wuchong commented on a change in pull request #11962: URL: https://github.com/apache/flink/pull/11962#discussion_r418128626
########## File path: flink-formats/flink-csv/src/main/java/org/apache/flink/formats/csv/CsvRowDataSerializationSchema.java ########## @@ -0,0 +1,377 @@ +/* + * 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.csv; + +import org.apache.flink.annotation.PublicEvolving; +import org.apache.flink.api.common.serialization.SerializationSchema; +import org.apache.flink.table.data.ArrayData; +import org.apache.flink.table.data.DecimalData; +import org.apache.flink.table.data.RowData; +import org.apache.flink.table.data.TimestampData; +import org.apache.flink.table.types.logical.ArrayType; +import org.apache.flink.table.types.logical.LogicalType; +import org.apache.flink.table.types.logical.RowType; +import org.apache.flink.util.Preconditions; + +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.JsonNode; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.ObjectWriter; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ArrayNode; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ContainerNode; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.dataformat.csv.CsvMapper; +import org.apache.flink.shaded.jackson2.com.fasterxml.jackson.dataformat.csv.CsvSchema; + +import java.io.Serializable; +import java.math.BigDecimal; +import java.time.LocalDate; +import java.time.LocalTime; +import java.time.format.DateTimeFormatter; +import java.time.format.DateTimeFormatterBuilder; +import java.util.Arrays; +import java.util.Objects; + +import static java.time.format.DateTimeFormatter.ISO_LOCAL_DATE; +import static java.time.format.DateTimeFormatter.ISO_LOCAL_TIME; + +/** + * Serialization schema that serializes an object of Flink Table & SQL internal data structure + * into a CSV bytes. + * + * <p>Serializes the input row into a {@link JsonNode} and + * converts it into <code>byte[]</code>. + * + * <p>Result <code>byte[]</code> messages can be deserialized using {@link CsvRowDataDeserializationSchema}. + */ +@PublicEvolving +public final class CsvRowDataSerializationSchema implements SerializationSchema<RowData> { + + private static final long serialVersionUID = 1L; + + /** Logical row type describing the input CSV data. */ + private final RowType rowType; + + /** Runtime instance that performs the actual work. */ + private final SerializationRuntimeConverter runtimeConverter; + + /** CsvMapper used to write {@link JsonNode} into bytes. */ + private final CsvMapper csvMapper; + + /** Schema describing the input CSV data. */ + private final CsvSchema csvSchema; + + /** Object writer used to write rows. It is configured by {@link CsvSchema}. */ + private final ObjectWriter objectWriter; + + /** Reusable object node. */ + private transient ObjectNode root; + + private CsvRowDataSerializationSchema( + RowType rowType, + CsvSchema csvSchema) { + this.rowType = rowType; + this.runtimeConverter = createRowConverter(rowType, true); + this.csvMapper = new CsvMapper(); + this.csvSchema = csvSchema; + this.objectWriter = csvMapper.writer(csvSchema); + } + + /** + * A builder for creating a {@link CsvRowDataSerializationSchema}. + */ + @PublicEvolving + public static class Builder { + + private final RowType rowType; + private CsvSchema csvSchema; + + /** + * Creates a {@link CsvRowDataSerializationSchema} expecting the given {@link RowType}. + * + * @param rowType logical row type used to create schema. + */ + public Builder(RowType rowType) { + Preconditions.checkNotNull(rowType, "Row type must not be null."); + + this.rowType = rowType; + this.csvSchema = CsvRowSchemaConverter.convert(rowType); + } + + public Builder setFieldDelimiter(char c) { + this.csvSchema = this.csvSchema.rebuild().setColumnSeparator(c).build(); + return this; + } + + public Builder setLineDelimiter(String delimiter) { + Preconditions.checkNotNull(delimiter, "Delimiter must not be null."); + if (!delimiter.equals("\n") && !delimiter.equals("\r") && !delimiter.equals("\r\n") && !delimiter.equals("")) { + throw new IllegalArgumentException( + "Unsupported new line delimiter. Only \\n, \\r, \\r\\n, or empty string are supported."); + } + this.csvSchema = this.csvSchema.rebuild().setLineSeparator(delimiter).build(); + return this; + } + + public Builder setArrayElementDelimiter(String delimiter) { + Preconditions.checkNotNull(delimiter, "Delimiter must not be null."); + this.csvSchema = this.csvSchema.rebuild().setArrayElementSeparator(delimiter).build(); + return this; + } + + public Builder disableQuoteCharacter() { + this.csvSchema = this.csvSchema.rebuild().disableQuoteChar().build(); + return this; + } + + public Builder setQuoteCharacter(char c) { + this.csvSchema = this.csvSchema.rebuild().setQuoteChar(c).build(); + return this; + } + + public Builder setEscapeCharacter(char c) { + this.csvSchema = this.csvSchema.rebuild().setEscapeChar(c).build(); + return this; + } + + public Builder setNullLiteral(String s) { + this.csvSchema = this.csvSchema.rebuild().setNullValue(s).build(); + return this; + } + + public CsvRowDataSerializationSchema build() { + return new CsvRowDataSerializationSchema( + rowType, + csvSchema); + } + } + + @Override + public byte[] serialize(RowData row) { + if (root == null) { + root = csvMapper.createObjectNode(); + } + try { + runtimeConverter.convert(csvMapper, root, row); + return objectWriter.writeValueAsBytes(root); + } catch (Throwable t) { + throw new RuntimeException("Could not serialize row '" + row + "'.", t); + } + } + + @Override + public boolean equals(Object o) { + if (o == null || o.getClass() != this.getClass()) { + return false; + } + if (this == o) { + return true; + } + final CsvRowDataSerializationSchema that = (CsvRowDataSerializationSchema) o; + final CsvSchema otherSchema = that.csvSchema; + + return rowType.equals(that.rowType) && + csvSchema.getColumnSeparator() == otherSchema.getColumnSeparator() && + Arrays.equals(csvSchema.getLineSeparator(), otherSchema.getLineSeparator()) && + csvSchema.getArrayElementSeparator().equals(otherSchema.getArrayElementSeparator()) && + csvSchema.getQuoteChar() == otherSchema.getQuoteChar() && + csvSchema.getEscapeChar() == otherSchema.getEscapeChar() && + Arrays.equals(csvSchema.getNullValue(), otherSchema.getNullValue()); + } + + @Override + public int hashCode() { + return Objects.hash( + rowType, + csvSchema.getColumnSeparator(), + csvSchema.getLineSeparator(), + csvSchema.getArrayElementSeparator(), + csvSchema.getQuoteChar(), + csvSchema.getEscapeChar(), + csvSchema.getNullValue()); + } + + // -------------------------------------------------------------------------------- + // Runtime Converters + // -------------------------------------------------------------------------------- + + /** + * Runtime converter that converts objects of Flink Table & SQL internal data structures + * to corresponding {@link JsonNode}s. + */ + private interface SerializationRuntimeConverter extends Serializable { Review comment: Or do you mean accessing fields of RowData using getters instead of `RowData.get` utiltiy? I thought about this, but due to we don't have `TypedGetters` interface for `RowData` and `ArrayData`, we have to implement two writers for each type. You can have a look at `org.apache.flink.table.runtime.arrow.writers.IntWriter`. This will be much more complex and we should come up with an idea how to reduce duplicate code. So I think that can be a future work. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
