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new ea73769d12 Spark 3.5, 4.0, 4.1: Backport format model TCK coverage for
vectorized reads (#18790)
ea73769d12 is described below
commit ea73769d120dc3819d8cfa2253b6dba4bb394886
Author: Joy Haldar <[email protected]>
AuthorDate: Wed Nov 4 23:07:28 2026 +0530
Spark 3.5, 4.0, 4.1: Backport format model TCK coverage for vectorized
reads (#18790)
* Spark 3.5, 4.0, 4.1: Backport format model TCK coverage for vectorized
reads
Co-authored-by: Joy Haldar <[email protected]>
* Fix formatting
Co-authored-by: Joy Haldar <[email protected]>
---------
Co-authored-by: Joy Haldar <[email protected]>
---
.../spark/data/TestSparkVectorizedFormatModel.java | 208 +++++++++++++++++++++
.../spark/data/TestSparkVectorizedFormatModel.java | 207 ++++++++++++++++++++
.../spark/data/TestSparkVectorizedFormatModel.java | 207 ++++++++++++++++++++
3 files changed, 622 insertions(+)
diff --git
a/spark/v3.5/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
b/spark/v3.5/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
new file mode 100644
index 0000000000..99f6d07429
--- /dev/null
+++
b/spark/v3.5/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
@@ -0,0 +1,208 @@
+/*
+ * 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.iceberg.spark.data;
+
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.assertj.core.api.Assumptions.assumeThat;
+
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.List;
+import java.util.Set;
+import org.apache.arrow.vector.ValueVector;
+import org.apache.iceberg.FileFormat;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.data.DataGenerator;
+import org.apache.iceberg.data.DataGenerators;
+import org.apache.iceberg.data.ReadFormatModelTests;
+import org.apache.iceberg.data.Record;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.SparkUtil;
+import org.apache.iceberg.spark.data.vectorized.IcebergArrowColumnVector;
+import org.apache.iceberg.types.Type;
+import org.apache.spark.sql.vectorized.ColumnarBatch;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.FieldSource;
+
+class TestSparkVectorizedFormatModel extends
ReadFormatModelTests<ColumnarBatch> {
+
+ private static final FileFormat[] FILE_FORMATS = {FileFormat.ORC,
FileFormat.PARQUET};
+
+ // Spark 3.5 has no TIME, TIMESTAMP_NANO or VARIANT type
+ private static final Set<Type.TypeID> SPARK_UNSUPPORTED_TYPE_IDS =
+ Set.of(Type.TypeID.TIME, Type.TypeID.TIMESTAMP_NANO,
Type.TypeID.VARIANT);
+
+ // The Arrow-based Parquet reader cannot read nested or geospatial columns;
+ // the vectorized ORC reader supports nested types.
+ private static final Set<Type.TypeID> ARROW_UNSUPPORTED_TYPE_IDS =
+ Set.of(
+ Type.TypeID.STRUCT,
+ Type.TypeID.LIST,
+ Type.TypeID.MAP,
+ Type.TypeID.GEOMETRY,
+ Type.TypeID.GEOGRAPHY);
+
+ private static final Set<Type.TypeID> PARQUET_UNSUPPORTED_TYPE_IDS =
+ ImmutableSet.<Type.TypeID>builder()
+ .addAll(SPARK_UNSUPPORTED_TYPE_IDS)
+ .addAll(ARROW_UNSUPPORTED_TYPE_IDS)
+ .build();
+
+ private static final List<Arguments> FORMAT_AND_GENERATOR =
+ Arrays.stream(FILE_FORMATS)
+ .flatMap(
+ format ->
+ Arrays.stream(DataGenerators.ALL)
+ .filter(generator -> supportsVectorized(format,
generator))
+ .map(generator -> Arguments.of(format, generator)))
+ .toList();
+
+ private static boolean supportsVectorized(FileFormat format, DataGenerator
generator) {
+ return supportsGenerator(format, generator)
+ && (format != FileFormat.PARQUET
+ || !containsType(generator.schema(), ARROW_UNSUPPORTED_TYPE_IDS));
+ }
+
+ @Override
+ protected Collection<Type.TypeID> unsupportedTypeIds(FileFormat fileFormat) {
+ return fileFormat == FileFormat.PARQUET
+ ? PARQUET_UNSUPPORTED_TYPE_IDS
+ : SPARK_UNSUPPORTED_TYPE_IDS;
+ }
+
+ @Override
+ protected boolean supportsBatchReads() {
+ return true;
+ }
+
+ @Override
+ protected int countRows(List<ColumnarBatch> batches) {
+ return batches.stream().mapToInt(ColumnarBatch::numRows).sum();
+ }
+
+ @Override
+ protected void assertContainersReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnIsDeleted(FileFormat fileFormat) throws
IOException {
+ assumeThat(fileFormat)
+ .as("Vectorized Parquet reader only populates _deleted when a delete
filter is set")
+ .isNotEqualTo(FileFormat.PARQUET);
+ super.testReadMetadataColumnIsDeleted(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineage(FileFormat fileFormat)
throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineage(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineageExistingValues(FileFormat
fileFormat)
+ throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineageExistingValues(fileFormat);
+ }
+
+ // TODO: remove when https://github.com/apache/iceberg/issues/18543 is fixed
+ private static void assumeRowLineageSupported(FileFormat fileFormat) {
+ assumeThat(fileFormat)
+ .as("Vectorized ORC reader does not apply row lineage")
+ .isNotEqualTo(FileFormat.ORC);
+ }
+
+ private ValueVector arrowVector(ColumnarBatch batch, int col) {
+ assertThat(batch.column(col)).isInstanceOf(IcebergArrowColumnVector.class);
+
+ IcebergArrowColumnVector vector = (IcebergArrowColumnVector)
batch.column(col);
+ return vector.vectorAccessor().getVector();
+ }
+
+ @Override
+ protected void assertContainersNotReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isNotSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ protected Object engineSchema(Schema schema) {
+ return SparkSchemaUtil.convert(schema);
+ }
+
+ @Override
+ protected Object convertConstantToEngine(Type type, Object value) {
+ return SparkUtil.internalToSpark(type, value);
+ }
+
+ @Override
+ protected Class<ColumnarBatch> engineType() {
+ return ColumnarBatch.class;
+ }
+
+ @Override
+ protected ColumnarBatch convertToEngine(Record record, Schema schema) {
+ throw new UnsupportedOperationException("Vectorized reads are read-only");
+ }
+
+ @Override
+ protected void assertEquals(
+ Schema schema, List<ColumnarBatch> expected, List<ColumnarBatch> actual)
{
+ throw new UnsupportedOperationException("Use assertRecordsEqual for batch
reads");
+ }
+
+ @Override
+ protected void assertRecordsEqual(
+ Schema schema, List<Record> expected, CloseableIterable<ColumnarBatch>
actual) {
+ int rowOffset = 0;
+
+ for (ColumnarBatch batch : actual) {
+ assertThat(rowOffset +
batch.numRows()).isLessThanOrEqualTo(expected.size());
+
+ for (int i = 0; i < batch.numRows(); i++) {
+ TestHelpers.assertEquals(
+ schema,
+ InternalRowConverter.convert(schema, expected.get(rowOffset + i)),
+ batch.getRow(i));
+ }
+
+ rowOffset += batch.numRows();
+ }
+
+ assertThat(rowOffset).isEqualTo(expected.size());
+ }
+}
diff --git
a/spark/v4.0/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
b/spark/v4.0/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
new file mode 100644
index 0000000000..88b4d7e214
--- /dev/null
+++
b/spark/v4.0/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
@@ -0,0 +1,207 @@
+/*
+ * 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.iceberg.spark.data;
+
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.assertj.core.api.Assumptions.assumeThat;
+
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.List;
+import java.util.Set;
+import org.apache.arrow.vector.ValueVector;
+import org.apache.iceberg.FileFormat;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.data.DataGenerator;
+import org.apache.iceberg.data.DataGenerators;
+import org.apache.iceberg.data.ReadFormatModelTests;
+import org.apache.iceberg.data.Record;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.SparkUtil;
+import org.apache.iceberg.spark.data.vectorized.IcebergArrowColumnVector;
+import org.apache.iceberg.types.Type;
+import org.apache.spark.sql.vectorized.ColumnarBatch;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.FieldSource;
+
+class TestSparkVectorizedFormatModel extends
ReadFormatModelTests<ColumnarBatch> {
+
+ private static final FileFormat[] FILE_FORMATS = {FileFormat.ORC,
FileFormat.PARQUET};
+
+ private static final Set<Type.TypeID> SPARK_UNSUPPORTED_TYPE_IDS =
+ Set.of(Type.TypeID.TIME, Type.TypeID.TIMESTAMP_NANO);
+
+ // The Arrow-based Parquet reader cannot read nested or geospatial columns;
+ // the vectorized ORC reader supports nested types.
+ private static final Set<Type.TypeID> ARROW_UNSUPPORTED_TYPE_IDS =
+ Set.of(
+ Type.TypeID.STRUCT,
+ Type.TypeID.LIST,
+ Type.TypeID.MAP,
+ Type.TypeID.GEOMETRY,
+ Type.TypeID.GEOGRAPHY);
+
+ private static final Set<Type.TypeID> PARQUET_UNSUPPORTED_TYPE_IDS =
+ ImmutableSet.<Type.TypeID>builder()
+ .addAll(SPARK_UNSUPPORTED_TYPE_IDS)
+ .addAll(ARROW_UNSUPPORTED_TYPE_IDS)
+ .build();
+
+ private static final List<Arguments> FORMAT_AND_GENERATOR =
+ Arrays.stream(FILE_FORMATS)
+ .flatMap(
+ format ->
+ Arrays.stream(DataGenerators.ALL)
+ .filter(generator -> supportsVectorized(format,
generator))
+ .map(generator -> Arguments.of(format, generator)))
+ .toList();
+
+ private static boolean supportsVectorized(FileFormat format, DataGenerator
generator) {
+ return supportsGenerator(format, generator)
+ && (format != FileFormat.PARQUET
+ || !containsType(generator.schema(), ARROW_UNSUPPORTED_TYPE_IDS));
+ }
+
+ @Override
+ protected Collection<Type.TypeID> unsupportedTypeIds(FileFormat fileFormat) {
+ return fileFormat == FileFormat.PARQUET
+ ? PARQUET_UNSUPPORTED_TYPE_IDS
+ : SPARK_UNSUPPORTED_TYPE_IDS;
+ }
+
+ @Override
+ protected boolean supportsBatchReads() {
+ return true;
+ }
+
+ @Override
+ protected int countRows(List<ColumnarBatch> batches) {
+ return batches.stream().mapToInt(ColumnarBatch::numRows).sum();
+ }
+
+ @Override
+ protected void assertContainersReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnIsDeleted(FileFormat fileFormat) throws
IOException {
+ assumeThat(fileFormat)
+ .as("Vectorized Parquet reader only populates _deleted when a delete
filter is set")
+ .isNotEqualTo(FileFormat.PARQUET);
+ super.testReadMetadataColumnIsDeleted(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineage(FileFormat fileFormat)
throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineage(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineageExistingValues(FileFormat
fileFormat)
+ throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineageExistingValues(fileFormat);
+ }
+
+ // TODO: remove when https://github.com/apache/iceberg/issues/18543 is fixed
+ private static void assumeRowLineageSupported(FileFormat fileFormat) {
+ assumeThat(fileFormat)
+ .as("Vectorized ORC reader does not apply row lineage")
+ .isNotEqualTo(FileFormat.ORC);
+ }
+
+ private ValueVector arrowVector(ColumnarBatch batch, int col) {
+ assertThat(batch.column(col)).isInstanceOf(IcebergArrowColumnVector.class);
+
+ IcebergArrowColumnVector vector = (IcebergArrowColumnVector)
batch.column(col);
+ return vector.vectorAccessor().getVector();
+ }
+
+ @Override
+ protected void assertContainersNotReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isNotSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ protected Object engineSchema(Schema schema) {
+ return SparkSchemaUtil.convert(schema);
+ }
+
+ @Override
+ protected Object convertConstantToEngine(Type type, Object value) {
+ return SparkUtil.internalToSpark(type, value);
+ }
+
+ @Override
+ protected Class<ColumnarBatch> engineType() {
+ return ColumnarBatch.class;
+ }
+
+ @Override
+ protected ColumnarBatch convertToEngine(Record record, Schema schema) {
+ throw new UnsupportedOperationException("Vectorized reads are read-only");
+ }
+
+ @Override
+ protected void assertEquals(
+ Schema schema, List<ColumnarBatch> expected, List<ColumnarBatch> actual)
{
+ throw new UnsupportedOperationException("Use assertRecordsEqual for batch
reads");
+ }
+
+ @Override
+ protected void assertRecordsEqual(
+ Schema schema, List<Record> expected, CloseableIterable<ColumnarBatch>
actual) {
+ int rowOffset = 0;
+
+ for (ColumnarBatch batch : actual) {
+ assertThat(rowOffset +
batch.numRows()).isLessThanOrEqualTo(expected.size());
+
+ for (int i = 0; i < batch.numRows(); i++) {
+ TestHelpers.assertEquals(
+ schema,
+ InternalRowConverter.convert(schema, expected.get(rowOffset + i)),
+ batch.getRow(i));
+ }
+
+ rowOffset += batch.numRows();
+ }
+
+ assertThat(rowOffset).isEqualTo(expected.size());
+ }
+}
diff --git
a/spark/v4.1/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
b/spark/v4.1/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
new file mode 100644
index 0000000000..88b4d7e214
--- /dev/null
+++
b/spark/v4.1/spark/src/test/java/org/apache/iceberg/spark/data/TestSparkVectorizedFormatModel.java
@@ -0,0 +1,207 @@
+/*
+ * 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.iceberg.spark.data;
+
+import static org.assertj.core.api.Assertions.assertThat;
+import static org.assertj.core.api.Assumptions.assumeThat;
+
+import java.io.IOException;
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.List;
+import java.util.Set;
+import org.apache.arrow.vector.ValueVector;
+import org.apache.iceberg.FileFormat;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.data.DataGenerator;
+import org.apache.iceberg.data.DataGenerators;
+import org.apache.iceberg.data.ReadFormatModelTests;
+import org.apache.iceberg.data.Record;
+import org.apache.iceberg.io.CloseableIterable;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableSet;
+import org.apache.iceberg.spark.SparkSchemaUtil;
+import org.apache.iceberg.spark.SparkUtil;
+import org.apache.iceberg.spark.data.vectorized.IcebergArrowColumnVector;
+import org.apache.iceberg.types.Type;
+import org.apache.spark.sql.vectorized.ColumnarBatch;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.FieldSource;
+
+class TestSparkVectorizedFormatModel extends
ReadFormatModelTests<ColumnarBatch> {
+
+ private static final FileFormat[] FILE_FORMATS = {FileFormat.ORC,
FileFormat.PARQUET};
+
+ private static final Set<Type.TypeID> SPARK_UNSUPPORTED_TYPE_IDS =
+ Set.of(Type.TypeID.TIME, Type.TypeID.TIMESTAMP_NANO);
+
+ // The Arrow-based Parquet reader cannot read nested or geospatial columns;
+ // the vectorized ORC reader supports nested types.
+ private static final Set<Type.TypeID> ARROW_UNSUPPORTED_TYPE_IDS =
+ Set.of(
+ Type.TypeID.STRUCT,
+ Type.TypeID.LIST,
+ Type.TypeID.MAP,
+ Type.TypeID.GEOMETRY,
+ Type.TypeID.GEOGRAPHY);
+
+ private static final Set<Type.TypeID> PARQUET_UNSUPPORTED_TYPE_IDS =
+ ImmutableSet.<Type.TypeID>builder()
+ .addAll(SPARK_UNSUPPORTED_TYPE_IDS)
+ .addAll(ARROW_UNSUPPORTED_TYPE_IDS)
+ .build();
+
+ private static final List<Arguments> FORMAT_AND_GENERATOR =
+ Arrays.stream(FILE_FORMATS)
+ .flatMap(
+ format ->
+ Arrays.stream(DataGenerators.ALL)
+ .filter(generator -> supportsVectorized(format,
generator))
+ .map(generator -> Arguments.of(format, generator)))
+ .toList();
+
+ private static boolean supportsVectorized(FileFormat format, DataGenerator
generator) {
+ return supportsGenerator(format, generator)
+ && (format != FileFormat.PARQUET
+ || !containsType(generator.schema(), ARROW_UNSUPPORTED_TYPE_IDS));
+ }
+
+ @Override
+ protected Collection<Type.TypeID> unsupportedTypeIds(FileFormat fileFormat) {
+ return fileFormat == FileFormat.PARQUET
+ ? PARQUET_UNSUPPORTED_TYPE_IDS
+ : SPARK_UNSUPPORTED_TYPE_IDS;
+ }
+
+ @Override
+ protected boolean supportsBatchReads() {
+ return true;
+ }
+
+ @Override
+ protected int countRows(List<ColumnarBatch> batches) {
+ return batches.stream().mapToInt(ColumnarBatch::numRows).sum();
+ }
+
+ @Override
+ protected void assertContainersReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnIsDeleted(FileFormat fileFormat) throws
IOException {
+ assumeThat(fileFormat)
+ .as("Vectorized Parquet reader only populates _deleted when a delete
filter is set")
+ .isNotEqualTo(FileFormat.PARQUET);
+ super.testReadMetadataColumnIsDeleted(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineage(FileFormat fileFormat)
throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineage(fileFormat);
+ }
+
+ @Override
+ @ParameterizedTest
+ @FieldSource("FILE_FORMATS")
+ protected void testReadMetadataColumnRowLineageExistingValues(FileFormat
fileFormat)
+ throws IOException {
+ assumeRowLineageSupported(fileFormat);
+ super.testReadMetadataColumnRowLineageExistingValues(fileFormat);
+ }
+
+ // TODO: remove when https://github.com/apache/iceberg/issues/18543 is fixed
+ private static void assumeRowLineageSupported(FileFormat fileFormat) {
+ assumeThat(fileFormat)
+ .as("Vectorized ORC reader does not apply row lineage")
+ .isNotEqualTo(FileFormat.ORC);
+ }
+
+ private ValueVector arrowVector(ColumnarBatch batch, int col) {
+ assertThat(batch.column(col)).isInstanceOf(IcebergArrowColumnVector.class);
+
+ IcebergArrowColumnVector vector = (IcebergArrowColumnVector)
batch.column(col);
+ return vector.vectorAccessor().getVector();
+ }
+
+ @Override
+ protected void assertContainersNotReused(ColumnarBatch first, ColumnarBatch
second) {
+ assertThat(second.numCols()).isEqualTo(first.numCols());
+
+ for (int i = 0; i < first.numCols(); i++) {
+ assertThat(arrowVector(second, i)).isNotSameAs(arrowVector(first, i));
+ }
+ }
+
+ @Override
+ protected Object engineSchema(Schema schema) {
+ return SparkSchemaUtil.convert(schema);
+ }
+
+ @Override
+ protected Object convertConstantToEngine(Type type, Object value) {
+ return SparkUtil.internalToSpark(type, value);
+ }
+
+ @Override
+ protected Class<ColumnarBatch> engineType() {
+ return ColumnarBatch.class;
+ }
+
+ @Override
+ protected ColumnarBatch convertToEngine(Record record, Schema schema) {
+ throw new UnsupportedOperationException("Vectorized reads are read-only");
+ }
+
+ @Override
+ protected void assertEquals(
+ Schema schema, List<ColumnarBatch> expected, List<ColumnarBatch> actual)
{
+ throw new UnsupportedOperationException("Use assertRecordsEqual for batch
reads");
+ }
+
+ @Override
+ protected void assertRecordsEqual(
+ Schema schema, List<Record> expected, CloseableIterable<ColumnarBatch>
actual) {
+ int rowOffset = 0;
+
+ for (ColumnarBatch batch : actual) {
+ assertThat(rowOffset +
batch.numRows()).isLessThanOrEqualTo(expected.size());
+
+ for (int i = 0; i < batch.numRows(); i++) {
+ TestHelpers.assertEquals(
+ schema,
+ InternalRowConverter.convert(schema, expected.get(rowOffset + i)),
+ batch.getRow(i));
+ }
+
+ rowOffset += batch.numRows();
+ }
+
+ assertThat(rowOffset).isEqualTo(expected.size());
+ }
+}
