yihua commented on a change in pull request #4106:
URL: https://github.com/apache/hudi/pull/4106#discussion_r766850766
##########
File path:
hudi-spark-datasource/hudi-spark/src/test/scala/org/apache/hudi/functional/TestSpaceCurveLayoutOptimization.scala
##########
@@ -52,23 +61,25 @@ class TestTableLayoutOptimization extends
HoodieClientTestBase {
HoodieWriteConfig.TBL_NAME.key -> "hoodie_test"
)
- @BeforeEach override def setUp() {
+ @BeforeEach
+ override def setUp() {
initPath()
initSparkContexts()
spark = sqlContext.sparkSession
initTestDataGenerator()
initFileSystem()
}
- @AfterEach override def tearDown() = {
+ @AfterEach
+ override def tearDown() = {
cleanupSparkContexts()
cleanupTestDataGenerator()
cleanupFileSystem()
}
@ParameterizedTest
- @MethodSource(Array("testLayOutParameter"))
- def testOptimizewithClustering(tableType: String, optimizeMode: String):
Unit = {
+ @MethodSource(Array("testLayoutOptimizationParameters"))
+ def testZOrderingLayoutClustering(tableType: String): Unit = {
Review comment:
I think this is still left out.
##########
File path:
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/sort/SpaceCurveSortingHelper.java
##########
@@ -0,0 +1,260 @@
+/*
+ * 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.hudi.sort;
+
+import org.apache.hudi.common.util.CollectionUtils;
+import org.apache.hudi.config.HoodieClusteringConfig;
+import org.apache.hudi.optimize.HilbertCurveUtils;
+import org.apache.hudi.common.util.BinaryUtil;
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.sql.Column;
+import org.apache.spark.sql.Dataset;
+import org.apache.spark.sql.Row;
+import org.apache.spark.sql.Row$;
+import org.apache.spark.sql.hudi.execution.RangeSampleSort$;
+import org.apache.spark.sql.hudi.execution.ZorderingBinarySort;
+import org.apache.spark.sql.types.BinaryType;
+import org.apache.spark.sql.types.BinaryType$;
+import org.apache.spark.sql.types.BooleanType;
+import org.apache.spark.sql.types.ByteType;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.DateType;
+import org.apache.spark.sql.types.DecimalType;
+import org.apache.spark.sql.types.DoubleType;
+import org.apache.spark.sql.types.FloatType;
+import org.apache.spark.sql.types.IntegerType;
+import org.apache.spark.sql.types.LongType;
+import org.apache.spark.sql.types.Metadata;
+import org.apache.spark.sql.types.ShortType;
+import org.apache.spark.sql.types.StringType;
+import org.apache.spark.sql.types.StructField;
+import org.apache.spark.sql.types.StructType;
+import org.apache.spark.sql.types.StructType$;
+import org.apache.spark.sql.types.TimestampType;
+import org.davidmoten.hilbert.HilbertCurve;
+import scala.collection.JavaConversions;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.function.Function;
+import java.util.stream.Collectors;
+
+public class SpaceCurveSortingHelper {
+
+ private static final Logger LOG =
LogManager.getLogger(SpaceCurveSortingHelper.class);
+
+ /**
+ * Orders provided {@link Dataset} by mapping values of the provided list of
columns
+ * {@code orderByCols} onto a specified space curve (Z-curve, Hilbert, etc)
+ *
+ * <p/>
+ * NOTE: Only support base data-types:
long,int,short,double,float,string,timestamp,decimal,date,byte.
+ * This method is more effective than {@link
#orderDataFrameBySamplingValues} leveraging
+ * data sampling instead of direct mapping
+ *
+ * @param df Spark {@link Dataset} holding data to be ordered
+ * @param orderByCols list of columns to be ordered by
+ * @param targetPartitionCount target number of output partitions
+ * @param layoutOptStrategy target layout optimization strategy
+ * @return a {@link Dataset} holding data ordered by mapping tuple of values
from provided columns
+ * onto a specified space-curve
+ */
+ public static Dataset<Row> orderDataFrameByMappingValues(
+ Dataset<Row> df,
+ HoodieClusteringConfig.LayoutOptimizationStrategy layoutOptStrategy,
+ List<String> orderByCols,
+ int targetPartitionCount
+ ) {
+ Map<String, StructField> columnsMap =
+ Arrays.stream(df.schema().fields())
+ .collect(Collectors.toMap(StructField::name, Function.identity()));
+
+ List<String> checkCols =
+ orderByCols.stream()
+ .filter(columnsMap::containsKey)
+ .collect(Collectors.toList());
+
+ if (orderByCols.size() != checkCols.size()) {
+ LOG.error(String.format("Trying to ordering over a column(s) not present
in the schema (%s); skipping", CollectionUtils.diff(orderByCols, checkCols)));
+ return df;
+ }
+
+ // In case when there's just one column to be ordered by, we can skip
space-curve
+ // ordering altogether (since it will match linear ordering anyway)
+ if (orderByCols.size() == 1) {
+ String orderByColName = orderByCols.get(0);
+ LOG.debug(String.format("Single column to order by (%s), skipping
space-curve ordering", orderByColName));
+
+ // TODO validate if we need Spark to re-partition
+ return df.repartitionByRange(targetPartitionCount, new
Column(orderByColName));
+ }
+
+ int fieldNum = df.schema().fields().length;
+
+ Map<Integer, StructField> fieldMap =
+ orderByCols.stream()
+ .collect(
+ Collectors.toMap(e ->
Arrays.asList(df.schema().fields()).indexOf(columnsMap.get(e)),
columnsMap::get));
+
+ JavaRDD<Row> sortedRDD;
+ switch (layoutOptStrategy) {
+ case ZORDER:
+ sortedRDD = createZCurveSortedRDD(df.toJavaRDD(), fieldMap, fieldNum,
targetPartitionCount);
+ break;
+ case HILBERT:
+ sortedRDD = createHilbertSortedRDD(df.toJavaRDD(), fieldMap, fieldNum,
targetPartitionCount);
+ break;
+ default:
+ throw new IllegalArgumentException(String.format("new only support
z-order/hilbert optimize but find: %s", layoutOptStrategy));
+ }
+
+ // Compose new {@code StructType} for ordered RDDs
+ StructType newStructType = composeOrderedRDDStructType(df.schema());
+
+ return df.sparkSession()
+ .createDataFrame(sortedRDD, newStructType)
+ .drop("Index");
+ }
+
+ private static StructType composeOrderedRDDStructType(StructType schema) {
+ return StructType$.MODULE$.apply(
+ CollectionUtils.combine(
+ Arrays.asList(schema.fields()),
+ Arrays.asList(new StructField("Index", BinaryType$.MODULE$, true,
Metadata.empty()))
+ )
+ );
+ }
+
+ private static JavaRDD<Row> createZCurveSortedRDD(JavaRDD<Row> originRDD,
Map<Integer, StructField> fieldMap, int fieldNum, int fileNum) {
+ return originRDD.map(row -> {
+ List<byte[]> zBytesList = fieldMap.entrySet().stream().map(entry -> {
+ int index = entry.getKey();
+ StructField field = entry.getValue();
+ DataType dataType = field.dataType();
+ if (dataType instanceof LongType) {
+ return BinaryUtil.longTo8Byte(row.isNullAt(index) ? Long.MAX_VALUE :
row.getLong(index));
+ } else if (dataType instanceof DoubleType) {
+ return BinaryUtil.doubleTo8Byte(row.isNullAt(index) ?
Double.MAX_VALUE : row.getDouble(index));
+ } else if (dataType instanceof IntegerType) {
+ return BinaryUtil.intTo8Byte(row.isNullAt(index) ? Integer.MAX_VALUE
: row.getInt(index));
+ } else if (dataType instanceof FloatType) {
+ return BinaryUtil.doubleTo8Byte(row.isNullAt(index) ?
Float.MAX_VALUE : row.getFloat(index));
+ } else if (dataType instanceof StringType) {
+ return BinaryUtil.utf8To8Byte(row.isNullAt(index) ? "" :
row.getString(index));
+ } else if (dataType instanceof DateType) {
+ return BinaryUtil.longTo8Byte(row.isNullAt(index) ? Long.MAX_VALUE :
row.getDate(index).getTime());
+ } else if (dataType instanceof TimestampType) {
+ return BinaryUtil.longTo8Byte(row.isNullAt(index) ? Long.MAX_VALUE :
row.getTimestamp(index).getTime());
+ } else if (dataType instanceof ByteType) {
+ return BinaryUtil.byteTo8Byte(row.isNullAt(index) ? Byte.MAX_VALUE :
row.getByte(index));
+ } else if (dataType instanceof ShortType) {
+ return BinaryUtil.intTo8Byte(row.isNullAt(index) ? Short.MAX_VALUE :
row.getShort(index));
+ } else if (dataType instanceof DecimalType) {
+ return BinaryUtil.longTo8Byte(row.isNullAt(index) ? Long.MAX_VALUE :
row.getDecimal(index).longValue());
+ } else if (dataType instanceof BooleanType) {
+ boolean value = row.isNullAt(index) ? false : row.getBoolean(index);
+ return BinaryUtil.intTo8Byte(value ? 1 : 0);
+ } else if (dataType instanceof BinaryType) {
+ return BinaryUtil.paddingTo8Byte(row.isNullAt(index) ? new byte[]
{0} : (byte[]) row.get(index));
+ }
+ return null;
+ }).filter(f -> f != null).collect(Collectors.toList());
+ byte[][] zBytes = new byte[zBytesList.size()][];
+ for (int i = 0; i < zBytesList.size(); i++) {
+ zBytes[i] = zBytesList.get(i);
+ }
+ List<Object> zVaules = new ArrayList<>();
+
zVaules.addAll(scala.collection.JavaConverters.bufferAsJavaListConverter(row.toSeq().toBuffer()).asJava());
+ zVaules.add(BinaryUtil.interleaving(zBytes, 8));
+ return Row$.MODULE$.apply(JavaConversions.asScalaBuffer(zVaules));
+ })
+ .sortBy(f -> new ZorderingBinarySort((byte[]) f.get(fieldNum)), true,
fileNum);
+ }
+
+ private static JavaRDD<Row> createHilbertSortedRDD(JavaRDD<Row> originRDD,
Map<Integer, StructField> fieldMap, int fieldNum, int fileNum) {
+ return originRDD.mapPartitions(rows -> {
+ HilbertCurve hilbertCurve =
HilbertCurve.bits(63).dimensions(fieldMap.size());
+ return new Iterator<Row>() {
+
+ @Override
+ public boolean hasNext() {
+ return rows.hasNext();
+ }
+
+ @Override
+ public Row next() {
+ Row row = rows.next();
+ List<Long> longList = fieldMap.entrySet().stream().map(entry -> {
+ int index = entry.getKey();
+ StructField field = entry.getValue();
+ DataType dataType = field.dataType();
+ if (dataType instanceof LongType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE : row.getLong(index);
+ } else if (dataType instanceof DoubleType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
Double.doubleToLongBits(row.getDouble(index));
+ } else if (dataType instanceof IntegerType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
(long)row.getInt(index);
+ } else if (dataType instanceof FloatType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
Double.doubleToLongBits((double) row.getFloat(index));
+ } else if (dataType instanceof StringType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
BinaryUtil.convertStringToLong(row.getString(index));
+ } else if (dataType instanceof DateType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
row.getDate(index).getTime();
+ } else if (dataType instanceof TimestampType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
row.getTimestamp(index).getTime();
+ } else if (dataType instanceof ByteType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
BinaryUtil.convertBytesToLong(new byte[] {row.getByte(index)});
+ } else if (dataType instanceof ShortType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
(long)row.getShort(index);
+ } else if (dataType instanceof DecimalType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
row.getDecimal(index).longValue();
+ } else if (dataType instanceof BooleanType) {
+ boolean value = row.isNullAt(index) ? false :
row.getBoolean(index);
+ return value ? Long.MAX_VALUE : 0;
+ } else if (dataType instanceof BinaryType) {
+ return row.isNullAt(index) ? Long.MAX_VALUE :
BinaryUtil.convertBytesToLong((byte[]) row.get(index));
+ }
+ return null;
+ }).filter(f -> f != null).collect(Collectors.toList());
+
+ byte[] hilbertValue = HilbertCurveUtils.indexBytes(
+ hilbertCurve, longList.stream().mapToLong(l -> l).toArray(), 63);
+ List<Object> values = new ArrayList<>();
+
values.addAll(scala.collection.JavaConverters.bufferAsJavaListConverter(row.toSeq().toBuffer()).asJava());
+ values.add(hilbertValue);
+ return Row$.MODULE$.apply(JavaConversions.asScalaBuffer(values));
+ }
+ };
+ }).sortBy(f -> new ZorderingBinarySort((byte[]) f.get(fieldNum)), true,
fileNum);
Review comment:
nit: rename to `OrderingBinarySort`?
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