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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.hadoop.hive.ql.io.orc;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertTrue;
import java.io.File;
import java.util.List;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.common.ValidTxnList;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.metastore.api.hive_metastoreConstants;
import org.apache.hadoop.hive.ql.exec.vector.LongColumnVector;
import org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch;
import org.apache.hadoop.hive.ql.io.AcidOutputFormat;
import org.apache.hadoop.hive.ql.io.AcidUtils;
import org.apache.hadoop.hive.ql.io.IOConstants;
import org.apache.hadoop.hive.ql.io.RecordIdentifier;
import org.apache.hadoop.hive.ql.io.RecordUpdater;
import org.apache.hadoop.hive.ql.io.orc.VectorizedOrcAcidRowBatchReader.ColumnizedDeleteEventRegistry;
import org.apache.hadoop.hive.ql.io.orc.VectorizedOrcAcidRowBatchReader.SortMergedDeleteEventRegistry;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.Reporter;
import org.apache.orc.TypeDescription;
import org.junit.Before;
import org.junit.Test;
import org.mockito.Mockito;
/**
* This class tests the VectorizedOrcAcidRowBatchReader by creating an actual split and a set
* of delete delta files. The split is on an insert delta and there are multiple delete deltas
* with interleaving list of record ids that get deleted. Correctness is tested by validating
* that the correct set of record ids are returned in sorted order for valid transactions only.
*/
public class TestVectorizedOrcAcidRowBatchReader {
private static final long NUM_ROWID_PER_OTID = 15000L;
private static final long NUM_OTID = 10L;
private JobConf conf;
private FileSystem fs;
private Path root;
static class DummyRow {
LongWritable field;
RecordIdentifier ROW__ID;
DummyRow(long val) {
field = new LongWritable(val);
ROW__ID = null;
}
DummyRow(long val, long rowId, long origTxn, int bucket) {
field = new LongWritable(val);
ROW__ID = new RecordIdentifier(origTxn, bucket, rowId);
}
static String getColumnNamesProperty() {
return "field";
}
static String getColumnTypesProperty() {
return "bigint";
}
}
@Before
public void setup() throws Exception {
conf = new JobConf();
conf.set("bucket_count", "1");
conf.set(hive_metastoreConstants.TABLE_IS_TRANSACTIONAL, "true");
conf.setBoolean(HiveConf.ConfVars.HIVE_TRANSACTIONAL_TABLE_SCAN.varname, true);
conf.set(hive_metastoreConstants.TABLE_TRANSACTIONAL_PROPERTIES, "default");
conf.setInt(HiveConf.ConfVars.HIVE_TXN_OPERATIONAL_PROPERTIES.varname,
AcidUtils.AcidOperationalProperties.getDefault().toInt());
conf.set(IOConstants.SCHEMA_EVOLUTION_COLUMNS, DummyRow.getColumnNamesProperty());
conf.set(IOConstants.SCHEMA_EVOLUTION_COLUMNS_TYPES, DummyRow.getColumnTypesProperty());
conf.setBoolean(HiveConf.ConfVars.HIVE_VECTORIZATION_ENABLED.varname, true);
conf.set(HiveConf.ConfVars.HIVE_ORC_SPLIT_STRATEGY.varname, "BI");
fs = FileSystem.getLocal(conf);
Path workDir = new Path(System.getProperty("test.tmp.dir",
"target" + File.separator + "test" + File.separator + "tmp"));
root = new Path(workDir, "TestVectorizedOrcAcidRowBatch.testDump");
fs.delete(root, true);
ObjectInspector inspector;
synchronized (TestOrcFile.class) {
inspector = ObjectInspectorFactory.getReflectionObjectInspector
(DummyRow.class, ObjectInspectorFactory.ObjectInspectorOptions.JAVA);
}
int bucket = 0;
AcidOutputFormat.Options options = new AcidOutputFormat.Options(conf)
.filesystem(fs)
.bucket(bucket)
.writingBase(false)
.minimumTransactionId(1)
.maximumTransactionId(NUM_OTID)
.inspector(inspector)
.reporter(Reporter.NULL)
.recordIdColumn(1)
.finalDestination(root);
RecordUpdater updater = new OrcRecordUpdater(root, options);
// Create a single insert delta with 150,000 rows, with 15000 rowIds per original transaction id.
for (long i = 1; i <= NUM_OTID; ++i) {
for (long j = 0; j < NUM_ROWID_PER_OTID; ++j) {
long payload = (i-1) * NUM_ROWID_PER_OTID + j;
updater.insert(i, new DummyRow(payload, j, i, bucket));
}
}
updater.close(false);
// Now create three types of delete deltas- first has rowIds divisible by 2 but not by 3,
// second has rowIds divisible by 3 but not by 2, and the third has rowIds divisible by
// both 2 and 3. This should produce delete deltas that will thoroughly test the sort-merge
// logic when the delete events in the delete delta files interleave in the sort order.
// Create a delete delta that has rowIds divisible by 2 but not by 3. This will produce
// a delete delta file with 50,000 delete events.
long currTxnId = NUM_OTID + 1;
options.minimumTransactionId(currTxnId).maximumTransactionId(currTxnId);
updater = new OrcRecordUpdater(root, options);
for (long i = 1; i <= NUM_OTID; ++i) {
for (long j = 0; j < NUM_ROWID_PER_OTID; j += 1) {
if (j % 2 == 0 && j % 3 != 0) {
updater.delete(currTxnId, new DummyRow(-1, j, i, bucket));
}
}
}
updater.close(false);
// Now, create a delete delta that has rowIds divisible by 3 but not by 2. This will produce
// a delete delta file with 25,000 delete events.
currTxnId = NUM_OTID + 2;
options.minimumTransactionId(currTxnId).maximumTransactionId(currTxnId);
updater = new OrcRecordUpdater(root, options);
for (long i = 1; i <= NUM_OTID; ++i) {
for (long j = 0; j < NUM_ROWID_PER_OTID; j += 1) {
if (j % 2 != 0 && j % 3 == 0) {
updater.delete(currTxnId, new DummyRow(-1, j, i, bucket));
}
}
}
updater.close(false);
// Now, create a delete delta that has rowIds divisible by both 3 and 2. This will produce
// a delete delta file with 25,000 delete events.
currTxnId = NUM_OTID + 3;
options.minimumTransactionId(currTxnId).maximumTransactionId(currTxnId);
updater = new OrcRecordUpdater(root, options);
for (long i = 1; i <= NUM_OTID; ++i) {
for (long j = 0; j < NUM_ROWID_PER_OTID; j += 1) {
if (j % 2 == 0 && j % 3 == 0) {
updater.delete(currTxnId, new DummyRow(-1, j, i, bucket));
}
}
}
updater.close(false);
}
private List<OrcSplit> getSplits() throws Exception {
conf.setInt(HiveConf.ConfVars.HIVE_TXN_OPERATIONAL_PROPERTIES.varname,
AcidUtils.AcidOperationalProperties.getDefault().toInt());
OrcInputFormat.Context context = new OrcInputFormat.Context(conf);
OrcInputFormat.FileGenerator gen = new OrcInputFormat.FileGenerator(context, fs, root, false, null);
OrcInputFormat.AcidDirInfo adi = gen.call();
List<OrcInputFormat.SplitStrategy<?>> splitStrategies = OrcInputFormat.determineSplitStrategies(
null, context, adi.fs, adi.splitPath, adi.acidInfo, adi.baseFiles, adi.parsedDeltas,
null, null, true);
assertEquals(1, splitStrategies.size());
List<OrcSplit> splits = ((OrcInputFormat.ACIDSplitStrategy)splitStrategies.get(0)).getSplits();
assertEquals(1, splits.size());
assertEquals("file://" + root.toUri().toString() + File.separator + "delta_0000001_0000010_0000/bucket_00000",
splits.get(0).getPath().toUri().toString());
assertFalse(splits.get(0).isOriginal());
return splits;
}
@Test
public void testVectorizedOrcAcidRowBatchReader() throws Exception {
testVectorizedOrcAcidRowBatchReader(ColumnizedDeleteEventRegistry.class.getName());
// To test the SortMergedDeleteEventRegistry, we need to explicitly set the
// HIVE_TRANSACTIONAL_NUM_EVENTS_IN_MEMORY constant to a smaller value.
int oldValue = conf.getInt(HiveConf.ConfVars.HIVE_TRANSACTIONAL_NUM_EVENTS_IN_MEMORY.varname, 1000000);
conf.setInt(HiveConf.ConfVars.HIVE_TRANSACTIONAL_NUM_EVENTS_IN_MEMORY.varname, 1000);
testVectorizedOrcAcidRowBatchReader(SortMergedDeleteEventRegistry.class.getName());
// Restore the old value.
conf.setInt(HiveConf.ConfVars.HIVE_TRANSACTIONAL_NUM_EVENTS_IN_MEMORY.varname, oldValue);
}
private void testVectorizedOrcAcidRowBatchReader(String deleteEventRegistry) throws Exception {
List<OrcSplit> splits = getSplits();
// Mark one of the transactions as an exception to test that invalid transactions
// are being handled properly.
conf.set(ValidTxnList.VALID_TXNS_KEY, "14:1:1:5"); // Exclude transaction 5
VectorizedOrcAcidRowBatchReader vectorizedReader = new VectorizedOrcAcidRowBatchReader(splits.get(0), conf, Reporter.NULL);
if (deleteEventRegistry.equals(ColumnizedDeleteEventRegistry.class.getName())) {
assertTrue(vectorizedReader.getDeleteEventRegistry() instanceof ColumnizedDeleteEventRegistry);
}
if (deleteEventRegistry.equals(SortMergedDeleteEventRegistry.class.getName())) {
assertTrue(vectorizedReader.getDeleteEventRegistry() instanceof SortMergedDeleteEventRegistry);
}
TypeDescription schema = OrcInputFormat.getDesiredRowTypeDescr(conf, true, Integer.MAX_VALUE);
VectorizedRowBatch vectorizedRowBatch = schema.createRowBatch();
vectorizedRowBatch.setPartitionInfo(1, 0); // set data column count as 1.
long previousPayload = Long.MIN_VALUE;
while (vectorizedReader.next(null, vectorizedRowBatch)) {
assertTrue(vectorizedRowBatch.selectedInUse);
LongColumnVector col = (LongColumnVector) vectorizedRowBatch.cols[0];
for (int i = 0; i < vectorizedRowBatch.size; ++i) {
int idx = vectorizedRowBatch.selected[i];
long payload = col.vector[idx];
long otid = (payload / NUM_ROWID_PER_OTID) + 1;
long rowId = payload % NUM_ROWID_PER_OTID;
assertFalse(rowId % 2 == 0 || rowId % 3 == 0);
assertTrue(otid != 5); // Check that txn#5 has been excluded.
assertTrue(payload > previousPayload); // Check that the data is in sorted order.
previousPayload = payload;
}
}
}
@Test
public void testCanCreateVectorizedAcidRowBatchReaderOnSplit() throws Exception {
OrcSplit mockSplit = Mockito.mock(OrcSplit.class);
conf.setInt(HiveConf.ConfVars.HIVE_TXN_OPERATIONAL_PROPERTIES.varname,
AcidUtils.AcidOperationalProperties.getLegacy().toInt());
// Test false when trying to create a vectorized ACID row batch reader for a legacy table.
assertFalse(VectorizedOrcAcidRowBatchReader.canCreateVectorizedAcidRowBatchReaderOnSplit(conf, mockSplit));
conf.setInt(HiveConf.ConfVars.HIVE_TXN_OPERATIONAL_PROPERTIES.varname,
AcidUtils.AcidOperationalProperties.getDefault().toInt());
Mockito.when(mockSplit.isOriginal()).thenReturn(true);
// Test false when trying to create a vectorized ACID row batch reader when reading originals.
assertFalse(VectorizedOrcAcidRowBatchReader.canCreateVectorizedAcidRowBatchReaderOnSplit(conf, mockSplit));
// A positive test case.
Mockito.when(mockSplit.isOriginal()).thenReturn(false);
assertTrue(VectorizedOrcAcidRowBatchReader.canCreateVectorizedAcidRowBatchReaderOnSplit(conf, mockSplit));
}
}