Hi zhisheng,
目前 kafka source & jdbc sink 都是用的 TypeInformation ，所以都只能声明成 38, 18 或者直接写
DECIMAL ，默认就是 38, 18。
这个问题会在升级到 new source/sink interface （FLIP-95）后有效解决。
Best,
Jark
On Thu, 19 Mar 2020 at 10:31, zhisheng <zhisheng2...@gmail.com> wrote:
> hi, Jark
>
> 我只是使用了 flink-jdbc 这个 connector，发下我本地测试的 DDL 和 SQL 如下：
>
> String ddlSource = "CREATE TABLE test (\n" +
> " yidun_score numeric(5, 2)\n" +
> ") WITH (\n" +
> " 'connector.type' = 'kafka',\n" +
> " 'connector.version' = '0.11',\n" +
> " 'connector.topic' = 'test',\n" +
> " 'connector.startup-mode' = 'latest-offset',\n" +
> " 'connector.properties.zookeeper.connect' =
> 'localhost:2181',\n" +
> " 'connector.properties.bootstrap.servers' =
> 'localhost:9092',\n" +
> " 'format.type' = 'json'\n" +
> ")";
>
> String ddlSink = "CREATE TABLE test_aggregate (\n" +
> " yidun_score numeric(5, 2)\n" +
> ") WITH (\n" +
> " 'connector.type' = 'jdbc',\n" +
> " 'connector.driver' = 'org.postgresql.Driver',\n" +
> " 'connector.url' =
> 'jdbc:postgresql://localhost:3600/test',\n" +
> " 'connector.table' = 'test_aggregate', \n" +
> " 'connector.username' = 'admin', \n" +
> " 'connector.password' = '1234546',\n" +
> " 'connector.write.flush.max-rows' = '1' \n" +
> ")";
>
> String sql = "insert into test_aggregate select yidun_score from
> test";
>
> blinkStreamTableEnv.sqlUpdate(ddlSource);
> blinkStreamTableEnv.sqlUpdate(ddlSink);
> blinkStreamTableEnv.sqlUpdate(sql);
>
> 没有自定义过 TableSink
>
>
>
> Jark Wu <imj...@gmail.com> 于2020年3月19日周四 上午9:43写道：
>
> > Hi zhisheng,
> >
> > 我猜测你的 TableSink 的实现用了 legacy type, i.e. TypeInformation， 而不是 DataType。
> > legacy type 是无法表达精度的，所以只能 mapping 到默认的 38, 18 上。
> > 这是框架做的一个合法性校验。
> >
> > Best,
> > Jark
> >
> > On Thu, 19 Mar 2020 at 09:33, zhisheng <zhisheng2...@gmail.com> wrote:
> >
> > > hi, Jark
> > >
> > > 我刚使用 1.10.0 测试，报错异常如下：
> > >
> > > Exception in thread "main"
> > org.apache.flink.table.api.ValidationException:
> > > Type DECIMAL(5, 2) of table field 'yidun_score' does not match with the
> > > physical type LEGACY('DECIMAL', 'DECIMAL') of the 'yidun_score' field
> of
> > > the TableSink consumed type.
> > > at
> > >
> > >
> >
> org.apache.flink.table.utils.TypeMappingUtils.lambda$checkPhysicalLogicalTypeCompatible$4(TypeMappingUtils.java:164)
> > > at
> > >
> > >
> >
> org.apache.flink.table.utils.TypeMappingUtils$1.visit(TypeMappingUtils.java:265)
> > > at
> > >
> > >
> >
> org.apache.flink.table.utils.TypeMappingUtils$1.visit(TypeMappingUtils.java:254)
> > > at
> > >
> > >
> >
> org.apache.flink.table.types.logical.LegacyTypeInformationType.accept(LegacyTypeInformationType.java:102)
> > > at
> > >
> > >
> >
> org.apache.flink.table.utils.TypeMappingUtils.checkIfCompatible(TypeMappingUtils.java:254)
> > > at
> > >
> > >
> >
> org.apache.flink.table.utils.TypeMappingUtils.checkPhysicalLogicalTypeCompatible(TypeMappingUtils.java:160)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.sinks.TableSinkUtils$$anonfun$validateLogicalPhysicalTypesCompatible$1.apply$mcVI$sp(TableSinkUtils.scala:287)
> > > at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.sinks.TableSinkUtils$.validateLogicalPhysicalTypesCompatible(TableSinkUtils.scala:280)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:194)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:190)
> > > at scala.Option.map(Option.scala:146)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase.translateToRel(PlannerBase.scala:190)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:150)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:150)
> > > at
> > >
> > >
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> > > at
> > >
> > >
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> > > at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> > > at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
> > > at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> > > at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
> > > at
> scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> > > at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> > > at
> > >
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:150)
> > > at
> > >
> > >
> >
> org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:682)
> > > at
> > >
> > >
> >
> org.apache.flink.table.api.internal.TableEnvironmentImpl.sqlUpdate(TableEnvironmentImpl.java:495)
> > > at com.zhisheng.sql.blink.stream.example.Test.main(Test.java:49)
> > > Caused by: org.apache.flink.table.api.ValidationException: Legacy
> decimal
> > > type can only be mapped to DECIMAL(38, 18).
> > > ... 26 more
> > >
> > > 看报错日志像是只能使用 DECIMAL(38, 18)，不然映射会失败，然后我将表定义成 DECIMAL(38, 18) 类型，就不报错了。
> > >
> > > 看了下源码是 TypeMappingUtils 类中的 checkIfCompatible 做了校验
> > >
> > >
> http://zhisheng-blog.oss-cn-hangzhou.aliyuncs.com/2020-03-19-012349.png
> > >
> > > 看了下这个 private 方法的上层是 checkPhysicalLogicalTypeCompatible 方法，这个方法的注释说：
> > >
> > > Checks whether the given physical field type and logical field type are
> > > compatible at the edges of the table ecosystem. Types are still
> > compatible
> > > if the physical type is a legacy decimal type (converted from
> > > Types#BIG_DEC) and the logical type is DECIMAL(38, 18). This is to
> > support
> > > legacy TypeInformation for TableSource and TableSink.
> > >
> > > 看起来像是在兼容旧的 TypeInformation
> > >
> > > zhisheng <zhisheng2...@gmail.com> 于2020年3月19日周四 上午8:31写道：
> > >
> > > > 对的，这是生产的一个 1.9 blink planner 作业，今天我测试一下 1.10 blink planner
> > > >
> > > > Jark Wu <imj...@gmail.com> 于2020年3月18日周三 下午11:47写道：
> > > >
> > > >> Hi zhisheng,
> > > >>
> > > >> 你用的是1.9吗？ 试过 1.10.0 blink planner 么？
> > > >>
> > > >> On Wed, 18 Mar 2020 at 22:21, zhisheng <zhisheng2...@gmail.com>
> > wrote:
> > > >>
> > > >> > hi, all
> > > >> >
> > > >> > 我定义的一个表的一个字段（yidun_score）是 numeric(5,2) 类型，写入 PostgreSQL 的 DDL
> > > >> yidun_score
> > > >> > 字段也是定义的 numeric(5,2) 类型，结果会报异常。
> > > >> >
> > > >> > org.apache.flink.client.program.ProgramInvocationException: The
> main
> > > >> method
> > > >> > caused an error: Field types of query result and registered
> > TableSink
> > > >> > [Result] do not match.
> > > >> > Query result schema: [user_new_id: Long, total_credit_score:
> > Integer,
> > > >> > total_order_count: Integer, loss_total_order_count: Integer,
> > > >> yidun_score:
> > > >> > BigDecimal, is_delete: Boolean]
> > > >> > TableSink schema: [user_new_id: Long, total_credit_score:
> > Integer,
> > > >> > total_order_count: Integer, loss_total_order_count: Integer,
> > > >> yidun_score:
> > > >> > BigDecimal, is_delete: Boolean]
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.program.PackagedProgram.callMainMethod(PackagedProgram.java:593)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.program.PackagedProgram.invokeInteractiveModeForExecution(PackagedProgram.java:438)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.program.OptimizerPlanEnvironment.getOptimizedPlan(OptimizerPlanEnvironment.java:83)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.program.PackagedProgramUtils.createJobGraph(PackagedProgramUtils.java:80)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.program.PackagedProgramUtils.createJobGraph(PackagedProgramUtils.java:122)
> > > >> > at
> > > >>
> > org.apache.flink.client.cli.CliFrontend.runProgram(CliFrontend.java:227)
> > > >> > at
> org.apache.flink.client.cli.CliFrontend.run(CliFrontend.java:205)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.cli.CliFrontend.parseParameters(CliFrontend.java:1010)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.client.cli.CliFrontend.lambda$main$10(CliFrontend.java:1083)
> > > >> > at java.security.AccessController.doPrivileged(Native Method)
> > > >> > at javax.security.auth.Subject.doAs(Subject.java:422)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.runtime.security.HadoopSecurityContext.runSecured(HadoopSecurityContext.java:41)
> > > >> > at
> > org.apache.flink.client.cli.CliFrontend.main(CliFrontend.java:1083)
> > > >> > Caused by: org.apache.flink.table.api.ValidationException: Field
> > types
> > > >> of
> > > >> > query result and registered TableSink [Result] do not match.
> > > >> > Query result schema: [user_new_id: Long, total_credit_score:
> > Integer,
> > > >> > total_order_count: Integer, loss_total_order_count: Integer,
> > > >> yidun_score:
> > > >> > BigDecimal, is_delete: Boolean]
> > > >> > TableSink schema: [user_new_id: Long, total_credit_score:
> > Integer,
> > > >> > total_order_count: Integer, loss_total_order_count: Integer,
> > > >> yidun_score:
> > > >> > BigDecimal, is_delete: Boolean]
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.sinks.TableSinkUtils$.validateSink(TableSinkUtils.scala:69)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:179)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:178)
> > > >> > at scala.Option.map(Option.scala:146)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase.translateToRel(PlannerBase.scala:178)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:146)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:146)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> > > >> > at
> > > >> >
> > > >> >
> > > >>
> > >
> >
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> > > >> > at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> > > >> >
> > > >> > 我后面把 numeric(5,2) 类型都改成 double，结果发现就不报异常了，可以正常将数据写入 PG，不知道这个 case
> > > 是不是一个
> > > >> > bug？
> > > >> >
> > > >>
> > > >
> > >
> >
>
