.createTempDir()
+path.delete()
+try f(path) finally Utils.deleteRecursively(path)
+  }
+
+  def withTempTable(tableNames: String*)(f: => Unit): Unit = {
+try f finally tableNames.foreach(spark.catalog.dropTempView)
+  }
+
+  def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = {
+val (keys, values) = pairs.unzip
+val currentValues = keys.map(key => Try(spark.conf.get(key)).toOption)
+(keys, values).zipped.foreach(spark.conf.set)
+try f finally {
+  keys.zip(currentValues).foreach {
+case (key, Some(value)) => spark.conf.set(key, value)
+case (key, None) => spark.conf.unset(key)
+  }
+}
+  }
+
+  private val SQL_ORC_FILE_FORMAT = 
"org.apache.spark.sql.execution.datasources.orc.OrcFileFormat"
+  private val HIVE_ORC_FILE_FORMAT = 
"org.apache.spark.sql.hive.orc.OrcFileFormat"
--- End diff --

So to avoid datasource name conflict, we may change Hive ORC datasource's 
shortName to other than "orc".


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread dongjoon-hyun 
Github user dongjoon-hyun commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115650375
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala ---
@@ -0,0 +1,415 @@
+/*
+ * 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.hive.orc
+
+import java.io.File
+
+import scala.util.Try
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.io.IntWritable
+import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType}
+import org.apache.hadoop.mapreduce.lib.input.FileSplit
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+import org.apache.orc.OrcFile
+import org.apache.orc.mapred.OrcStruct
+import org.apache.orc.mapreduce.OrcInputFormat
+import org.apache.orc.storage.ql.exec.vector.{BytesColumnVector, 
LongColumnVector}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.SparkSession
+import 
org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase
+import org.apache.spark.unsafe.types.UTF8String
+import org.apache.spark.util.{Benchmark, Utils}
+
+
+/**
+ * Benchmark to measure orc read performance.
+ *
+ * This is in `sql/hive` module in order to compare `sql/core` and 
`sql/hive` ORC data sources.
+ * After removing `sql/hive` ORC data sources, we need to move this into 
`sql/core` module
+ * like the other ORC test suites.
+ */
+object OrcReadBenchmark {
+  val conf = new SparkConf()
+  conf.set("orc.compression", "snappy")
+
+  private val spark = SparkSession.builder()
+.master("local[1]")
+.appName("OrcReadBenchmark")
+.config(conf)
+.getOrCreate()
+
+  // Set default configs. Individual cases will change them if necessary.
+  spark.conf.set(SQLConf.ORC_VECTORIZED_READER_ENABLED.key, "true")
+  spark.conf.set(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key, "true")
+  spark.conf.set(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key, "true")
+
+  def withTempPath(f: File => Unit): Unit = {
+val path = Utils.createTempDir()
+path.delete()
+try f(path) finally Utils.deleteRecursively(path)
+  }
+
+  def withTempTable(tableNames: String*)(f: => Unit): Unit = {
+try f finally tableNames.foreach(spark.catalog.dropTempView)
+  }
+
+  def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = {
+val (keys, values) = pairs.unzip
+val currentValues = keys.map(key => Try(spark.conf.get(key)).toOption)
+(keys, values).zipped.foreach(spark.conf.set)
+try f finally {
+  keys.zip(currentValues).foreach {
+case (key, Some(value)) => spark.conf.set(key, value)
+case (key, None) => spark.conf.unset(key)
+  }
+}
+  }
+
+  private val SQL_ORC_FILE_FORMAT = 
"org.apache.spark.sql.execution.datasources.orc.OrcFileFormat"
+  private val HIVE_ORC_FILE_FORMAT = 
"org.apache.spark.sql.hive.orc.OrcFileFormat"
--- End diff --

We need to keep both versions before complete transition and for safety. 
Instead, we can make configurable which file format is used for `orc` data 
source string, e.g, `USING ORC`.


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread viirya 
Github user viirya commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115649175
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/hive/orc/OrcReadBenchmark.scala ---
@@ -0,0 +1,415 @@
+/*
+ * 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.hive.orc
+
+import java.io.File
+
+import scala.util.Try
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.io.IntWritable
+import org.apache.hadoop.mapreduce.{JobID, TaskAttemptID, TaskID, TaskType}
+import org.apache.hadoop.mapreduce.lib.input.FileSplit
+import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl
+import org.apache.orc.OrcFile
+import org.apache.orc.mapred.OrcStruct
+import org.apache.orc.mapreduce.OrcInputFormat
+import org.apache.orc.storage.ql.exec.vector.{BytesColumnVector, 
LongColumnVector}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.SparkSession
+import 
org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase
+import org.apache.spark.unsafe.types.UTF8String
+import org.apache.spark.util.{Benchmark, Utils}
+
+
+/**
+ * Benchmark to measure orc read performance.
+ *
+ * This is in `sql/hive` module in order to compare `sql/core` and 
`sql/hive` ORC data sources.
+ * After removing `sql/hive` ORC data sources, we need to move this into 
`sql/core` module
+ * like the other ORC test suites.
+ */
+object OrcReadBenchmark {
+  val conf = new SparkConf()
+  conf.set("orc.compression", "snappy")
+
+  private val spark = SparkSession.builder()
+.master("local[1]")
+.appName("OrcReadBenchmark")
+.config(conf)
+.getOrCreate()
+
+  // Set default configs. Individual cases will change them if necessary.
+  spark.conf.set(SQLConf.ORC_VECTORIZED_READER_ENABLED.key, "true")
+  spark.conf.set(SQLConf.ORC_FILTER_PUSHDOWN_ENABLED.key, "true")
+  spark.conf.set(SQLConf.WHOLESTAGE_CODEGEN_ENABLED.key, "true")
+
+  def withTempPath(f: File => Unit): Unit = {
+val path = Utils.createTempDir()
+path.delete()
+try f(path) finally Utils.deleteRecursively(path)
+  }
+
+  def withTempTable(tableNames: String*)(f: => Unit): Unit = {
+try f finally tableNames.foreach(spark.catalog.dropTempView)
+  }
+
+  def withSQLConf(pairs: (String, String)*)(f: => Unit): Unit = {
+val (keys, values) = pairs.unzip
+val currentValues = keys.map(key => Try(spark.conf.get(key)).toOption)
+(keys, values).zipped.foreach(spark.conf.set)
+try f finally {
+  keys.zip(currentValues).foreach {
+case (key, Some(value)) => spark.conf.set(key, value)
+case (key, None) => spark.conf.unset(key)
+  }
+}
+  }
+
+  private val SQL_ORC_FILE_FORMAT = 
"org.apache.spark.sql.execution.datasources.orc.OrcFileFormat"
+  private val HIVE_ORC_FILE_FORMAT = 
"org.apache.spark.sql.hive.orc.OrcFileFormat"
--- End diff --

Will we keep current Hive ORC datasource even this is in Spark?


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread viirya 
Github user viirya commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115646941
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
 ---
@@ -0,0 +1,407 @@
+/*
+ * 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.spark.internal.Logging
+import org.apache.spark.memory.MemoryMode
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
+import org.apache.spark.sql.execution.vectorized.{ColumnarBatch, 
ColumnVectorUtils}
+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 {
+  import OrcColumnarBatchReader._
+
+  /**
+   * ORC File Reader.
+   */
+  private var reader: Reader = _
+
+  /**
+   * ORC Data Schema.
+   */
+  private var schema: TypeDescription = _
+
+  /**
+   * Vectorized Row Batch.
+   */
+  private var batch: VectorizedRowBatch = _
+
+  /**
+   * Record reader from row batch.
+   */
+  private var rows: org.apache.orc.RecordReader = _
+
+  /**
+   * Spark Schema.
+   */
+  private var sparkSchema: StructType = _
+
+  /**
+   * Required Schema.
+   */
+  private var requiredSchema: StructType = _
+
+  /**
+   * Partition Column.
+   */
+  private var partitionColumns: StructType = _
+
+  private var useIndex: Boolean = false
+
+  /**
+   * Full Schema: requiredSchema + partition schema.
+   */
+  private var fullSchema: StructType = _
+
+  /**
+   * ColumnarBatch for vectorized execution by whole-stage codegen.
+   */
+  private var columnarBatch: ColumnarBatch = _
--- End diff --

Btw, the PR is at #13775.


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread viirya 
Github user viirya commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115646778
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
 ---
@@ -0,0 +1,407 @@
+/*
+ * 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.spark.internal.Logging
+import org.apache.spark.memory.MemoryMode
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
+import org.apache.spark.sql.execution.vectorized.{ColumnarBatch, 
ColumnVectorUtils}
+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 {
+  import OrcColumnarBatchReader._
+
+  /**
+   * ORC File Reader.
+   */
+  private var reader: Reader = _
+
+  /**
+   * ORC Data Schema.
+   */
+  private var schema: TypeDescription = _
+
+  /**
+   * Vectorized Row Batch.
+   */
+  private var batch: VectorizedRowBatch = _
+
+  /**
+   * Record reader from row batch.
+   */
+  private var rows: org.apache.orc.RecordReader = _
+
+  /**
+   * Spark Schema.
+   */
+  private var sparkSchema: StructType = _
+
+  /**
+   * Required Schema.
+   */
+  private var requiredSchema: StructType = _
+
+  /**
+   * Partition Column.
+   */
+  private var partitionColumns: StructType = _
+
+  private var useIndex: Boolean = false
+
+  /**
+   * Full Schema: requiredSchema + partition schema.
+   */
+  private var fullSchema: StructType = _
+
+  /**
+   * ColumnarBatch for vectorized execution by whole-stage codegen.
+   */
+  private var columnarBatch: ColumnarBatch = _
--- End diff --

More specially, we wrap Hive's `ColumnVector` to expose spark 
`ColumnVector` for constructing Spark `ColumnarBatch`. So we don't need to move 
data from one vector format to another vector format.



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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread dongjoon-hyun 
Github user dongjoon-hyun commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115646321
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
 ---
@@ -0,0 +1,407 @@
+/*
+ * 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.spark.internal.Logging
+import org.apache.spark.memory.MemoryMode
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
+import org.apache.spark.sql.execution.vectorized.{ColumnarBatch, 
ColumnVectorUtils}
+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 {
+  import OrcColumnarBatchReader._
+
+  /**
+   * ORC File Reader.
+   */
+  private var reader: Reader = _
+
+  /**
+   * ORC Data Schema.
+   */
+  private var schema: TypeDescription = _
+
+  /**
+   * Vectorized Row Batch.
+   */
+  private var batch: VectorizedRowBatch = _
+
+  /**
+   * Record reader from row batch.
+   */
+  private var rows: org.apache.orc.RecordReader = _
+
+  /**
+   * Spark Schema.
+   */
+  private var sparkSchema: StructType = _
+
+  /**
+   * Required Schema.
+   */
+  private var requiredSchema: StructType = _
+
+  /**
+   * Partition Column.
+   */
+  private var partitionColumns: StructType = _
+
+  private var useIndex: Boolean = false
+
+  /**
+   * Full Schema: requiredSchema + partition schema.
+   */
+  private var fullSchema: StructType = _
+
+  /**
+   * ColumnarBatch for vectorized execution by whole-stage codegen.
+   */
+  private var columnarBatch: ColumnarBatch = _
--- End diff --

Oh, thank you for the comment. It sounds efficient. I'll take a look.


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread cloud-fan 
Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/17924#discussion_r115646099
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/orc/OrcColumnarBatchReader.scala
 ---
@@ -0,0 +1,407 @@
+/*
+ * 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.spark.internal.Logging
+import org.apache.spark.memory.MemoryMode
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.parser.CatalystSqlParser
+import org.apache.spark.sql.execution.vectorized.{ColumnarBatch, 
ColumnVectorUtils}
+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 {
+  import OrcColumnarBatchReader._
+
+  /**
+   * ORC File Reader.
+   */
+  private var reader: Reader = _
+
+  /**
+   * ORC Data Schema.
+   */
+  private var schema: TypeDescription = _
+
+  /**
+   * Vectorized Row Batch.
+   */
+  private var batch: VectorizedRowBatch = _
+
+  /**
+   * Record reader from row batch.
+   */
+  private var rows: org.apache.orc.RecordReader = _
+
+  /**
+   * Spark Schema.
+   */
+  private var sparkSchema: StructType = _
+
+  /**
+   * Required Schema.
+   */
+  private var requiredSchema: StructType = _
+
+  /**
+   * Partition Column.
+   */
+  private var partitionColumns: StructType = _
+
+  private var useIndex: Boolean = false
+
+  /**
+   * Full Schema: requiredSchema + partition schema.
+   */
+  private var fullSchema: StructType = _
+
+  /**
+   * ColumnarBatch for vectorized execution by whole-stage codegen.
+   */
+  private var columnarBatch: ColumnarBatch = _
--- End diff --

IIRC, @viirya also has a PR for vectorized orc reader. In that PR, we 
simply wrap the orc column batch to expose spark column batch interfaces, 
instead of writing orc column batch to spark column batch. I think that 
approach is more efficient.


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[GitHub] spark pull request #17924: [SPARK-20682][SQL] Support a new faster ORC data ...

2017-05-09 Thread dongjoon-hyun 
GitHub user dongjoon-hyun opened a pull request:

https://github.com/apache/spark/pull/17924

[SPARK-20682][SQL] Support a new faster ORC data source based on Apache ORC

## What changes were proposed in this pull request?

Since [SPARK-2883](https://issues.apache.org/jira/browse/SPARK-2883), 
Apache Spark supports Apache ORC inside `sql/hive` module with Hive dependency. 
This issue aims to add a new and faster ORC data source inside `sql/core` and 
to replace the old ORC data source eventually. In this issue, the latest Apache 
ORC 1.4.0 (released yesterday) is used.

There are four key benefits.

- Speed: Use both Spark `ColumnarBatch` and ORC `RowBatch` together. This 
is faster than the current implementation in Spark.
- Stability: Apache ORC 1.4.0 has many fixes and we can depend on ORC 
community more.
- Usability: User can use `ORC` data sources without hive module, i.e, 
`-Phive`.
- Maintainability: Reduce the Hive dependency and can remove old legacy 
code later.


## How was this patch tested?

Pass the Jenkins tests with newly added test suites in `sql/core`.

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/dongjoon-hyun/spark SPARK-20682

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/17924.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #17924


commit 8bfd4bb4aec6dc3a5e7f41ec8d5c2a25f14ab87b
Author: Dongjoon Hyun 
Date:   2017-04-25T19:30:24Z

[SPARK-20682][SQL] Implement new ORC data source based on Apache ORC




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