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? > > > >> > > > > >> > > > > > > > > > >