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188 changes: 188 additions & 0 deletions
188
.../spark/sql/execution/datasources/parquet/Spark312HoodieVectorizedParquetRecordReader.java
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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.parquet; | ||
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| import org.apache.hadoop.mapreduce.InputSplit; | ||
| import org.apache.hadoop.mapreduce.TaskAttemptContext; | ||
| import org.apache.hudi.client.utils.SparkSchemaUtils; | ||
| import org.apache.hudi.common.util.collection.Pair; | ||
| import org.apache.spark.memory.MemoryMode; | ||
| import org.apache.spark.sql.catalyst.InternalRow; | ||
| import org.apache.spark.sql.execution.vectorized.OffHeapColumnVector; | ||
| import org.apache.spark.sql.execution.vectorized.OnHeapColumnVector; | ||
| import org.apache.spark.sql.execution.vectorized.WritableColumnVector; | ||
| import org.apache.spark.sql.types.DataType; | ||
| import org.apache.spark.sql.types.StructType; | ||
| import org.apache.spark.sql.vectorized.ColumnarBatch; | ||
|
|
||
| import java.io.IOException; | ||
| import java.time.ZoneId; | ||
| import java.util.HashMap; | ||
| import java.util.Map; | ||
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| public class Spark312HoodieVectorizedParquetRecordReader extends VectorizedParquetRecordReader { | ||
|
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| // save the col type change info. | ||
| private Map<Integer, Pair<DataType, DataType>> typeChangeInfos; | ||
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| private ColumnarBatch columnarBatch; | ||
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| private Map<Integer, WritableColumnVector> idToColumnVectors; | ||
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| private WritableColumnVector[] columnVectors; | ||
|
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| // The capacity of vectorized batch. | ||
| private int capacity; | ||
|
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| // If true, this class returns batches instead of rows. | ||
| private boolean returnColumnarBatch; | ||
|
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| // The memory mode of the columnarBatch. | ||
| private final MemoryMode memoryMode; | ||
|
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| /** | ||
| * Batch of rows that we assemble and the current index we've returned. Every time this | ||
| * batch is used up (batchIdx == numBatched), we populated the batch. | ||
| */ | ||
| private int batchIdx = 0; | ||
| private int numBatched = 0; | ||
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| public Spark312HoodieVectorizedParquetRecordReader( | ||
| ZoneId convertTz, | ||
| String datetimeRebaseMode, | ||
| String int96RebaseMode, | ||
| boolean useOffHeap, | ||
| int capacity, | ||
| Map<Integer, Pair<DataType, DataType>> typeChangeInfos) { | ||
| super(convertTz, datetimeRebaseMode, int96RebaseMode, useOffHeap, capacity); | ||
| memoryMode = useOffHeap ? MemoryMode.OFF_HEAP : MemoryMode.ON_HEAP; | ||
| this.typeChangeInfos = typeChangeInfos; | ||
| this.capacity = capacity; | ||
| } | ||
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| @Override | ||
| public void initBatch(StructType partitionColumns, InternalRow partitionValues) { | ||
| super.initBatch(partitionColumns, partitionValues); | ||
| if (columnVectors == null) { | ||
| columnVectors = new WritableColumnVector[sparkSchema.length() + partitionColumns.length()]; | ||
| } | ||
| if (idToColumnVectors == null) { | ||
| idToColumnVectors = new HashMap<>(); | ||
| typeChangeInfos.entrySet() | ||
| .stream() | ||
| .forEach(f -> { | ||
| WritableColumnVector vector = | ||
| memoryMode == MemoryMode.OFF_HEAP ? new OffHeapColumnVector(capacity, f.getValue().getLeft()) : new OnHeapColumnVector(capacity, f.getValue().getLeft()); | ||
| idToColumnVectors.put(f.getKey(), vector); | ||
| }); | ||
| } | ||
| } | ||
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| @Override | ||
| public void initialize(InputSplit inputSplit, TaskAttemptContext taskAttemptContext) throws IOException, InterruptedException, UnsupportedOperationException { | ||
| super.initialize(inputSplit, taskAttemptContext); | ||
| } | ||
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| @Override | ||
| public void close() throws IOException { | ||
| super.close(); | ||
| for (Map.Entry<Integer, WritableColumnVector> e : idToColumnVectors.entrySet()) { | ||
| e.getValue().close(); | ||
| } | ||
| idToColumnVectors = null; | ||
| columnarBatch = null; | ||
| columnVectors = null; | ||
| } | ||
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| @Override | ||
| public ColumnarBatch resultBatch() { | ||
| ColumnarBatch currentColumnBatch = super.resultBatch(); | ||
| boolean changed = false; | ||
| for (Map.Entry<Integer, Pair<DataType, DataType>> entry : typeChangeInfos.entrySet()) { | ||
| boolean rewrite = SparkSchemaUtils | ||
| .convertColumnVectorType((WritableColumnVector) currentColumnBatch.column(entry.getKey()), | ||
| idToColumnVectors.get(entry.getKey()), currentColumnBatch.numRows()); | ||
| if (rewrite) { | ||
| changed = true; | ||
| columnVectors[entry.getKey()] = idToColumnVectors.get(entry.getKey()); | ||
| } | ||
| } | ||
| if (changed) { | ||
| if (columnarBatch == null) { | ||
| // fill other vector | ||
| for (int i = 0; i < columnVectors.length; i++) { | ||
| if (columnVectors[i] == null) { | ||
| columnVectors[i] = (WritableColumnVector) currentColumnBatch.column(i); | ||
| } | ||
| } | ||
| columnarBatch = new ColumnarBatch(columnVectors); | ||
| } | ||
| columnarBatch.setNumRows(currentColumnBatch.numRows()); | ||
| return columnarBatch; | ||
| } else { | ||
| return currentColumnBatch; | ||
| } | ||
| } | ||
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| @Override | ||
| public boolean nextBatch() throws IOException { | ||
| boolean result = super.nextBatch(); | ||
| if (idToColumnVectors != null) { | ||
| idToColumnVectors.entrySet().stream().forEach(e -> e.getValue().reset()); | ||
| } | ||
| numBatched = resultBatch().numRows(); | ||
| batchIdx = 0; | ||
| return result; | ||
| } | ||
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| @Override | ||
| public void enableReturningBatches() { | ||
| returnColumnarBatch = true; | ||
| super.enableReturningBatches(); | ||
| } | ||
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| @Override | ||
| public Object getCurrentValue() { | ||
| if (typeChangeInfos == null || typeChangeInfos.isEmpty()) { | ||
| return super.getCurrentValue(); | ||
| } | ||
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| if (returnColumnarBatch) { | ||
| return columnarBatch == null ? super.getCurrentValue() : columnarBatch; | ||
| } | ||
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| return columnarBatch == null ? super.getCurrentValue() : columnarBatch.getRow(batchIdx - 1); | ||
| } | ||
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| @Override | ||
| public boolean nextKeyValue() throws IOException { | ||
| resultBatch(); | ||
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| if (returnColumnarBatch) { | ||
| return nextBatch(); | ||
| } | ||
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| if (batchIdx >= numBatched) { | ||
| if (!nextBatch()) { | ||
| return false; | ||
| } | ||
| } | ||
| ++batchIdx; | ||
| return true; | ||
| } | ||
| } |
66 changes: 66 additions & 0 deletions
66
...di-spark3.1.x/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/HStatments.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
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| package org.apache.spark.sql.catalyst.plans.logical | ||
|
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| import org.apache.spark.sql.connector.catalog.TableChange.ColumnPosition | ||
| import org.apache.spark.sql.types.DataType | ||
|
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| /** | ||
| * ALTER TABLE ... ADD COLUMNS command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableAddColumnsStatement( | ||
| tableName: Seq[String], | ||
| columnsToAdd: Seq[QualifiedColType]) extends ParsedStatement | ||
|
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| /** | ||
| * ALTER TABLE ... CHANGE COLUMN command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableAlterColumnStatement( | ||
| tableName: Seq[String], | ||
| column: Seq[String], | ||
| dataType: Option[DataType], | ||
| nullable: Option[Boolean], | ||
| comment: Option[String], | ||
| position: Option[ColumnPosition]) extends ParsedStatement | ||
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| /** | ||
| * ALTER TABLE ... RENAME COLUMN command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableRenameColumnStatement( | ||
| tableName: Seq[String], | ||
| column: Seq[String], | ||
| newName: String) extends ParsedStatement | ||
|
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| /** | ||
| * ALTER TABLE ... DROP COLUMNS command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableDropColumnsStatement( | ||
| tableName: Seq[String], columnsToDrop: Seq[Seq[String]]) extends ParsedStatement | ||
|
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| /** | ||
| * ALTER TABLE ... SET TBLPROPERTIES command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableSetPropertiesStatement( | ||
| tableName: Seq[String], properties: Map[String, String]) extends ParsedStatement | ||
|
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| /** | ||
| * ALTER TABLE ... UNSET TBLPROPERTIES command, as parsed from SQL. | ||
| */ | ||
| case class HoodieAlterTableUnsetPropertiesStatement( | ||
| tableName: Seq[String], propertyKeys: Seq[String], ifExists: Boolean) extends ParsedStatement |
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