rdblue commented on a change in pull request #1237:
URL: https://github.com/apache/iceberg/pull/1237#discussion_r460561369
##########
File path:
flink/src/main/java/org/apache/iceberg/flink/data/FlinkParquetReaders.java
##########
@@ -19,64 +19,714 @@
package org.apache.iceberg.flink.data;
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.nio.ByteBuffer;
import java.util.List;
-import org.apache.flink.types.Row;
+import java.util.Map;
+import org.apache.commons.lang3.ArrayUtils;
+import org.apache.flink.table.data.ArrayData;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.GenericRowData;
+import org.apache.flink.table.data.MapData;
+import org.apache.flink.table.data.RawValueData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.data.StringData;
+import org.apache.flink.table.data.TimestampData;
import org.apache.iceberg.Schema;
-import org.apache.iceberg.data.parquet.BaseParquetReaders;
+import org.apache.iceberg.parquet.ParquetSchemaUtil;
import org.apache.iceberg.parquet.ParquetValueReader;
import org.apache.iceberg.parquet.ParquetValueReaders;
+import org.apache.iceberg.parquet.TypeWithSchemaVisitor;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableList;
+import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap;
+import org.apache.iceberg.relocated.com.google.common.collect.Lists;
+import org.apache.iceberg.relocated.com.google.common.collect.Maps;
import org.apache.iceberg.types.Types;
+import org.apache.parquet.column.ColumnDescriptor;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.GroupType;
+import
org.apache.parquet.schema.LogicalTypeAnnotation.DecimalLogicalTypeAnnotation;
import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.PrimitiveType;
import org.apache.parquet.schema.Type;
-public class FlinkParquetReaders extends BaseParquetReaders<Row> {
+public class FlinkParquetReaders {
+ private FlinkParquetReaders() {
+ }
- private static final FlinkParquetReaders INSTANCE = new
FlinkParquetReaders();
+ public static ParquetValueReader<RowData> buildReader(Schema expectedSchema,
MessageType fileSchema) {
+ return buildReader(expectedSchema, fileSchema, ImmutableMap.of());
+ }
- private FlinkParquetReaders() {
+ @SuppressWarnings("unchecked")
+ public static ParquetValueReader<RowData> buildReader(Schema expectedSchema,
+ MessageType fileSchema,
+ Map<Integer, ?>
idToConstant) {
+ if (ParquetSchemaUtil.hasIds(fileSchema)) {
+ return (ParquetValueReader<RowData>)
+ TypeWithSchemaVisitor.visit(expectedSchema.asStruct(), fileSchema,
+ new ReadBuilder(fileSchema, idToConstant));
+ } else {
+ return (ParquetValueReader<RowData>)
+ TypeWithSchemaVisitor.visit(expectedSchema.asStruct(), fileSchema,
+ new FallbackReadBuilder(fileSchema, idToConstant));
+ }
+ }
+
+ private static class FallbackReadBuilder extends ReadBuilder {
+ FallbackReadBuilder(MessageType type, Map<Integer, ?> idToConstant) {
+ super(type, idToConstant);
+ }
+
+ @Override
+ public ParquetValueReader<?> message(Types.StructType expected,
MessageType message,
+ List<ParquetValueReader<?>>
fieldReaders) {
+ // the top level matches by ID, but the remaining IDs are missing
+ return super.struct(expected, message, fieldReaders);
+ }
+
+ @Override
+ public ParquetValueReader<?> struct(Types.StructType ignored, GroupType
struct,
+ List<ParquetValueReader<?>>
fieldReaders) {
+ // the expected struct is ignored because nested fields are never found
when the
+ List<ParquetValueReader<?>> newFields =
Lists.newArrayListWithExpectedSize(
+ fieldReaders.size());
+ List<Type> types =
Lists.newArrayListWithExpectedSize(fieldReaders.size());
+ List<Type> fields = struct.getFields();
+ for (int i = 0; i < fields.size(); i += 1) {
+ Type fieldType = fields.get(i);
+ int fieldD = type().getMaxDefinitionLevel(path(fieldType.getName())) -
1;
+ newFields.add(ParquetValueReaders.option(fieldType, fieldD,
fieldReaders.get(i)));
+ types.add(fieldType);
+ }
+
+ return new RowDataReader(types, newFields);
+ }
+ }
+
+ private static class ReadBuilder extends
TypeWithSchemaVisitor<ParquetValueReader<?>> {
+ private final MessageType type;
+ private final Map<Integer, ?> idToConstant;
+
+ ReadBuilder(MessageType type, Map<Integer, ?> idToConstant) {
+ this.type = type;
+ this.idToConstant = idToConstant;
+ }
+
+ @Override
+ public ParquetValueReader<?> message(Types.StructType expected,
MessageType message,
+ List<ParquetValueReader<?>>
fieldReaders) {
+ return struct(expected, message.asGroupType(), fieldReaders);
+ }
+
+ @Override
+ public ParquetValueReader<?> struct(Types.StructType expected, GroupType
struct,
+ List<ParquetValueReader<?>>
fieldReaders) {
+ // match the expected struct's order
+ Map<Integer, ParquetValueReader<?>> readersById = Maps.newHashMap();
+ Map<Integer, Type> typesById = Maps.newHashMap();
+ List<Type> fields = struct.getFields();
+ for (int i = 0; i < fields.size(); i += 1) {
+ Type fieldType = fields.get(i);
+ int fieldD = type.getMaxDefinitionLevel(path(fieldType.getName())) - 1;
+ if (fieldType.getId() != null) {
+ int id = fieldType.getId().intValue();
+ readersById.put(id, ParquetValueReaders.option(fieldType, fieldD,
fieldReaders.get(i)));
+ typesById.put(id, fieldType);
+ }
+ }
+
+ List<Types.NestedField> expectedFields = expected != null ?
+ expected.fields() : ImmutableList.of();
+ List<ParquetValueReader<?>> reorderedFields =
Lists.newArrayListWithExpectedSize(
+ expectedFields.size());
+ List<Type> types =
Lists.newArrayListWithExpectedSize(expectedFields.size());
+ for (Types.NestedField field : expectedFields) {
+ int id = field.fieldId();
+ if (idToConstant.containsKey(id)) {
+ // containsKey is used because the constant may be null
+
reorderedFields.add(ParquetValueReaders.constant(idToConstant.get(id)));
+ types.add(null);
+ } else {
+ ParquetValueReader<?> reader = readersById.get(id);
+ if (reader != null) {
+ reorderedFields.add(reader);
+ types.add(typesById.get(id));
+ } else {
+ reorderedFields.add(ParquetValueReaders.nulls());
+ types.add(null);
+ }
+ }
+ }
+
+ return new RowDataReader(types, reorderedFields);
+ }
+
+ @Override
+ public ParquetValueReader<?> list(Types.ListType expectedList, GroupType
array,
+ ParquetValueReader<?> elementReader) {
+ GroupType repeated = array.getFields().get(0).asGroupType();
+ String[] repeatedPath = currentPath();
+
+ int repeatedD = type.getMaxDefinitionLevel(repeatedPath) - 1;
+ int repeatedR = type.getMaxRepetitionLevel(repeatedPath) - 1;
+
+ Type elementType = repeated.getType(0);
+ int elementD = type.getMaxDefinitionLevel(path(elementType.getName())) -
1;
+
+ return new ArrayReader<>(repeatedD, repeatedR,
ParquetValueReaders.option(elementType, elementD, elementReader));
+ }
+
+ @Override
+ public ParquetValueReader<?> map(Types.MapType expectedMap, GroupType map,
+ ParquetValueReader<?> keyReader,
+ ParquetValueReader<?> valueReader) {
+ GroupType repeatedKeyValue = map.getFields().get(0).asGroupType();
+ String[] repeatedPath = currentPath();
+
+ int repeatedD = type.getMaxDefinitionLevel(repeatedPath) - 1;
+ int repeatedR = type.getMaxRepetitionLevel(repeatedPath) - 1;
+
+ Type keyType = repeatedKeyValue.getType(0);
+ int keyD = type.getMaxDefinitionLevel(path(keyType.getName())) - 1;
+ Type valueType = repeatedKeyValue.getType(1);
+ int valueD = type.getMaxDefinitionLevel(path(valueType.getName())) - 1;
+
+ return new MapReader<>(repeatedD, repeatedR,
+ ParquetValueReaders.option(keyType, keyD, keyReader),
+ ParquetValueReaders.option(valueType, valueD, valueReader));
+ }
+
+ @Override
+ public ParquetValueReader<?>
primitive(org.apache.iceberg.types.Type.PrimitiveType expected,
+ PrimitiveType primitive) {
+ ColumnDescriptor desc = type.getColumnDescription(currentPath());
+
+ if (primitive.getOriginalType() != null) {
+ switch (primitive.getOriginalType()) {
+ case ENUM:
+ case JSON:
+ case UTF8:
+ return new StringReader(desc);
+ case INT_8:
+ case INT_16:
+ case INT_32:
+ case TIME_MICROS:
Review comment:
According to the table on #1215, a time should be in milliseconds.
Because Parquet stores the time in micros for TIME_MICROS, this will need a
converter.
@JingsongLi, how should we handle lossy conversions to Flink types?
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