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https://issues.apache.org/jira/browse/FLINK-9964?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16580940#comment-16580940
]
ASF GitHub Bot commented on FLINK-9964:
---------------------------------------
buptljy commented on a change in pull request #6541: [FLINK-9964] [table] Add a
CSV table format factory
URL: https://github.com/apache/flink/pull/6541#discussion_r210239352
##########
File path:
flink-formats/flink-csv/src/main/java/org/apache/flink/formats/csv/CsvRowDeserializationSchema.java
##########
@@ -0,0 +1,228 @@
+/*
+ * 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.DeserializationSchema;
+import org.apache.flink.api.common.typeinfo.BasicArrayTypeInfo;
+import org.apache.flink.api.common.typeinfo.PrimitiveArrayTypeInfo;
+import org.apache.flink.api.common.typeinfo.TypeInformation;
+import org.apache.flink.api.common.typeinfo.Types;
+import org.apache.flink.api.java.typeutils.RowTypeInfo;
+import org.apache.flink.types.Row;
+import org.apache.flink.util.Preconditions;
+
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.node.ArrayNode;
+import com.fasterxml.jackson.databind.node.TextNode;
+import com.fasterxml.jackson.dataformat.csv.CsvMapper;
+import com.fasterxml.jackson.dataformat.csv.CsvSchema;
+
+import java.io.IOException;
+import java.io.UnsupportedEncodingException;
+import java.lang.reflect.Array;
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.sql.Date;
+import java.sql.Time;
+import java.sql.Timestamp;
+
+/**
+ * Deserialization schema from CSV to Flink types.
+ *
+ * <p>Deserializes a <code>byte[]</code> message as a {@link JsonNode} and
+ * convert it to {@link Row}.
+ *
+ * <p>Failure during deserialization are forwarded as wrapped IOExceptions.
+ */
+@PublicEvolving
+public class CsvRowDeserializationSchema implements DeserializationSchema<Row>
{
+
+ /** Schema describing the input csv data. */
+ private CsvSchema csvSchema;
+
+ /** Type information describing the input csv data. */
+ private TypeInformation<Row> rowTypeInfo;
+
+ /** CsvMapper used to write {@link JsonNode} into bytes. */
+ private CsvMapper csvMapper = new CsvMapper();
+
+ /** Charset for byte[]. */
+ private String charset = "UTF-8";
+
+
+ /**
+ * Create a csv row DeserializationSchema with given {@link
TypeInformation}.
+ */
+ CsvRowDeserializationSchema(TypeInformation<Row> rowTypeInfo) {
+ Preconditions.checkNotNull(rowTypeInfo, "rowTypeInfo must not
be null !");
+ this.rowTypeInfo = rowTypeInfo;
+ this.csvSchema =
CsvRowSchemaConverter.rowTypeToCsvSchema((RowTypeInfo) rowTypeInfo);
+ }
+
+ @Override
+ public Row deserialize(byte[] message) throws IOException {
+ JsonNode root = csvMapper.readerFor(JsonNode.class)
+ .with(csvSchema).readValue(message);
+ return convertRow(root, (RowTypeInfo) rowTypeInfo);
+ }
+
+ @Override
+ public boolean isEndOfStream(Row nextElement) {
+ return false;
+ }
+
+ @Override
+ public TypeInformation<Row> getProducedType() {
+ return rowTypeInfo;
+ }
+
+ /**
+ *
+ * @param root json node that contains a row's data.
+ * @param rowTypeInfo type information for root.
+ * @return result row
+ */
+ private Row convertRow(JsonNode root, RowTypeInfo rowTypeInfo) {
+ String[] fields = rowTypeInfo.getFieldNames();
+ TypeInformation<?>[] types = rowTypeInfo.getFieldTypes();
+ Row row = new Row(fields.length);
+
+ for (int i = 0; i < fields.length; i++) {
+ String columnName = fields[i];
+ JsonNode node = root.get(columnName);
+ row.setField(i, convert(node, types[i]));
+ }
+ return row;
+ }
+
+ /**
+ *
+ * @param node array node that contains a row's data.
+ * @param rowTypeInfo type information for node.
+ * @return result row
+ */
+ private Row convertRow(ArrayNode node, RowTypeInfo rowTypeInfo) {
+ TypeInformation[] types = rowTypeInfo.getFieldTypes();
+ String[] fields = rowTypeInfo.getFieldNames();
+ Row row = new Row(fields.length);
+ for (int i = 0; i < fields.length; i++) {
+ row.setField(i, convert(node.get(i), types[i]));
+ }
+ return row;
+ }
+
+ /**
+ * Converts json node to object with given type information.
+ * @param node json node to be converted.
+ * @param info type information for the json data.
+ * @return converted object
+ */
+ private Object convert(JsonNode node, TypeInformation<?> info) {
+ if (info == Types.STRING) {
+ return node.asText();
+ } else if (info == Types.LONG) {
+ return node.asLong();
+ } else if (info == Types.INT) {
+ return node.asInt();
+ } else if (info == Types.DOUBLE) {
+ return node.asDouble();
+ } else if (info == Types.FLOAT) {
+ return Double.valueOf(node.asDouble()).floatValue();
Review comment:
No, after we call
```
JsonNode root =
csvMapper.readerFor(JsonNode.class).with(csvSchema).readValue(message)
```
there are only two kinds of JsonNodes left: TextNode and ArrayNode(because
jackson cannot recognize the types from byte array.), and the
textNode.floatValue() will return 0.0f.
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> Add a CSV table format factory
> ------------------------------
>
> Key: FLINK-9964
> URL: https://issues.apache.org/jira/browse/FLINK-9964
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Timo Walther
> Assignee: buptljy
> Priority: Major
> Labels: pull-request-available
>
> We should add a RFC 4180 compliant CSV table format factory to read and write
> data into Kafka and other connectors. This requires a
> {{SerializationSchemaFactory}} and {{DeserializationSchemaFactory}}. How we
> want to represent all data types and nested types is still up for discussion.
> For example, we could flatten and deflatten nested types as it is done
> [here|http://support.gnip.com/articles/json2csv.html]. We can also have a
> look how tools such as the Avro to CSV tool perform the conversion.
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