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https://issues.apache.org/jira/browse/FLINK-37300?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated FLINK-37300:
-----------------------------------
Labels: pull-request-available (was: )
> Add database native type information to Column struct to generate ddl
> correctly
> -------------------------------------------------------------------------------
>
> Key: FLINK-37300
> URL: https://issues.apache.org/jira/browse/FLINK-37300
> Project: Flink
> Issue Type: Improvement
> Components: Flink CDC
> Reporter: He Wang
> Assignee: He Wang
> Priority: Major
> Labels: pull-request-available
>
> Many data types in the database do not have a one-to-one correspondence with
> the data types in Flink. So to ensure that the data types on the source and
> sink sides match accurately, we need to add the column type information in
> the database to the Column struct.
> We can introduce new structs like below to represent data types in data
> sources.
> {code:java}
> /** Describes the raw data type in data sources. */
> public interface RawDataType extends Serializable {} {code}
> {code:java}
> /** Describes the raw data type in jdbc data sources. */
> public class JdbcRawDataType implements RawDataType {
> private static final long serialVersionUID = 1L;
> private final int jdbcType;
> private final String typeName;
> private final int length;
> private final Integer scale;
> public JdbcRawDataType(int jdbcType, String typeName, int length, Integer
> scale) {
> this.jdbcType = jdbcType;
> this.typeName = typeName;
> this.length = length;
> this.scale = scale;
> }
> /** Returns the {@link java.sql.Types}. */
> public int getJdbcType() {
> return jdbcType;
> }
> /** Returns the type name. */
> public String getTypeName() {
> return typeName;
> }
> /** Returns the maximum length. For numeric data types, this represents
> the precision. */
> public int getLength() {
> return length;
> }
> /** Returns the scale. */
> public Integer getScale() {
> return scale;
> }
> } {code}
> Then I thought we could add RawDataType as a new field of
> org.apache.flink.cdc.common.types.DataType and set that field when
> instantiating SchemaChangeEvent so that we can get the type in the passed
> schema.
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