hi、 好吧，测试发现Decimal用不了，即使是DECIMAL(38, 18)，换成其他类型就好了，不知道是不是bug [image: image.png]
On Fri, Mar 20, 2020 at 2:17 PM 宇张 <[email protected]> wrote: > hi，我这面再次进行了尝试，当json数据中有数字类型的时候，即使按照将 data 的schema定义需要改成 > ARRAY(ROW(...)) > 另外删除 > .jsonSchema(...)后，程序仍然无法运行，当没有数字类型的时候是可以的；而报错信息输出来看，这两个结构是对的上的，但是貌似校验未通过 > [image: image.png] > > > On Fri, Mar 20, 2020 at 12:08 PM 宇张 <[email protected]> wrote: > >> hi， >> 好的，我这面进行了尝试，将 data 的schema定义需要改成 >> ARRAY(ROW(FIELD("tracking_numbrer", STRING), FIELD("invoice_no", STRING))) >> 另外删除 .jsonSchema(...)后，程序数据解析已经没问题了；但是如果保留 >> .jsonSchema(...)的话会抛出如下异常信息：Exception in thread "main" >> org.apache.flink.table.api.ValidationException: Type >> ARRAY<ROW<`tracking_number` STRING, `invoice_no` STRING>> of table field >> 'data' does not match with the physical type ROW<`f0` ROW<`tracking_number` >> STRING, `invoice_no` STRING>> of the 'data' field of the TableSource return >> type. >> >> 而之所以保留这个jsonschema是因为我想尝试将这种复杂的json源的元数据保存到hive，进而通过这种方式推断出下面语句的格式，因为我不知道对于上述的复杂json在定义下面sql的时候字段信息怎么映射，或者说有这种复杂json的sql映射案例吗，感谢 >> [image: image.png] >> >> On Fri, Mar 20, 2020 at 11:42 AM Jark Wu <[email protected]> wrote: >> >>> Hi, >>> >>> 看了你的数据，"data" 是一个 array<row> 的类型，所以 data 的schema定义需要改成 >>> ARRAY(ROW(FIELD("tracking_numbrer", STRING), FIELD("invoice_no", >>> STRING))) >>> 另外建议删除 .jsonSchema(...)， 1.10 开始 flink-json 已经支持自动从 table schema 中推断 json >>> schema 了。 >>> >>> Best, >>> Jark >>> >>> On Fri, 20 Mar 2020 at 11:34, 宇张 <[email protected]> wrote: >>> >>> > hi： >>> > 1、在Json数据解析的时候，请问这里面为什么用的是decimal，而不是bigint >>> > [image: image.png] >>> > 2、我在使用connect的时候，发现解析Json数组元素出现异常，这是误用导致的还是一个bug >>> > >>> > >>> json：{"business":"riskt","data":[{"tracking_number":"0180024020920","invoice_no":"2020021025"}],"database":"installmentdb","table":"t_sales_order","ts":1581576074069,"type":"UPDATE","putRowNum":19999} >>> > >>> > >>> jsonSchema：{"type":"object","properties":{"business":{"type":"string"},"data":{"type":"array","items":[{"type":"object","properties":{"tracking_number":{"type":"string"},"invoice_no":{"type":"string"}}}]},"database":{"type":"string"},"table":{"type":"string"},"ts":{"type":"integer"},"type":{"type":"string"},"putRowNum":{"type":"integer"}}} >>> > connect： >>> > >>> > streamTableEnv >>> > .connect( >>> > new Kafka() >>> > .version("0.11") >>> > .topic("mysql_binlog_test_str") >>> > .startFromEarliest() >>> > .property("zookeeper.connect", >>> "localhost:2181") >>> > .property("bootstrap.servers", >>> "localhost:9092") >>> > ) >>> > .withFormat( >>> > new Json() >>> > >>> >>> .jsonSchema("{\"type\":\"object\",\"properties\":{\"business\":{\"type\":\"string\"},\"data\":{\"type\":\"array\",\"items\":[{\"type\":\"object\",\"properties\":{\"tracking_number\":{\"type\":\"string\"},\"invoice_no\":{\"type\":\"string\"}}}]},\"database\":{\"type\":\"string\"},\"table\":{\"type\":\"string\"},\"ts\":{\"type\":\"integer\"},\"type\":{\"type\":\"string\"},\"putRowNum\":{\"type\":\"integer\"}}}") >>> > ) >>> > .withSchema( >>> > new Schema() >>> > .field("business", DataTypes.STRING()) >>> > .field("data", >>> DataTypes.ROW(DataTypes.FIELD("f0", DataTypes.ROW( >>> > DataTypes.FIELD("tracking_number", >>> DataTypes.STRING()), >>> > DataTypes.FIELD("invoice_no", >>> DataTypes.STRING()))))) >>> > .field("database", DataTypes.STRING()) >>> > .field("table", DataTypes.STRING()) >>> > .field("ts", DataTypes.DECIMAL(38, 18)) >>> > .field("type", DataTypes.STRING()) >>> > .field("putRowNum", DataTypes.DECIMAL(38, 18)) >>> > ) >>> > .createTemporaryTable("Test"); >>> > >>> > 异常信息：Caused by: java.io.IOException: Failed to deserialize JSON object. >>> > >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:133) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:76) >>> > at >>> > >>> org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:45) >>> > at >>> > >>> org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:146) >>> > at >>> > >>> org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:715) >>> > at >>> > >>> org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:100) >>> > at >>> > >>> org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:63) >>> > at >>> > >>> org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:196) >>> > Caused by: java.lang.ClassCastException: >>> > >>> org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ArrayNode >>> > cannot be cast to >>> > >>> org.apache.flink.shaded.jackson2.com.fasterxml.jackson.databind.node.ObjectNode >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$assembleRowConverter$77f7700$1(JsonRowDeserializationSchema.java:411) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:236) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.convertField(JsonRowDeserializationSchema.java:439) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$assembleRowConverter$77f7700$1(JsonRowDeserializationSchema.java:418) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:236) >>> > at >>> > >>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:131) >>> > ... 7 more >>> > >>> > >>> > >>> >>
