wuchong commented on a change in pull request #12133:
URL: https://github.com/apache/flink/pull/12133#discussion_r426121118
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -157,4 +166,118 @@ private AvroSchemaConverter() {
}
throw new IllegalArgumentException("Unsupported Avro type '" +
schema.getType() + "'.");
}
+
+ /**
+ * Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
+ *
+ * @param logicalType logical type
+ * @return Avro's {@link Schema} matching this logical type.
+ */
+ public static Schema convertToSchema(LogicalType logicalType) {
+ return convertToSchema(logicalType, 0);
+ }
+
+ private static Schema convertToSchema(LogicalType logicalType, int
rowTypeCounter) {
+ switch (logicalType.getTypeRoot()) {
+ case NULL:
+ return SchemaBuilder.builder().nullType();
+ case BOOLEAN:
+ return
getNullableBuilder(logicalType).booleanType();
+ case INTEGER:
+ return
getNullableBuilder(logicalType).intType();
+ case BIGINT:
+ return
getNullableBuilder(logicalType).longType();
+ case FLOAT:
+ return
getNullableBuilder(logicalType).floatType();
+ case DOUBLE:
+ return
getNullableBuilder(logicalType).doubleType();
+ case CHAR:
+ case VARCHAR:
+ return
getNullableBuilder(logicalType).stringType();
+ case BINARY:
+ case VARBINARY:
+ return
getNullableBuilder(logicalType).bytesType();
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ // use long to represents Timestamp
+ final TimestampType timestampType =
(TimestampType) logicalType;
+ int precision = timestampType.getPrecision();
+ org.apache.avro.LogicalType avroLogicalType;
+ if (precision == 3) {
Review comment:
`precision <= 3`?
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -157,4 +166,118 @@ private AvroSchemaConverter() {
}
throw new IllegalArgumentException("Unsupported Avro type '" +
schema.getType() + "'.");
}
+
+ /**
+ * Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
+ *
+ * @param logicalType logical type
+ * @return Avro's {@link Schema} matching this logical type.
+ */
+ public static Schema convertToSchema(LogicalType logicalType) {
+ return convertToSchema(logicalType, 0);
+ }
+
+ private static Schema convertToSchema(LogicalType logicalType, int
rowTypeCounter) {
+ switch (logicalType.getTypeRoot()) {
+ case NULL:
+ return SchemaBuilder.builder().nullType();
+ case BOOLEAN:
+ return
getNullableBuilder(logicalType).booleanType();
+ case INTEGER:
+ return
getNullableBuilder(logicalType).intType();
+ case BIGINT:
+ return
getNullableBuilder(logicalType).longType();
+ case FLOAT:
+ return
getNullableBuilder(logicalType).floatType();
+ case DOUBLE:
+ return
getNullableBuilder(logicalType).doubleType();
+ case CHAR:
+ case VARCHAR:
+ return
getNullableBuilder(logicalType).stringType();
+ case BINARY:
+ case VARBINARY:
+ return
getNullableBuilder(logicalType).bytesType();
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ // use long to represents Timestamp
+ final TimestampType timestampType =
(TimestampType) logicalType;
+ int precision = timestampType.getPrecision();
+ org.apache.avro.LogicalType avroLogicalType;
+ if (precision == 3) {
+ avroLogicalType =
LogicalTypes.timestampMillis();
+ } else if (precision == 9) {
Review comment:
`precision <= 6`?
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -157,4 +166,118 @@ private AvroSchemaConverter() {
}
throw new IllegalArgumentException("Unsupported Avro type '" +
schema.getType() + "'.");
}
+
+ /**
+ * Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
+ *
+ * @param logicalType logical type
+ * @return Avro's {@link Schema} matching this logical type.
+ */
+ public static Schema convertToSchema(LogicalType logicalType) {
+ return convertToSchema(logicalType, 0);
+ }
+
+ private static Schema convertToSchema(LogicalType logicalType, int
rowTypeCounter) {
+ switch (logicalType.getTypeRoot()) {
+ case NULL:
+ return SchemaBuilder.builder().nullType();
+ case BOOLEAN:
+ return
getNullableBuilder(logicalType).booleanType();
+ case INTEGER:
+ return
getNullableBuilder(logicalType).intType();
+ case BIGINT:
+ return
getNullableBuilder(logicalType).longType();
+ case FLOAT:
+ return
getNullableBuilder(logicalType).floatType();
+ case DOUBLE:
+ return
getNullableBuilder(logicalType).doubleType();
+ case CHAR:
+ case VARCHAR:
+ return
getNullableBuilder(logicalType).stringType();
+ case BINARY:
+ case VARBINARY:
+ return
getNullableBuilder(logicalType).bytesType();
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ // use long to represents Timestamp
+ final TimestampType timestampType =
(TimestampType) logicalType;
+ int precision = timestampType.getPrecision();
+ org.apache.avro.LogicalType avroLogicalType;
+ if (precision == 3) {
+ avroLogicalType =
LogicalTypes.timestampMillis();
+ } else if (precision == 9) {
+ avroLogicalType =
LogicalTypes.timestampMicros();
+ } else {
+ throw new
IllegalArgumentException("Avro Timestamp does not support Timestamp with
precision: " +
+ precision +
+ ", it only supports precision
of 3 or 9.");
+ }
+ return
avroLogicalType.addToSchema(SchemaBuilder.builder().longType());
+ case DATE:
+ // use int to represents Date
+ return
LogicalTypes.date().addToSchema(SchemaBuilder.builder().intType());
+ case TIME_WITHOUT_TIME_ZONE:
+ // use int to represents Time, we only support
millisecond when deserialization
+ return
LogicalTypes.timeMillis().addToSchema(SchemaBuilder.builder().intType());
+ case DECIMAL:
+ DecimalType decimalType = (DecimalType)
logicalType;
+ // store BigDecimal as byte[]
+ return LogicalTypes
+ .decimal(decimalType.getPrecision(),
decimalType.getScale())
+
.addToSchema(SchemaBuilder.builder().bytesType());
+ case ROW:
+ RowType rowType = (RowType) logicalType;
+ List<String> fieldNames =
rowType.getFieldNames();
+ // we have to make sure the record name is
different in a Schema
+ SchemaBuilder.FieldAssembler<Schema> builder =
SchemaBuilder
+ .builder()
+ .record("row_" + rowTypeCounter)
+ .fields();
+ rowTypeCounter++;
+ for (int i = 0; i < rowType.getFieldCount();
i++) {
+ builder = builder
+ .name(fieldNames.get(i))
+
.type(convertToSchema(rowType.getTypeAt(i), rowTypeCounter))
+ .noDefault();
+ }
+ return builder.endRecord();
+ case MAP:
+ MapType mapType = (MapType) logicalType;
+ if (!hasFamily(mapType.getKeyType(),
LogicalTypeFamily.CHARACTER_STRING)) {
+ throw new IllegalArgumentException(
+ "Avro assumes map keys are
strings, " + mapType.getKeyType() +
+ " type as key type is
not supported.");
+ }
+ return SchemaBuilder
+ .builder()
+ .nullable() // will be UNION of Array
and null
Review comment:
`will be UNION of map and null`?
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDataDeserializationSchema.java
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.flink.formats.avro;
+
+import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.api.common.serialization.DeserializationSchema;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
+import org.apache.flink.formats.avro.utils.MutableByteArrayInputStream;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.GenericArrayData;
+import org.apache.flink.table.data.GenericMapData;
+import org.apache.flink.table.data.GenericRowData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.data.StringData;
+import org.apache.flink.table.data.TimestampData;
+import org.apache.flink.table.types.logical.ArrayType;
+import org.apache.flink.table.types.logical.DecimalType;
+import org.apache.flink.table.types.logical.LogicalType;
+import org.apache.flink.table.types.logical.LogicalTypeFamily;
+import org.apache.flink.table.types.logical.MapType;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.table.types.logical.utils.LogicalTypeChecks;
+import org.apache.flink.table.types.logical.utils.LogicalTypeUtils;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericFixed;
+import org.apache.avro.generic.IndexedRecord;
+import org.apache.avro.io.DatumReader;
+import org.apache.avro.io.Decoder;
+import org.apache.avro.io.DecoderFactory;
+import org.apache.avro.specific.SpecificDatumReader;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeFieldType;
+import org.joda.time.LocalDate;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.lang.reflect.Array;
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+
+/**
+ * Deserialization schema from Avro bytes to {@link RowData}.
+ *
+ * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink
RowData. It converts Avro types
+ * into types that are compatible with Flink's Table & SQL API.
+ *
+ * <p>Projects with Avro records containing logical date/time types need to
add a JodaTime
+ * dependency.
+ *
+ * <p>Note: Changes in this class need to be kept in sync with the
corresponding runtime
+ * class {@link AvroRowDataSerializationSchema} and schema converter {@link
AvroSchemaConverter}.
+ */
+@PublicEvolving
+public class AvroRowDataDeserializationSchema implements
DeserializationSchema<RowData> {
+
+ private static final long serialVersionUID = 1L;
+
+ /**
+ * Used for converting Date type.
+ */
+ private static final int MILLIS_PER_DAY = 86400_000;
+
+ /**
+ * Logical type describing the result type.
+ */
+ private final RowType rowType;
+
+ /**
+ * Type information describing the result type.
+ */
+ private final TypeInformation<RowData> typeInfo;
+
+ /**
+ * Runtime instance that performs the actual work.
+ */
+ private final DeserializationRuntimeConverter runtimeConverter;
+
+ /**
+ * Record to deserialize byte array.
+ */
+ private transient IndexedRecord record;
+
+ /**
+ * Reader that deserializes byte array into a record.
+ */
+ private transient DatumReader<IndexedRecord> datumReader;
+
+ /**
+ * Input stream to read message from.
+ */
+ private transient MutableByteArrayInputStream inputStream;
+
+ /**
+ * Avro decoder that decodes binary data.
+ */
+ private transient Decoder decoder;
+
+ /**
+ * Creates a Avro deserialization schema for the given logical type.
+ *
+ * @param rowType The logical type used to deserialize the data.
+ * @param typeInfo The TypeInformation to be used by {@link
AvroRowDataDeserializationSchema#getProducedType()}.
+ */
+ public AvroRowDataDeserializationSchema(
+ RowType rowType,
+ TypeInformation<RowData> typeInfo) {
+ this.rowType = rowType;
+ this.typeInfo = typeInfo;
+ this.runtimeConverter = createRowConverter(rowType);
+ }
+
+ @Override
+ public void open(InitializationContext context) throws Exception {
+ final Schema schema =
AvroSchemaConverter.convertToSchema(rowType);
+ this.record = new GenericData.Record(schema);
+ this.datumReader = new SpecificDatumReader<>(schema);
+ this.inputStream = new MutableByteArrayInputStream();
+ this.decoder =
DecoderFactory.get().binaryDecoder(this.inputStream, null);
+ }
+
+ @Override
+ public RowData deserialize(byte[] message) throws IOException {
+ try {
+ inputStream.setBuffer(message);
+ record = datumReader.read(record, decoder);
+ return (RowData) runtimeConverter.convert(record);
+ } catch (Exception e) {
+ throw new IOException("Failed to deserialize Avro
record.", e);
+ }
+ }
+
+ @Override
+ public boolean isEndOfStream(RowData nextElement) {
+ return false;
+ }
+
+ @Override
+ public TypeInformation<RowData> getProducedType() {
+ return typeInfo;
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ }
+ if (o == null || getClass() != o.getClass()) {
+ return false;
+ }
+ final AvroRowDataDeserializationSchema that =
(AvroRowDataDeserializationSchema) o;
+ return Objects.equals(rowType, that.rowType) &&
+ Objects.equals(typeInfo, that.typeInfo);
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(rowType, typeInfo);
+ }
+
+ //
-------------------------------------------------------------------------------------
+ // Runtime Converters
+ //
-------------------------------------------------------------------------------------
+
+ /**
+ * Runtime converter that converts Avro data structures into objects of
Flink Table & SQL
+ * internal data structures.
+ */
+ @FunctionalInterface
+ private interface DeserializationRuntimeConverter extends Serializable {
+ Object convert(Object object);
+ }
+
+ private DeserializationRuntimeConverter createRowConverter(RowType
rowType) {
+ final DeserializationRuntimeConverter[] fieldConverters =
rowType.getFields().stream()
+ .map(RowType.RowField::getType)
+ .map(this::createNullableConverter)
+ .toArray(DeserializationRuntimeConverter[]::new);
+ final int arity = rowType.getFieldCount();
+
+ return avroObject -> {
+ IndexedRecord record = (IndexedRecord) avroObject;
+ GenericRowData row = new GenericRowData(arity);
+ for (int i = 0; i < arity; ++i) {
+ row.setField(i,
fieldConverters[i].convert(record.get(i)));
+ }
+ return row;
+ };
+ }
+
+ /**
+ * Creates a runtime converter which is null safe.
+ */
+ private DeserializationRuntimeConverter
createNullableConverter(LogicalType type) {
+ final DeserializationRuntimeConverter converter =
createConverter(type);
+ return avroObject -> {
+ if (avroObject == null) {
+ return null;
+ }
+ return converter.convert(avroObject);
+ };
+ }
+
+ /**
+ * Creates a runtime converter which assuming input object is not null.
+ */
+ private DeserializationRuntimeConverter createConverter(LogicalType
type) {
+ switch (type.getTypeRoot()) {
+ case NULL:
+ return avroObject -> null;
+ case BOOLEAN: // boolean
+ case TINYINT: // short
+ case SMALLINT: // int
+ case INTEGER: // int
+ case INTERVAL_YEAR_MONTH: // long
+ case BIGINT: // long
+ case INTERVAL_DAY_TIME: // long
+ case FLOAT: // float
+ case DOUBLE: // double
+ return avroObject -> avroObject;
+ case DATE:
+ return this::convertToDate;
+ case TIME_WITHOUT_TIME_ZONE:
+ return this::convertToTime;
+ case TIMESTAMP_WITH_TIME_ZONE:
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ return this::convertToTimestamp;
+ case CHAR:
+ case VARCHAR:
+ return avroObject ->
StringData.fromString(avroObject.toString());
+ case BINARY:
+ case VARBINARY:
+ return this::convertToBytes;
+ case DECIMAL:
+ return createDecimalConverter((DecimalType)
type);
+ case ARRAY:
+ return createArrayConverter((ArrayType) type);
+ case ROW:
+ return createRowConverter((RowType) type);
+ case MAP:
+ case MULTISET:
+ return createMapConverter((MapType) type);
+ case RAW:
+ default:
+ throw new
UnsupportedOperationException("Unsupported type: " + type);
+ }
+ }
+
+ private DeserializationRuntimeConverter
createDecimalConverter(DecimalType decimalType) {
+ return avroObject -> {
+ final byte[] bytes;
+ if (avroObject instanceof GenericFixed) {
+ bytes = ((GenericFixed) avroObject).bytes();
+ } else if (avroObject instanceof ByteBuffer) {
+ ByteBuffer byteBuffer = (ByteBuffer) avroObject;
+ bytes = new byte[byteBuffer.remaining()];
+ byteBuffer.get(bytes);
+ } else {
+ bytes = (byte[]) avroObject;
+ }
+ return DecimalData.fromUnscaledBytes(bytes,
decimalType.getPrecision(), decimalType.getScale());
+ };
+ }
+
+ private DeserializationRuntimeConverter createArrayConverter(ArrayType
arrayType) {
+ final DeserializationRuntimeConverter elementConverter =
createNullableConverter(arrayType.getElementType());
+ final Class<?> elementClass =
LogicalTypeUtils.toInternalConversionClass(arrayType.getElementType());
+
+ return avroObject -> {
+ final List<?> list = (List<?>) avroObject;
+ final int length = list.size();
+ final Object[] array = (Object[])
Array.newInstance(elementClass, length);
+ for (int i = 0; i < length; ++i) {
+ array[i] =
elementConverter.convert(list.get(i));
+ }
+ return new GenericArrayData(array);
+ };
+ }
+
+ private DeserializationRuntimeConverter createMapConverter(MapType
mapType) {
+ LogicalType keyType = mapType.getKeyType();
+ if (!LogicalTypeChecks.hasFamily(keyType,
LogicalTypeFamily.CHARACTER_STRING)) {
+ throw new UnsupportedOperationException(
+ "Avro format doesn't support non-string as key
type of map. " +
+ "The map type is: " +
mapType.asSummaryString());
+ }
+ final DeserializationRuntimeConverter keyConverter =
createConverter(keyType);
+ final DeserializationRuntimeConverter valueConverter =
createConverter(mapType.getValueType());
+
+ return avroObject -> {
+ final Map<?, ?> map = (Map<?, ?>) avroObject;
+ Map<Object, Object> result = new HashMap<>();
+ for (Map.Entry<?, ?> entry : map.entrySet()) {
+ Object key =
keyConverter.convert(entry.getKey());
+ Object value =
valueConverter.convert(entry.getValue());
+ result.put(key, value);
+ }
+ return new GenericMapData(result);
+ };
+ }
+
+ private TimestampData convertToTimestamp(Object object) {
+ final long millis;
+ if (object instanceof Long) {
+ millis = (Long) object;
+ } else {
+ // use 'provided' Joda time
+ final DateTime value = (DateTime) object;
+ millis = value.toDate().getTime();
+ }
+ return TimestampData.fromEpochMillis(millis);
+ }
+
+ private int convertToDate(Object object) {
+ final long millis;
+ if (object instanceof Integer) {
+ final Integer value = (Integer) object;
+ millis = (long) value * MILLIS_PER_DAY;
Review comment:
Just return the day value. Don't need to recomute MILLIS_PER_DAY.
##########
File path:
flink-formats/flink-avro/src/test/java/org/apache/flink/formats/avro/AvroRowDataDeSerializationSchemaTest.java
##########
@@ -0,0 +1,155 @@
+/*
+ * 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.flink.formats.avro;
+
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.runtime.typeutils.RowDataTypeInfo;
+import org.apache.flink.table.types.DataType;
+import org.apache.flink.table.types.logical.RowType;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.avro.generic.IndexedRecord;
+import org.apache.avro.io.DatumWriter;
+import org.apache.avro.io.Encoder;
+import org.apache.avro.io.EncoderFactory;
+import org.apache.avro.specific.SpecificDatumWriter;
+import org.junit.Test;
+
+import java.io.ByteArrayOutputStream;
+import java.math.BigDecimal;
+import java.nio.ByteBuffer;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import static org.apache.flink.table.api.DataTypes.ARRAY;
+import static org.apache.flink.table.api.DataTypes.BIGINT;
+import static org.apache.flink.table.api.DataTypes.BOOLEAN;
+import static org.apache.flink.table.api.DataTypes.BYTES;
+import static org.apache.flink.table.api.DataTypes.DATE;
+import static org.apache.flink.table.api.DataTypes.DECIMAL;
+import static org.apache.flink.table.api.DataTypes.DOUBLE;
+import static org.apache.flink.table.api.DataTypes.FIELD;
+import static org.apache.flink.table.api.DataTypes.FLOAT;
+import static org.apache.flink.table.api.DataTypes.INT;
+import static org.apache.flink.table.api.DataTypes.MAP;
+import static org.apache.flink.table.api.DataTypes.ROW;
+import static org.apache.flink.table.api.DataTypes.STRING;
+import static org.apache.flink.table.api.DataTypes.TIME;
+import static org.apache.flink.table.api.DataTypes.TIMESTAMP;
+import static org.junit.Assert.assertArrayEquals;
+
+/**
+ * Test for the Avro serialization and deserialization schema.
+ */
+public class AvroRowDataDeSerializationSchemaTest {
+
+ @Test
+ public void testSerializeDeserialize() throws Exception {
+ final DataType dataType = ROW(
+ FIELD("bool", BOOLEAN()),
+ FIELD("int", INT()),
+ FIELD("bigint", BIGINT()),
+ FIELD("float", FLOAT()),
+ FIELD("double",DOUBLE()),
+ FIELD("name", STRING()),
+ FIELD("bytes", BYTES()),
+ FIELD("decimal", DECIMAL(9, 6)),
+ FIELD("doubles", ARRAY(DOUBLE())),
+ FIELD("time", TIME(0)),
+ FIELD("date", DATE()),
+ FIELD("timestamp3", TIMESTAMP(3)),
+ FIELD("timestamp9", TIMESTAMP(9)),
+ FIELD("map", MAP(STRING(), BIGINT())),
+ FIELD("map2map", MAP(STRING(), MAP(STRING(), INT()))),
+ FIELD("map2array", MAP(STRING(), ARRAY(INT()))));
+ final RowType rowType = (RowType) dataType.getLogicalType();
+ final TypeInformation<RowData> typeInfo = new
RowDataTypeInfo(rowType);
+
+ final Schema schema =
AvroSchemaConverter.convertToSchema(rowType);
+ final GenericRecord record = new GenericData.Record(schema);
+ record.put(0, true);
+ record.put(1, 33);
+ record.put(2, 44L);
+ record.put(3, 12.34F);
+ record.put(4, 23.45);
+ record.put(5, "hello avro");
+ record.put(6, ByteBuffer.wrap(new byte[]{1, 2, 4, 5, 6, 7, 8,
12}));
+
+ ByteBuffer byteBuffer =
ByteBuffer.wrap(DecimalData.fromBigDecimal(
+ BigDecimal.valueOf(123456789, 6), 9, 6)
+ .toUnscaledBytes());
+ record.put(7, byteBuffer);
+
+ List<Double> doubles = new ArrayList<>();
+ doubles.add(1.2);
+ doubles.add(3.4);
+ doubles.add(567.8901);
+ record.put(8, doubles);
+
+ record.put(9, 18397);
+ record.put(10, 10087);
+ record.put(11, 1589530213123L);
+ record.put(12, 1589530213123000000L);
Review comment:
Add some more tests for data from Joda time.
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDataDeserializationSchema.java
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.flink.formats.avro;
+
+import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.api.common.serialization.DeserializationSchema;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
+import org.apache.flink.formats.avro.utils.MutableByteArrayInputStream;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.GenericArrayData;
+import org.apache.flink.table.data.GenericMapData;
+import org.apache.flink.table.data.GenericRowData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.data.StringData;
+import org.apache.flink.table.data.TimestampData;
+import org.apache.flink.table.types.logical.ArrayType;
+import org.apache.flink.table.types.logical.DecimalType;
+import org.apache.flink.table.types.logical.LogicalType;
+import org.apache.flink.table.types.logical.LogicalTypeFamily;
+import org.apache.flink.table.types.logical.MapType;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.table.types.logical.utils.LogicalTypeChecks;
+import org.apache.flink.table.types.logical.utils.LogicalTypeUtils;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericFixed;
+import org.apache.avro.generic.IndexedRecord;
+import org.apache.avro.io.DatumReader;
+import org.apache.avro.io.Decoder;
+import org.apache.avro.io.DecoderFactory;
+import org.apache.avro.specific.SpecificDatumReader;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeFieldType;
+import org.joda.time.LocalDate;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.lang.reflect.Array;
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+
+/**
+ * Deserialization schema from Avro bytes to {@link RowData}.
+ *
+ * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink
RowData. It converts Avro types
+ * into types that are compatible with Flink's Table & SQL API.
+ *
+ * <p>Projects with Avro records containing logical date/time types need to
add a JodaTime
+ * dependency.
+ *
+ * <p>Note: Changes in this class need to be kept in sync with the
corresponding runtime
+ * class {@link AvroRowDataSerializationSchema} and schema converter {@link
AvroSchemaConverter}.
+ */
+@PublicEvolving
+public class AvroRowDataDeserializationSchema implements
DeserializationSchema<RowData> {
+
+ private static final long serialVersionUID = 1L;
+
+ /**
+ * Used for converting Date type.
+ */
+ private static final int MILLIS_PER_DAY = 86400_000;
+
+ /**
+ * Logical type describing the result type.
+ */
+ private final RowType rowType;
+
+ /**
+ * Type information describing the result type.
+ */
+ private final TypeInformation<RowData> typeInfo;
+
+ /**
+ * Runtime instance that performs the actual work.
+ */
+ private final DeserializationRuntimeConverter runtimeConverter;
+
+ /**
+ * Record to deserialize byte array.
+ */
+ private transient IndexedRecord record;
+
+ /**
+ * Reader that deserializes byte array into a record.
+ */
+ private transient DatumReader<IndexedRecord> datumReader;
+
+ /**
+ * Input stream to read message from.
+ */
+ private transient MutableByteArrayInputStream inputStream;
+
+ /**
+ * Avro decoder that decodes binary data.
+ */
+ private transient Decoder decoder;
+
+ /**
+ * Creates a Avro deserialization schema for the given logical type.
+ *
+ * @param rowType The logical type used to deserialize the data.
+ * @param typeInfo The TypeInformation to be used by {@link
AvroRowDataDeserializationSchema#getProducedType()}.
+ */
+ public AvroRowDataDeserializationSchema(
+ RowType rowType,
+ TypeInformation<RowData> typeInfo) {
+ this.rowType = rowType;
+ this.typeInfo = typeInfo;
+ this.runtimeConverter = createRowConverter(rowType);
+ }
+
+ @Override
+ public void open(InitializationContext context) throws Exception {
+ final Schema schema =
AvroSchemaConverter.convertToSchema(rowType);
+ this.record = new GenericData.Record(schema);
+ this.datumReader = new SpecificDatumReader<>(schema);
+ this.inputStream = new MutableByteArrayInputStream();
+ this.decoder =
DecoderFactory.get().binaryDecoder(this.inputStream, null);
+ }
+
+ @Override
+ public RowData deserialize(byte[] message) throws IOException {
+ try {
+ inputStream.setBuffer(message);
+ record = datumReader.read(record, decoder);
+ return (RowData) runtimeConverter.convert(record);
+ } catch (Exception e) {
+ throw new IOException("Failed to deserialize Avro
record.", e);
+ }
+ }
+
+ @Override
+ public boolean isEndOfStream(RowData nextElement) {
+ return false;
+ }
+
+ @Override
+ public TypeInformation<RowData> getProducedType() {
+ return typeInfo;
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ }
+ if (o == null || getClass() != o.getClass()) {
+ return false;
+ }
+ final AvroRowDataDeserializationSchema that =
(AvroRowDataDeserializationSchema) o;
+ return Objects.equals(rowType, that.rowType) &&
+ Objects.equals(typeInfo, that.typeInfo);
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(rowType, typeInfo);
+ }
+
+ //
-------------------------------------------------------------------------------------
+ // Runtime Converters
+ //
-------------------------------------------------------------------------------------
+
+ /**
+ * Runtime converter that converts Avro data structures into objects of
Flink Table & SQL
+ * internal data structures.
+ */
+ @FunctionalInterface
+ private interface DeserializationRuntimeConverter extends Serializable {
+ Object convert(Object object);
+ }
+
+ private DeserializationRuntimeConverter createRowConverter(RowType
rowType) {
+ final DeserializationRuntimeConverter[] fieldConverters =
rowType.getFields().stream()
+ .map(RowType.RowField::getType)
+ .map(this::createNullableConverter)
+ .toArray(DeserializationRuntimeConverter[]::new);
+ final int arity = rowType.getFieldCount();
+
+ return avroObject -> {
+ IndexedRecord record = (IndexedRecord) avroObject;
+ GenericRowData row = new GenericRowData(arity);
+ for (int i = 0; i < arity; ++i) {
+ row.setField(i,
fieldConverters[i].convert(record.get(i)));
+ }
+ return row;
+ };
+ }
+
+ /**
+ * Creates a runtime converter which is null safe.
+ */
+ private DeserializationRuntimeConverter
createNullableConverter(LogicalType type) {
+ final DeserializationRuntimeConverter converter =
createConverter(type);
+ return avroObject -> {
+ if (avroObject == null) {
+ return null;
+ }
+ return converter.convert(avroObject);
+ };
+ }
+
+ /**
+ * Creates a runtime converter which assuming input object is not null.
+ */
+ private DeserializationRuntimeConverter createConverter(LogicalType
type) {
+ switch (type.getTypeRoot()) {
+ case NULL:
+ return avroObject -> null;
+ case BOOLEAN: // boolean
+ case TINYINT: // short
+ case SMALLINT: // int
+ case INTEGER: // int
+ case INTERVAL_YEAR_MONTH: // long
+ case BIGINT: // long
+ case INTERVAL_DAY_TIME: // long
+ case FLOAT: // float
+ case DOUBLE: // double
+ return avroObject -> avroObject;
+ case DATE:
+ return this::convertToDate;
+ case TIME_WITHOUT_TIME_ZONE:
+ return this::convertToTime;
+ case TIMESTAMP_WITH_TIME_ZONE:
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ return this::convertToTimestamp;
+ case CHAR:
+ case VARCHAR:
+ return avroObject ->
StringData.fromString(avroObject.toString());
+ case BINARY:
+ case VARBINARY:
+ return this::convertToBytes;
+ case DECIMAL:
+ return createDecimalConverter((DecimalType)
type);
+ case ARRAY:
+ return createArrayConverter((ArrayType) type);
+ case ROW:
+ return createRowConverter((RowType) type);
+ case MAP:
+ case MULTISET:
+ return createMapConverter((MapType) type);
+ case RAW:
+ default:
+ throw new
UnsupportedOperationException("Unsupported type: " + type);
+ }
+ }
+
+ private DeserializationRuntimeConverter
createDecimalConverter(DecimalType decimalType) {
+ return avroObject -> {
+ final byte[] bytes;
+ if (avroObject instanceof GenericFixed) {
+ bytes = ((GenericFixed) avroObject).bytes();
+ } else if (avroObject instanceof ByteBuffer) {
+ ByteBuffer byteBuffer = (ByteBuffer) avroObject;
+ bytes = new byte[byteBuffer.remaining()];
+ byteBuffer.get(bytes);
+ } else {
+ bytes = (byte[]) avroObject;
+ }
+ return DecimalData.fromUnscaledBytes(bytes,
decimalType.getPrecision(), decimalType.getScale());
+ };
+ }
+
+ private DeserializationRuntimeConverter createArrayConverter(ArrayType
arrayType) {
+ final DeserializationRuntimeConverter elementConverter =
createNullableConverter(arrayType.getElementType());
+ final Class<?> elementClass =
LogicalTypeUtils.toInternalConversionClass(arrayType.getElementType());
+
+ return avroObject -> {
+ final List<?> list = (List<?>) avroObject;
+ final int length = list.size();
+ final Object[] array = (Object[])
Array.newInstance(elementClass, length);
+ for (int i = 0; i < length; ++i) {
+ array[i] =
elementConverter.convert(list.get(i));
+ }
+ return new GenericArrayData(array);
+ };
+ }
+
+ private DeserializationRuntimeConverter createMapConverter(MapType
mapType) {
+ LogicalType keyType = mapType.getKeyType();
+ if (!LogicalTypeChecks.hasFamily(keyType,
LogicalTypeFamily.CHARACTER_STRING)) {
+ throw new UnsupportedOperationException(
+ "Avro format doesn't support non-string as key
type of map. " +
+ "The map type is: " +
mapType.asSummaryString());
+ }
+ final DeserializationRuntimeConverter keyConverter =
createConverter(keyType);
+ final DeserializationRuntimeConverter valueConverter =
createConverter(mapType.getValueType());
+
+ return avroObject -> {
+ final Map<?, ?> map = (Map<?, ?>) avroObject;
+ Map<Object, Object> result = new HashMap<>();
+ for (Map.Entry<?, ?> entry : map.entrySet()) {
+ Object key =
keyConverter.convert(entry.getKey());
+ Object value =
valueConverter.convert(entry.getValue());
+ result.put(key, value);
+ }
+ return new GenericMapData(result);
+ };
+ }
+
+ private TimestampData convertToTimestamp(Object object) {
+ final long millis;
+ if (object instanceof Long) {
+ millis = (Long) object;
+ } else {
+ // use 'provided' Joda time
+ final DateTime value = (DateTime) object;
+ millis = value.toDate().getTime();
+ }
+ return TimestampData.fromEpochMillis(millis);
+ }
+
+ private int convertToDate(Object object) {
+ final long millis;
+ if (object instanceof Integer) {
+ final Integer value = (Integer) object;
+ millis = (long) value * MILLIS_PER_DAY;
+ } else {
+ // use 'provided' Joda time
+ final LocalDate value = (LocalDate) object;
+ millis = value.toDate().getTime();
Review comment:
ditto
```
new java.sql.Date(value.toDate().getTime()).toLocalDate().toEpochDay();
```
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -157,4 +166,118 @@ private AvroSchemaConverter() {
}
throw new IllegalArgumentException("Unsupported Avro type '" +
schema.getType() + "'.");
}
+
+ /**
+ * Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
+ *
+ * @param logicalType logical type
+ * @return Avro's {@link Schema} matching this logical type.
+ */
+ public static Schema convertToSchema(LogicalType logicalType) {
+ return convertToSchema(logicalType, 0);
+ }
+
+ private static Schema convertToSchema(LogicalType logicalType, int
rowTypeCounter) {
+ switch (logicalType.getTypeRoot()) {
+ case NULL:
+ return SchemaBuilder.builder().nullType();
+ case BOOLEAN:
+ return
getNullableBuilder(logicalType).booleanType();
+ case INTEGER:
+ return
getNullableBuilder(logicalType).intType();
+ case BIGINT:
+ return
getNullableBuilder(logicalType).longType();
+ case FLOAT:
+ return
getNullableBuilder(logicalType).floatType();
+ case DOUBLE:
+ return
getNullableBuilder(logicalType).doubleType();
+ case CHAR:
+ case VARCHAR:
+ return
getNullableBuilder(logicalType).stringType();
+ case BINARY:
+ case VARBINARY:
+ return
getNullableBuilder(logicalType).bytesType();
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
Review comment:
We can also support `TIMESTAMP_WITH_LOCAL_TIME_ZONE`. You can add a
`case TIMESTAMP_WITH_LOCAL_TIME_ZONE` along with `TIMESTAMP_WITHOUT_TIME_ZONE`,
then use `LogicalTypeChecks#getPrecision(logiclType)` to get precision.
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -157,4 +166,118 @@ private AvroSchemaConverter() {
}
throw new IllegalArgumentException("Unsupported Avro type '" +
schema.getType() + "'.");
}
+
+ /**
+ * Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
+ *
+ * @param logicalType logical type
+ * @return Avro's {@link Schema} matching this logical type.
+ */
+ public static Schema convertToSchema(LogicalType logicalType) {
+ return convertToSchema(logicalType, 0);
+ }
+
+ private static Schema convertToSchema(LogicalType logicalType, int
rowTypeCounter) {
+ switch (logicalType.getTypeRoot()) {
+ case NULL:
+ return SchemaBuilder.builder().nullType();
+ case BOOLEAN:
+ return
getNullableBuilder(logicalType).booleanType();
+ case INTEGER:
+ return
getNullableBuilder(logicalType).intType();
+ case BIGINT:
+ return
getNullableBuilder(logicalType).longType();
+ case FLOAT:
+ return
getNullableBuilder(logicalType).floatType();
+ case DOUBLE:
+ return
getNullableBuilder(logicalType).doubleType();
+ case CHAR:
+ case VARCHAR:
+ return
getNullableBuilder(logicalType).stringType();
+ case BINARY:
+ case VARBINARY:
+ return
getNullableBuilder(logicalType).bytesType();
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ // use long to represents Timestamp
+ final TimestampType timestampType =
(TimestampType) logicalType;
+ int precision = timestampType.getPrecision();
+ org.apache.avro.LogicalType avroLogicalType;
+ if (precision == 3) {
+ avroLogicalType =
LogicalTypes.timestampMillis();
+ } else if (precision == 9) {
+ avroLogicalType =
LogicalTypes.timestampMicros();
+ } else {
+ throw new
IllegalArgumentException("Avro Timestamp does not support Timestamp with
precision: " +
+ precision +
+ ", it only supports precision
of 3 or 9.");
+ }
+ return
avroLogicalType.addToSchema(SchemaBuilder.builder().longType());
+ case DATE:
+ // use int to represents Date
+ return
LogicalTypes.date().addToSchema(SchemaBuilder.builder().intType());
+ case TIME_WITHOUT_TIME_ZONE:
+ // use int to represents Time, we only support
millisecond when deserialization
+ return
LogicalTypes.timeMillis().addToSchema(SchemaBuilder.builder().intType());
+ case DECIMAL:
+ DecimalType decimalType = (DecimalType)
logicalType;
+ // store BigDecimal as byte[]
+ return LogicalTypes
+ .decimal(decimalType.getPrecision(),
decimalType.getScale())
+
.addToSchema(SchemaBuilder.builder().bytesType());
+ case ROW:
+ RowType rowType = (RowType) logicalType;
+ List<String> fieldNames =
rowType.getFieldNames();
+ // we have to make sure the record name is
different in a Schema
+ SchemaBuilder.FieldAssembler<Schema> builder =
SchemaBuilder
+ .builder()
+ .record("row_" + rowTypeCounter)
+ .fields();
+ rowTypeCounter++;
+ for (int i = 0; i < rowType.getFieldCount();
i++) {
+ builder = builder
+ .name(fieldNames.get(i))
+
.type(convertToSchema(rowType.getTypeAt(i), rowTypeCounter))
+ .noDefault();
+ }
+ return builder.endRecord();
+ case MAP:
Review comment:
Add `MULTIMAP` support?
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDataDeserializationSchema.java
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.flink.formats.avro;
+
+import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.api.common.serialization.DeserializationSchema;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
+import org.apache.flink.formats.avro.utils.MutableByteArrayInputStream;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.GenericArrayData;
+import org.apache.flink.table.data.GenericMapData;
+import org.apache.flink.table.data.GenericRowData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.data.StringData;
+import org.apache.flink.table.data.TimestampData;
+import org.apache.flink.table.types.logical.ArrayType;
+import org.apache.flink.table.types.logical.DecimalType;
+import org.apache.flink.table.types.logical.LogicalType;
+import org.apache.flink.table.types.logical.LogicalTypeFamily;
+import org.apache.flink.table.types.logical.MapType;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.table.types.logical.utils.LogicalTypeChecks;
+import org.apache.flink.table.types.logical.utils.LogicalTypeUtils;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericFixed;
+import org.apache.avro.generic.IndexedRecord;
+import org.apache.avro.io.DatumReader;
+import org.apache.avro.io.Decoder;
+import org.apache.avro.io.DecoderFactory;
+import org.apache.avro.specific.SpecificDatumReader;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeFieldType;
+import org.joda.time.LocalDate;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.lang.reflect.Array;
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+
+/**
+ * Deserialization schema from Avro bytes to {@link RowData}.
+ *
+ * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink
RowData. It converts Avro types
+ * into types that are compatible with Flink's Table & SQL API.
+ *
+ * <p>Projects with Avro records containing logical date/time types need to
add a JodaTime
+ * dependency.
+ *
+ * <p>Note: Changes in this class need to be kept in sync with the
corresponding runtime
+ * class {@link AvroRowDataSerializationSchema} and schema converter {@link
AvroSchemaConverter}.
+ */
+@PublicEvolving
+public class AvroRowDataDeserializationSchema implements
DeserializationSchema<RowData> {
+
+ private static final long serialVersionUID = 1L;
+
+ /**
+ * Used for converting Date type.
+ */
+ private static final int MILLIS_PER_DAY = 86400_000;
+
+ /**
+ * Logical type describing the result type.
+ */
+ private final RowType rowType;
+
+ /**
+ * Type information describing the result type.
+ */
+ private final TypeInformation<RowData> typeInfo;
+
+ /**
+ * Runtime instance that performs the actual work.
+ */
+ private final DeserializationRuntimeConverter runtimeConverter;
+
+ /**
+ * Record to deserialize byte array.
+ */
+ private transient IndexedRecord record;
+
+ /**
+ * Reader that deserializes byte array into a record.
+ */
+ private transient DatumReader<IndexedRecord> datumReader;
+
+ /**
+ * Input stream to read message from.
+ */
+ private transient MutableByteArrayInputStream inputStream;
+
+ /**
+ * Avro decoder that decodes binary data.
+ */
+ private transient Decoder decoder;
+
+ /**
+ * Creates a Avro deserialization schema for the given logical type.
+ *
+ * @param rowType The logical type used to deserialize the data.
+ * @param typeInfo The TypeInformation to be used by {@link
AvroRowDataDeserializationSchema#getProducedType()}.
+ */
+ public AvroRowDataDeserializationSchema(
+ RowType rowType,
+ TypeInformation<RowData> typeInfo) {
+ this.rowType = rowType;
+ this.typeInfo = typeInfo;
+ this.runtimeConverter = createRowConverter(rowType);
+ }
+
+ @Override
+ public void open(InitializationContext context) throws Exception {
+ final Schema schema =
AvroSchemaConverter.convertToSchema(rowType);
+ this.record = new GenericData.Record(schema);
+ this.datumReader = new SpecificDatumReader<>(schema);
+ this.inputStream = new MutableByteArrayInputStream();
+ this.decoder =
DecoderFactory.get().binaryDecoder(this.inputStream, null);
+ }
+
+ @Override
+ public RowData deserialize(byte[] message) throws IOException {
+ try {
+ inputStream.setBuffer(message);
+ record = datumReader.read(record, decoder);
+ return (RowData) runtimeConverter.convert(record);
+ } catch (Exception e) {
+ throw new IOException("Failed to deserialize Avro
record.", e);
+ }
+ }
+
+ @Override
+ public boolean isEndOfStream(RowData nextElement) {
+ return false;
+ }
+
+ @Override
+ public TypeInformation<RowData> getProducedType() {
+ return typeInfo;
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ }
+ if (o == null || getClass() != o.getClass()) {
+ return false;
+ }
+ final AvroRowDataDeserializationSchema that =
(AvroRowDataDeserializationSchema) o;
+ return Objects.equals(rowType, that.rowType) &&
+ Objects.equals(typeInfo, that.typeInfo);
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(rowType, typeInfo);
+ }
+
+ //
-------------------------------------------------------------------------------------
+ // Runtime Converters
+ //
-------------------------------------------------------------------------------------
+
+ /**
+ * Runtime converter that converts Avro data structures into objects of
Flink Table & SQL
+ * internal data structures.
+ */
+ @FunctionalInterface
+ private interface DeserializationRuntimeConverter extends Serializable {
+ Object convert(Object object);
+ }
+
+ private DeserializationRuntimeConverter createRowConverter(RowType
rowType) {
+ final DeserializationRuntimeConverter[] fieldConverters =
rowType.getFields().stream()
+ .map(RowType.RowField::getType)
+ .map(this::createNullableConverter)
+ .toArray(DeserializationRuntimeConverter[]::new);
+ final int arity = rowType.getFieldCount();
+
+ return avroObject -> {
+ IndexedRecord record = (IndexedRecord) avroObject;
+ GenericRowData row = new GenericRowData(arity);
+ for (int i = 0; i < arity; ++i) {
+ row.setField(i,
fieldConverters[i].convert(record.get(i)));
+ }
+ return row;
+ };
+ }
+
+ /**
+ * Creates a runtime converter which is null safe.
+ */
+ private DeserializationRuntimeConverter
createNullableConverter(LogicalType type) {
+ final DeserializationRuntimeConverter converter =
createConverter(type);
+ return avroObject -> {
+ if (avroObject == null) {
+ return null;
+ }
+ return converter.convert(avroObject);
+ };
+ }
+
+ /**
+ * Creates a runtime converter which assuming input object is not null.
+ */
+ private DeserializationRuntimeConverter createConverter(LogicalType
type) {
+ switch (type.getTypeRoot()) {
+ case NULL:
+ return avroObject -> null;
+ case BOOLEAN: // boolean
+ case TINYINT: // short
+ case SMALLINT: // int
+ case INTEGER: // int
+ case INTERVAL_YEAR_MONTH: // long
+ case BIGINT: // long
+ case INTERVAL_DAY_TIME: // long
+ case FLOAT: // float
+ case DOUBLE: // double
+ return avroObject -> avroObject;
+ case DATE:
+ return this::convertToDate;
+ case TIME_WITHOUT_TIME_ZONE:
+ return this::convertToTime;
+ case TIMESTAMP_WITH_TIME_ZONE:
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ return this::convertToTimestamp;
+ case CHAR:
+ case VARCHAR:
+ return avroObject ->
StringData.fromString(avroObject.toString());
+ case BINARY:
+ case VARBINARY:
+ return this::convertToBytes;
+ case DECIMAL:
+ return createDecimalConverter((DecimalType)
type);
+ case ARRAY:
+ return createArrayConverter((ArrayType) type);
+ case ROW:
+ return createRowConverter((RowType) type);
+ case MAP:
+ case MULTISET:
+ return createMapConverter((MapType) type);
+ case RAW:
+ default:
+ throw new
UnsupportedOperationException("Unsupported type: " + type);
+ }
+ }
+
+ private DeserializationRuntimeConverter
createDecimalConverter(DecimalType decimalType) {
+ return avroObject -> {
+ final byte[] bytes;
+ if (avroObject instanceof GenericFixed) {
+ bytes = ((GenericFixed) avroObject).bytes();
+ } else if (avroObject instanceof ByteBuffer) {
+ ByteBuffer byteBuffer = (ByteBuffer) avroObject;
+ bytes = new byte[byteBuffer.remaining()];
+ byteBuffer.get(bytes);
+ } else {
+ bytes = (byte[]) avroObject;
+ }
+ return DecimalData.fromUnscaledBytes(bytes,
decimalType.getPrecision(), decimalType.getScale());
Review comment:
We should avoid depending LogicalType in the hot path (runtime code).
You can get the precision and scale value out of the lambda with `final`
modifier.
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/AvroRowDataDeserializationSchema.java
##########
@@ -0,0 +1,371 @@
+/*
+ * 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.flink.formats.avro;
+
+import org.apache.flink.annotation.PublicEvolving;
+import org.apache.flink.api.common.serialization.DeserializationSchema;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.formats.avro.typeutils.AvroSchemaConverter;
+import org.apache.flink.formats.avro.utils.MutableByteArrayInputStream;
+import org.apache.flink.table.data.DecimalData;
+import org.apache.flink.table.data.GenericArrayData;
+import org.apache.flink.table.data.GenericMapData;
+import org.apache.flink.table.data.GenericRowData;
+import org.apache.flink.table.data.RowData;
+import org.apache.flink.table.data.StringData;
+import org.apache.flink.table.data.TimestampData;
+import org.apache.flink.table.types.logical.ArrayType;
+import org.apache.flink.table.types.logical.DecimalType;
+import org.apache.flink.table.types.logical.LogicalType;
+import org.apache.flink.table.types.logical.LogicalTypeFamily;
+import org.apache.flink.table.types.logical.MapType;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.table.types.logical.utils.LogicalTypeChecks;
+import org.apache.flink.table.types.logical.utils.LogicalTypeUtils;
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericFixed;
+import org.apache.avro.generic.IndexedRecord;
+import org.apache.avro.io.DatumReader;
+import org.apache.avro.io.Decoder;
+import org.apache.avro.io.DecoderFactory;
+import org.apache.avro.specific.SpecificDatumReader;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeFieldType;
+import org.joda.time.LocalDate;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.lang.reflect.Array;
+import java.nio.ByteBuffer;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Objects;
+
+/**
+ * Deserialization schema from Avro bytes to {@link RowData}.
+ *
+ * <p>Deserializes the <code>byte[]</code> messages into (nested) Flink
RowData. It converts Avro types
+ * into types that are compatible with Flink's Table & SQL API.
+ *
+ * <p>Projects with Avro records containing logical date/time types need to
add a JodaTime
+ * dependency.
+ *
+ * <p>Note: Changes in this class need to be kept in sync with the
corresponding runtime
+ * class {@link AvroRowDataSerializationSchema} and schema converter {@link
AvroSchemaConverter}.
+ */
+@PublicEvolving
+public class AvroRowDataDeserializationSchema implements
DeserializationSchema<RowData> {
+
+ private static final long serialVersionUID = 1L;
+
+ /**
+ * Used for converting Date type.
+ */
+ private static final int MILLIS_PER_DAY = 86400_000;
+
+ /**
+ * Logical type describing the result type.
+ */
+ private final RowType rowType;
+
+ /**
+ * Type information describing the result type.
+ */
+ private final TypeInformation<RowData> typeInfo;
+
+ /**
+ * Runtime instance that performs the actual work.
+ */
+ private final DeserializationRuntimeConverter runtimeConverter;
+
+ /**
+ * Record to deserialize byte array.
+ */
+ private transient IndexedRecord record;
+
+ /**
+ * Reader that deserializes byte array into a record.
+ */
+ private transient DatumReader<IndexedRecord> datumReader;
+
+ /**
+ * Input stream to read message from.
+ */
+ private transient MutableByteArrayInputStream inputStream;
+
+ /**
+ * Avro decoder that decodes binary data.
+ */
+ private transient Decoder decoder;
+
+ /**
+ * Creates a Avro deserialization schema for the given logical type.
+ *
+ * @param rowType The logical type used to deserialize the data.
+ * @param typeInfo The TypeInformation to be used by {@link
AvroRowDataDeserializationSchema#getProducedType()}.
+ */
+ public AvroRowDataDeserializationSchema(
+ RowType rowType,
+ TypeInformation<RowData> typeInfo) {
+ this.rowType = rowType;
+ this.typeInfo = typeInfo;
+ this.runtimeConverter = createRowConverter(rowType);
+ }
+
+ @Override
+ public void open(InitializationContext context) throws Exception {
+ final Schema schema =
AvroSchemaConverter.convertToSchema(rowType);
+ this.record = new GenericData.Record(schema);
+ this.datumReader = new SpecificDatumReader<>(schema);
+ this.inputStream = new MutableByteArrayInputStream();
+ this.decoder =
DecoderFactory.get().binaryDecoder(this.inputStream, null);
+ }
+
+ @Override
+ public RowData deserialize(byte[] message) throws IOException {
+ try {
+ inputStream.setBuffer(message);
+ record = datumReader.read(record, decoder);
+ return (RowData) runtimeConverter.convert(record);
+ } catch (Exception e) {
+ throw new IOException("Failed to deserialize Avro
record.", e);
+ }
+ }
+
+ @Override
+ public boolean isEndOfStream(RowData nextElement) {
+ return false;
+ }
+
+ @Override
+ public TypeInformation<RowData> getProducedType() {
+ return typeInfo;
+ }
+
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) {
+ return true;
+ }
+ if (o == null || getClass() != o.getClass()) {
+ return false;
+ }
+ final AvroRowDataDeserializationSchema that =
(AvroRowDataDeserializationSchema) o;
+ return Objects.equals(rowType, that.rowType) &&
+ Objects.equals(typeInfo, that.typeInfo);
+ }
+
+ @Override
+ public int hashCode() {
+ return Objects.hash(rowType, typeInfo);
+ }
+
+ //
-------------------------------------------------------------------------------------
+ // Runtime Converters
+ //
-------------------------------------------------------------------------------------
+
+ /**
+ * Runtime converter that converts Avro data structures into objects of
Flink Table & SQL
+ * internal data structures.
+ */
+ @FunctionalInterface
+ private interface DeserializationRuntimeConverter extends Serializable {
+ Object convert(Object object);
+ }
+
+ private DeserializationRuntimeConverter createRowConverter(RowType
rowType) {
+ final DeserializationRuntimeConverter[] fieldConverters =
rowType.getFields().stream()
+ .map(RowType.RowField::getType)
+ .map(this::createNullableConverter)
+ .toArray(DeserializationRuntimeConverter[]::new);
+ final int arity = rowType.getFieldCount();
+
+ return avroObject -> {
+ IndexedRecord record = (IndexedRecord) avroObject;
+ GenericRowData row = new GenericRowData(arity);
+ for (int i = 0; i < arity; ++i) {
+ row.setField(i,
fieldConverters[i].convert(record.get(i)));
+ }
+ return row;
+ };
+ }
+
+ /**
+ * Creates a runtime converter which is null safe.
+ */
+ private DeserializationRuntimeConverter
createNullableConverter(LogicalType type) {
+ final DeserializationRuntimeConverter converter =
createConverter(type);
+ return avroObject -> {
+ if (avroObject == null) {
+ return null;
+ }
+ return converter.convert(avroObject);
+ };
+ }
+
+ /**
+ * Creates a runtime converter which assuming input object is not null.
+ */
+ private DeserializationRuntimeConverter createConverter(LogicalType
type) {
+ switch (type.getTypeRoot()) {
+ case NULL:
+ return avroObject -> null;
+ case BOOLEAN: // boolean
+ case TINYINT: // short
+ case SMALLINT: // int
+ case INTEGER: // int
+ case INTERVAL_YEAR_MONTH: // long
+ case BIGINT: // long
+ case INTERVAL_DAY_TIME: // long
+ case FLOAT: // float
+ case DOUBLE: // double
+ return avroObject -> avroObject;
+ case DATE:
+ return this::convertToDate;
+ case TIME_WITHOUT_TIME_ZONE:
+ return this::convertToTime;
+ case TIMESTAMP_WITH_TIME_ZONE:
+ case TIMESTAMP_WITHOUT_TIME_ZONE:
+ return this::convertToTimestamp;
+ case CHAR:
+ case VARCHAR:
+ return avroObject ->
StringData.fromString(avroObject.toString());
+ case BINARY:
+ case VARBINARY:
+ return this::convertToBytes;
+ case DECIMAL:
+ return createDecimalConverter((DecimalType)
type);
+ case ARRAY:
+ return createArrayConverter((ArrayType) type);
+ case ROW:
+ return createRowConverter((RowType) type);
+ case MAP:
+ case MULTISET:
+ return createMapConverter((MapType) type);
+ case RAW:
+ default:
+ throw new
UnsupportedOperationException("Unsupported type: " + type);
+ }
+ }
+
+ private DeserializationRuntimeConverter
createDecimalConverter(DecimalType decimalType) {
+ return avroObject -> {
+ final byte[] bytes;
+ if (avroObject instanceof GenericFixed) {
+ bytes = ((GenericFixed) avroObject).bytes();
+ } else if (avroObject instanceof ByteBuffer) {
+ ByteBuffer byteBuffer = (ByteBuffer) avroObject;
+ bytes = new byte[byteBuffer.remaining()];
+ byteBuffer.get(bytes);
+ } else {
+ bytes = (byte[]) avroObject;
+ }
+ return DecimalData.fromUnscaledBytes(bytes,
decimalType.getPrecision(), decimalType.getScale());
+ };
+ }
+
+ private DeserializationRuntimeConverter createArrayConverter(ArrayType
arrayType) {
+ final DeserializationRuntimeConverter elementConverter =
createNullableConverter(arrayType.getElementType());
+ final Class<?> elementClass =
LogicalTypeUtils.toInternalConversionClass(arrayType.getElementType());
+
+ return avroObject -> {
+ final List<?> list = (List<?>) avroObject;
+ final int length = list.size();
+ final Object[] array = (Object[])
Array.newInstance(elementClass, length);
+ for (int i = 0; i < length; ++i) {
+ array[i] =
elementConverter.convert(list.get(i));
+ }
+ return new GenericArrayData(array);
+ };
+ }
+
+ private DeserializationRuntimeConverter createMapConverter(MapType
mapType) {
+ LogicalType keyType = mapType.getKeyType();
+ if (!LogicalTypeChecks.hasFamily(keyType,
LogicalTypeFamily.CHARACTER_STRING)) {
+ throw new UnsupportedOperationException(
+ "Avro format doesn't support non-string as key
type of map. " +
+ "The map type is: " +
mapType.asSummaryString());
+ }
+ final DeserializationRuntimeConverter keyConverter =
createConverter(keyType);
+ final DeserializationRuntimeConverter valueConverter =
createConverter(mapType.getValueType());
+
+ return avroObject -> {
+ final Map<?, ?> map = (Map<?, ?>) avroObject;
+ Map<Object, Object> result = new HashMap<>();
+ for (Map.Entry<?, ?> entry : map.entrySet()) {
+ Object key =
keyConverter.convert(entry.getKey());
+ Object value =
valueConverter.convert(entry.getValue());
+ result.put(key, value);
+ }
+ return new GenericMapData(result);
+ };
+ }
+
+ private TimestampData convertToTimestamp(Object object) {
+ final long millis;
+ if (object instanceof Long) {
+ millis = (Long) object;
+ } else {
+ // use 'provided' Joda time
+ final DateTime value = (DateTime) object;
+ millis = value.toDate().getTime();
Review comment:
This might be not correct, because the `java.util.Date` will use local
time zone.
A simpler way to to this is convert it into sql Timestamp first:
```java
TimestampData.fromTimestamp(new java.sql.Timestamp(value.getMillis());
```
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