steveloughran commented on code in PR #14297: URL: https://github.com/apache/iceberg/pull/14297#discussion_r2983740823
########## spark/v4.1/spark/src/test/java/org/apache/iceberg/spark/variant/TestVariantShredding.java: ########## @@ -0,0 +1,1015 @@ +/* + * 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.variant; + +import static org.apache.hadoop.hive.conf.HiveConf.ConfVars.METASTOREURIS; +import static org.apache.iceberg.TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES; +import static org.apache.parquet.schema.Types.optional; +import static org.assertj.core.api.Assertions.assertThat; + +import java.io.IOException; +import java.net.InetAddress; +import java.util.List; +import java.util.Map; +import org.apache.hadoop.conf.Configuration; +import org.apache.iceberg.FileScanTask; +import org.apache.iceberg.Parameters; +import org.apache.iceberg.Schema; +import org.apache.iceberg.Table; +import org.apache.iceberg.TableProperties; +import org.apache.iceberg.io.CloseableIterable; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.spark.CatalogTestBase; +import org.apache.iceberg.spark.SparkCatalogConfig; +import org.apache.iceberg.spark.SparkSQLProperties; +import org.apache.iceberg.types.Types; +import org.apache.iceberg.variants.Variant; +import org.apache.parquet.hadoop.ParquetFileReader; +import org.apache.parquet.hadoop.util.HadoopInputFile; +import org.apache.parquet.schema.GroupType; +import org.apache.parquet.schema.LogicalTypeAnnotation; +import org.apache.parquet.schema.MessageType; +import org.apache.parquet.schema.PrimitiveType; +import org.apache.parquet.schema.Type; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.catalyst.analysis.NoSuchTableException; +import org.apache.spark.sql.internal.SQLConf; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.TestTemplate; + +public class TestVariantShredding extends CatalogTestBase { + + private static final Schema SCHEMA = + new Schema( + Types.NestedField.required(1, "id", Types.IntegerType.get()), + Types.NestedField.optional(2, "address", Types.VariantType.get())); + + private static final Schema SCHEMA2 = + new Schema( + Types.NestedField.required(1, "id", Types.IntegerType.get()), + Types.NestedField.optional(2, "address", Types.VariantType.get()), + Types.NestedField.optional(3, "metadata", Types.VariantType.get())); + + @Parameters(name = "catalogName = {0}, implementation = {1}, config = {2}") + protected static Object[][] parameters() { + return new Object[][] { + { + SparkCatalogConfig.HADOOP.catalogName(), + SparkCatalogConfig.HADOOP.implementation(), + SparkCatalogConfig.HADOOP.properties() + }, + }; + } + + @BeforeAll + public static void startMetastoreAndSpark() { + // First call parent to initialize metastore and spark with local[2] + CatalogTestBase.startMetastoreAndSpark(); + + // Now stop and recreate spark with local[1] to write all rows to a single file + if (spark != null) { + spark.stop(); + } + + spark = + SparkSession.builder() + .master("local[1]") // Use one thread to write the rows to a single parquet file + .config("spark.driver.host", InetAddress.getLoopbackAddress().getHostAddress()) + .config(SQLConf.PARTITION_OVERWRITE_MODE().key(), "dynamic") + .config("spark.hadoop." + METASTOREURIS.varname, hiveConf.get(METASTOREURIS.varname)) + .config("spark.sql.legacy.respectNullabilityInTextDatasetConversion", "true") + .enableHiveSupport() + .getOrCreate(); + + sparkContext = JavaSparkContext.fromSparkContext(spark.sparkContext()); + } + + @BeforeEach + public void before() { + super.before(); + validationCatalog.createTable( + tableIdent, SCHEMA, null, Map.of(TableProperties.FORMAT_VERSION, "3")); + } + + @AfterEach + public void after() { + spark.conf().unset(SparkSQLProperties.SHRED_VARIANTS); + spark.conf().unset(SparkSQLProperties.VARIANT_INFERENCE_BUFFER_SIZE); + validationCatalog.dropTable(tableIdent, true); + } + + @TestTemplate + public void testVariantShreddingDisabled() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "false"); + + String values = "(1, parse_json('{\"city\": \"NYC\", \"zip\": 10001}')), (2, null)"; + sql("INSERT INTO %s VALUES %s", tableName, values); + + GroupType address = variant("address", 2, Type.Repetition.OPTIONAL); + MessageType expectedSchema = parquetSchema(address); + + Table table = validationCatalog.loadTable(tableIdent); + verifyParquetSchema(table, expectedSchema); + } + + @TestTemplate + public void testExcludingNullValue() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "true"); + + String values = + "(1, parse_json('{\"name\": \"Alice\", \"age\": 30, \"dummy\": null}'))," + + " (2, parse_json('{\"name\": \"Bob\", \"age\": 25}'))," + + " (3, parse_json('{\"name\": \"Charlie\", \"age\": 35}'))"; + sql("INSERT INTO %s VALUES %s", tableName, values); + + GroupType name = + field( + "name", + shreddedPrimitive( + PrimitiveType.PrimitiveTypeName.BINARY, LogicalTypeAnnotation.stringType())); + GroupType age = + field( + "age", + shreddedPrimitive( + PrimitiveType.PrimitiveTypeName.INT32, LogicalTypeAnnotation.intType(8, true))); + GroupType address = variant("address", 2, Type.Repetition.REQUIRED, objectFields(age, name)); + MessageType expectedSchema = parquetSchema(address); + + Table table = validationCatalog.loadTable(tableIdent); + verifyParquetSchema(table, expectedSchema); + } + + @TestTemplate + public void testInconsistentType() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "true"); + + String values = + "(1, parse_json('{\"age\": \"25\"}'))," Review Comment: java17 has that """" multiline string thing which is ideal for json like this ########## spark/v4.1/spark/src/test/java/org/apache/iceberg/spark/variant/TestVariantShredding.java: ########## @@ -0,0 +1,1015 @@ +/* + * 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.variant; + +import static org.apache.hadoop.hive.conf.HiveConf.ConfVars.METASTOREURIS; +import static org.apache.iceberg.TableProperties.PARQUET_ROW_GROUP_SIZE_BYTES; +import static org.apache.parquet.schema.Types.optional; +import static org.assertj.core.api.Assertions.assertThat; + +import java.io.IOException; +import java.net.InetAddress; +import java.util.List; +import java.util.Map; +import org.apache.hadoop.conf.Configuration; +import org.apache.iceberg.FileScanTask; +import org.apache.iceberg.Parameters; +import org.apache.iceberg.Schema; +import org.apache.iceberg.Table; +import org.apache.iceberg.TableProperties; +import org.apache.iceberg.io.CloseableIterable; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.spark.CatalogTestBase; +import org.apache.iceberg.spark.SparkCatalogConfig; +import org.apache.iceberg.spark.SparkSQLProperties; +import org.apache.iceberg.types.Types; +import org.apache.iceberg.variants.Variant; +import org.apache.parquet.hadoop.ParquetFileReader; +import org.apache.parquet.hadoop.util.HadoopInputFile; +import org.apache.parquet.schema.GroupType; +import org.apache.parquet.schema.LogicalTypeAnnotation; +import org.apache.parquet.schema.MessageType; +import org.apache.parquet.schema.PrimitiveType; +import org.apache.parquet.schema.Type; +import org.apache.spark.api.java.JavaSparkContext; +import org.apache.spark.sql.SparkSession; +import org.apache.spark.sql.catalyst.analysis.NoSuchTableException; +import org.apache.spark.sql.internal.SQLConf; +import org.junit.jupiter.api.AfterEach; +import org.junit.jupiter.api.BeforeAll; +import org.junit.jupiter.api.BeforeEach; +import org.junit.jupiter.api.TestTemplate; + +public class TestVariantShredding extends CatalogTestBase { + + private static final Schema SCHEMA = + new Schema( + Types.NestedField.required(1, "id", Types.IntegerType.get()), + Types.NestedField.optional(2, "address", Types.VariantType.get())); + + private static final Schema SCHEMA2 = + new Schema( + Types.NestedField.required(1, "id", Types.IntegerType.get()), + Types.NestedField.optional(2, "address", Types.VariantType.get()), + Types.NestedField.optional(3, "metadata", Types.VariantType.get())); + + @Parameters(name = "catalogName = {0}, implementation = {1}, config = {2}") + protected static Object[][] parameters() { + return new Object[][] { + { + SparkCatalogConfig.HADOOP.catalogName(), + SparkCatalogConfig.HADOOP.implementation(), + SparkCatalogConfig.HADOOP.properties() + }, + }; + } + + @BeforeAll + public static void startMetastoreAndSpark() { + // First call parent to initialize metastore and spark with local[2] + CatalogTestBase.startMetastoreAndSpark(); + + // Now stop and recreate spark with local[1] to write all rows to a single file + if (spark != null) { + spark.stop(); + } + + spark = + SparkSession.builder() + .master("local[1]") // Use one thread to write the rows to a single parquet file + .config("spark.driver.host", InetAddress.getLoopbackAddress().getHostAddress()) + .config(SQLConf.PARTITION_OVERWRITE_MODE().key(), "dynamic") + .config("spark.hadoop." + METASTOREURIS.varname, hiveConf.get(METASTOREURIS.varname)) + .config("spark.sql.legacy.respectNullabilityInTextDatasetConversion", "true") + .enableHiveSupport() + .getOrCreate(); + + sparkContext = JavaSparkContext.fromSparkContext(spark.sparkContext()); + } + + @BeforeEach + public void before() { + super.before(); + validationCatalog.createTable( + tableIdent, SCHEMA, null, Map.of(TableProperties.FORMAT_VERSION, "3")); + } + + @AfterEach + public void after() { + spark.conf().unset(SparkSQLProperties.SHRED_VARIANTS); + spark.conf().unset(SparkSQLProperties.VARIANT_INFERENCE_BUFFER_SIZE); + validationCatalog.dropTable(tableIdent, true); + } + + @TestTemplate + public void testVariantShreddingDisabled() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "false"); + + String values = "(1, parse_json('{\"city\": \"NYC\", \"zip\": 10001}')), (2, null)"; + sql("INSERT INTO %s VALUES %s", tableName, values); + + GroupType address = variant("address", 2, Type.Repetition.OPTIONAL); + MessageType expectedSchema = parquetSchema(address); + + Table table = validationCatalog.loadTable(tableIdent); + verifyParquetSchema(table, expectedSchema); + } + + @TestTemplate + public void testExcludingNullValue() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "true"); + + String values = + "(1, parse_json('{\"name\": \"Alice\", \"age\": 30, \"dummy\": null}'))," + + " (2, parse_json('{\"name\": \"Bob\", \"age\": 25}'))," + + " (3, parse_json('{\"name\": \"Charlie\", \"age\": 35}'))"; + sql("INSERT INTO %s VALUES %s", tableName, values); + + GroupType name = + field( + "name", + shreddedPrimitive( + PrimitiveType.PrimitiveTypeName.BINARY, LogicalTypeAnnotation.stringType())); + GroupType age = + field( + "age", + shreddedPrimitive( + PrimitiveType.PrimitiveTypeName.INT32, LogicalTypeAnnotation.intType(8, true))); + GroupType address = variant("address", 2, Type.Repetition.REQUIRED, objectFields(age, name)); + MessageType expectedSchema = parquetSchema(address); + + Table table = validationCatalog.loadTable(tableIdent); + verifyParquetSchema(table, expectedSchema); + } + + @TestTemplate + public void testInconsistentType() throws IOException { + spark.conf().set(SparkSQLProperties.SHRED_VARIANTS, "true"); + + String values = + "(1, parse_json('{\"age\": \"25\"}'))," + + " (2, parse_json('{\"age\": 30}'))," + + " (3, parse_json('{\"age\": \"35\"}'))"; + sql("INSERT INTO %s VALUES %s", tableName, values); + + GroupType age = + field( + "age", + shreddedPrimitive( + PrimitiveType.PrimitiveTypeName.BINARY, LogicalTypeAnnotation.stringType())); + GroupType address = variant("address", 2, Type.Repetition.REQUIRED, objectFields(age)); + MessageType expectedSchema = parquetSchema(address); + + Table table = validationCatalog.loadTable(tableIdent); + verifyParquetSchema(table, expectedSchema); Review Comment: I'd add a test to make sure that row 2 had age of value 30:int, just to make sure that the parser hasn't decided to "be helpful" ########## core/src/main/java/org/apache/iceberg/io/BufferedFileAppender.java: ########## @@ -0,0 +1,132 @@ +/* + * 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.io; + +import java.io.IOException; +import java.util.List; +import java.util.function.Function; +import java.util.function.UnaryOperator; +import org.apache.iceberg.Metrics; +import org.apache.iceberg.relocated.com.google.common.base.Preconditions; +import org.apache.iceberg.relocated.com.google.common.collect.Lists; + +/** + * A FileAppender that buffers the first N rows, then creates a delegate appender via a factory. + * + * <p>The factory receives the buffered rows, is responsible for creating the real appender and + * writing the buffered rows into it before returning. All subsequent {@link #add} calls delegate + * directly to the real appender. + * + * <p>If fewer than N rows are written before {@link #close}, the factory is called at close time. + * + * @param <D> the row type + */ +public class BufferedFileAppender<D> implements FileAppender<D> { + private final int bufferRowCount; + private final Function<List<D>, FileAppender<D>> appenderFactory; + private final UnaryOperator<D> copyFunc; + private List<D> buffer; + private FileAppender<D> delegate; + private boolean closed = false; + + /** + * @param bufferRowCount number of rows to buffer before creating the delegate appender + * @param appenderFactory given the buffered rows, creates the delegate appender and replays them + * @param copyFunc copies a row before buffering (needed when row objects are reused, e.g. Spark + * InternalRow) + */ + public BufferedFileAppender( + int bufferRowCount, + Function<List<D>, FileAppender<D>> appenderFactory, + UnaryOperator<D> copyFunc) { + Preconditions.checkArgument( + bufferRowCount > 0, "bufferRowCount must be > 0, got %s", bufferRowCount); + Preconditions.checkNotNull(appenderFactory, "appenderFactory must not be null"); + Preconditions.checkNotNull(copyFunc, "copyFunc must not be null"); + this.bufferRowCount = bufferRowCount; + this.appenderFactory = appenderFactory; + this.copyFunc = copyFunc; + this.buffer = Lists.newArrayList(); + } + + @Override + public void add(D datum) { + Preconditions.checkState(!closed, "Cannot add to a closed appender"); + if (delegate != null) { + delegate.add(datum); + } else { + buffer.add(copyFunc.apply(datum)); + if (buffer.size() >= bufferRowCount) { + initialize(); + } + } + } + + @Override + public Metrics metrics() { + Preconditions.checkState(closed, "Cannot return metrics for unclosed appender"); + Preconditions.checkState(delegate != null, "Delegate appender was never created"); + return delegate.metrics(); + } + + @Override + public long length() { + if (delegate != null) { + return delegate.length(); + } + return 0L; + } + + @Override + public List<Long> splitOffsets() { + if (delegate != null) { + return delegate.splitOffsets(); + } + return null; + } + + @Override + public void close() throws IOException { Review Comment: what happens on a create().close() sequence with no data written? it should be a no-op. 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