Hi Rex, the connector expects a value without a schema, but the message contains a schema. You can tell Flink that the schema is included as written in the documentation [1].
CREATE TABLE topic_products ( -- schema is totally the same to the MySQL "products" table id BIGINT, name STRING, description STRING, weight DECIMAL(10, 2)) WITH ( 'connector' = 'kafka', 'topic' = 'products_binlog', 'properties.bootstrap.servers' = 'localhost:9092', 'properties.group.id' = 'testGroup', 'format' = 'debezium-json', 'debezium-json.schema-include' = true) @Jark Wu <imj...@gmail.com> , it would be probably good to make the connector more robust and catch these types of misconfigurations. [1] https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/table/connectors/formats/debezium.html#how-to-use-debezium-format On Fri, Aug 28, 2020 at 11:56 PM Rex Fenley <r...@remind101.com> wrote: > Awesome, so that took me a step further. When running i'm receiving an > error however. FYI, my docker-compose file is based on the Debezium mysql > tutorial which can be found here > https://debezium.io/documentation/reference/1.2/tutorial.html > > Part of the stack trace: > > flink-jobmanager_1 | Caused by: java.io.IOException: Corrupt Debezium > JSON message > '{"schema":{"type":"struct","fields":[{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"int32","optional":false,"field":"customer_id"},{"type":"string","optional":false,"field":"street"},{"type":"string","optional":false,"field":"city"},{"type":"string","optional":false,"field":"state"},{"type":"string","optional":false,"field":"zip"},{"type":"string","optional":false,"name":"io.debezium.data.Enum","version":1,"parameters":{"allowed":"SHIPPING,BILLING,LIVING"},"field":"type"}],"optional":true,"name":"dbserver1.inventory.addresses.Value","field":"before"},{"type":"struct","fields":[{"type":"int32","optional":false,"field":"id"},{"type":"int32","optional":false,"field":"customer_id"},{"type":"string","optional":false,"field":"street"},{"type":"string","optional":false,"field":"city"},{"type":"string","optional":false,"field":"state"},{"type":"string","optional":false,"field":"zip"},{"type":"string","optional":false,"name":"io.debezium.data.Enum","version":1,"parameters":{"allowed":"SHIPPING,BILLING,LIVING"},"field":"type"}],"optional":true,"name":"dbserver1.inventory.addresses.Value","field":"after"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"version"},{"type":"string","optional":false,"field":"connector"},{"type":"string","optional":false,"field":"name"},{"type":"int64","optional":false,"field":"ts_ms"},{"type":"string","optional":true,"name":"io.debezium.data.Enum","version":1,"parameters":{"allowed":"true,last,false"},"default":"false","field":"snapshot"},{"type":"string","optional":false,"field":"db"},{"type":"string","optional":true,"field":"table"},{"type":"int64","optional":false,"field":"server_id"},{"type":"string","optional":true,"field":"gtid"},{"type":"string","optional":false,"field":"file"},{"type":"int64","optional":false,"field":"pos"},{"type":"int32","optional":false,"field":"row"},{"type":"int64","optional":true,"field":"thread"},{"type":"string","optional":true,"field":"query"}],"optional":false,"name":"io.debezium.connector.mysql.Source","field":"source"},{"type":"string","optional":false,"field":"op"},{"type":"int64","optional":true,"field":"ts_ms"},{"type":"struct","fields":[{"type":"string","optional":false,"field":"id"},{"type":"int64","optional":false,"field":"total_order"},{"type":"int64","optional":false,"field":"data_collection_order"}],"optional":true,"field":"transaction"}],"optional":false,"name":"dbserver1.inventory.addresses.Envelope"},"payload":{"before":null,"after":{"id":18,"customer_id":1004,"street":"111 > cool street","city":"Big > City","state":"California","zip":"90000","type":"BILLING"},"source":{"version":"1.2.1.Final","connector":"mysql","name":"dbserver1","ts_ms":1598651432000,"snapshot":"false","db":"inventory","table":"addresses","server_id":223344,"gtid":null,"file":"mysql-bin.000010","pos":369,"row":0,"thread":5,"query":null},"op":"c","ts_ms":1598651432407,"transaction":null}}'. > flink-jobmanager_1 | at > org.apache.flink.formats.json.debezium.DebeziumJsonDeserializationSchema.deserialize(DebeziumJsonDeserializationSchema.java:136) > ~[flink-json-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:56) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.partitionConsumerRecordsHandler(KafkaFetcher.java:181) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.runFetchLoop(KafkaFetcher.java:141) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:755) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:100) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:63) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:201) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > flink-jobmanager_1 | Caused by: java.lang.NullPointerException > flink-jobmanager_1 | at > org.apache.flink.formats.json.debezium.DebeziumJsonDeserializationSchema.deserialize(DebeziumJsonDeserializationSchema.java:115) > ~[flink-json-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:56) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.partitionConsumerRecordsHandler(KafkaFetcher.java:181) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.runFetchLoop(KafkaFetcher.java:141) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:755) > ~[?:?] > flink-jobmanager_1 | at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:100) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:63) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > flink-jobmanager_1 | at > org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:201) > ~[flink-dist_2.12-1.11.1.jar:1.11.1] > > On Thu, Aug 27, 2020 at 8:12 PM Jark Wu <imj...@gmail.com> wrote: > >> Hi, >> >> This is a known issue in 1.11.0, and has been fixed in 1.11.1. >> >> >> Best, >> Jark >> >> On Fri, 28 Aug 2020 at 06:52, Rex Fenley <r...@remind101.com> wrote: >> >>> Hi again! >>> >>> I'm tested out locally in docker on Flink 1.11 first to get my bearings >>> before downgrading to 1.10 and figuring out how to replace the Debezium >>> connector. However, I'm getting the following error >>> ``` >>> Provided trait [BEFORE_AND_AFTER] can't satisfy required trait >>> [ONLY_UPDATE_AFTER]. This is a bug in planner, please file an issue. >>> ``` >>> >>> Any suggestions for me to fix this? >>> >>> code: >>> >>> val bsEnv = StreamExecutionEnvironment.getExecutionEnvironment >>> val blinkStreamSettings = >>> EnvironmentSettings >>> .newInstance() >>> .useBlinkPlanner() >>> .inStreamingMode() >>> .build() >>> val tableEnv = StreamTableEnvironment.create(bsEnv, blinkStreamSettings) >>> >>> // Table from Debezium mysql example docker: >>> // >>> +-------------+-------------------------------------+------+-----+---------+----------------+ >>> // | Field | Type | Null | Key | Default | Extra | >>> // >>> +-------------+-------------------------------------+------+-----+---------+----------------+ >>> // | id | int(11) | NO | PRI | NULL | auto_increment | >>> // | customer_id | int(11) | NO | MUL | NULL | | >>> // | street | varchar(255) | NO | | NULL | | >>> // | city | varchar(255) | NO | | NULL | | >>> // | state | varchar(255) | NO | | NULL | | >>> // | zip | varchar(255) | NO | | NULL | | >>> // | type | enum('SHIPPING','BILLING','LIVING') | NO | | NULL | | >>> // >>> +-------------+-------------------------------------+------+-----+---------+----------------+ >>> >>> tableEnv.executeSql(""" >>> CREATE TABLE topic_addresses ( >>> -- schema is totally the same to the MySQL "addresses" table >>> id INT, >>> customer_id INT, >>> street STRING, >>> city STRING, >>> state STRING, >>> zip STRING, >>> type STRING, >>> PRIMARY KEY (id) NOT ENFORCED >>> ) WITH ( >>> 'connector' = 'kafka', >>> 'topic' = 'dbserver1.inventory.addresses', >>> 'properties.bootstrap.servers' = 'flink-jdbc-test_kafka_1:9092', >>> 'properties.group.id' = 'testGroup', >>> 'format' = 'debezium-json' -- using debezium-json as the format >>> ) >>> """) >>> >>> val table = tableEnv.from("topic_addresses").select($"*") >>> >>> // Defining a PK automatically puts it in Upsert mode, which we want. >>> // TODO: type should be a keyword, is that acceptable by the DDL? >>> tableEnv.executeSql(""" >>> CREATE TABLE ESAddresses ( >>> id INT, >>> customer_id INT, >>> street STRING, >>> city STRING, >>> state STRING, >>> zip STRING, >>> type STRING, >>> PRIMARY KEY (id) NOT ENFORCED >>> ) WITH ( >>> 'connector' = 'elasticsearch-7', >>> 'hosts' = 'http://flink-jdbc-test_graph-elasticsearch_1:9200', >>> 'index' = 'flinkaddresses', >>> 'format' = 'json' >>> ) >>> """) >>> >>> table.executeInsert("ESAddresses").print() >>> >>> Thanks! >>> >>> On Thu, Aug 27, 2020 at 11:53 AM Rex Fenley <r...@remind101.com> wrote: >>> >>>> Thanks! >>>> >>>> On Thu, Aug 27, 2020 at 5:33 AM Jark Wu <imj...@gmail.com> wrote: >>>> >>>>> Hi, >>>>> >>>>> Regarding the performance difference, the proposed way will have one >>>>> more stateful operator (deduplication) than the native 1.11 cdc support. >>>>> The overhead of the deduplication operator is just similar to a simple >>>>> group by aggregate (max on each non-key column). >>>>> >>>>> Best, >>>>> Jark >>>>> >>>>> On Tue, 25 Aug 2020 at 02:21, Rex Fenley <r...@remind101.com> wrote: >>>>> >>>>>> Thank you so much for the help! >>>>>> >>>>>> On Mon, Aug 24, 2020 at 4:08 AM Marta Paes Moreira < >>>>>> ma...@ververica.com> wrote: >>>>>> >>>>>>> Yes — you'll get the full row in the payload; and you can also >>>>>>> access the change operation, which might be useful in your case. >>>>>>> >>>>>>> About performance, I'm summoning Kurt and @Jark Wu <j...@apache.org> to >>>>>>> the thread, who will be able to give you a more complete answer and >>>>>>> likely >>>>>>> also some optimization tips for your specific use case. >>>>>>> >>>>>>> Marta >>>>>>> >>>>>>> On Fri, Aug 21, 2020 at 8:55 PM Rex Fenley <r...@remind101.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Yup! This definitely helps and makes sense. >>>>>>>> >>>>>>>> The 'after' payload comes with all data from the row right? So >>>>>>>> essentially inserts and updates I can insert/replace data by pk and >>>>>>>> null >>>>>>>> values I just delete by pk, and then I can build out the rest of my >>>>>>>> joins >>>>>>>> like normal. >>>>>>>> >>>>>>>> Are there any performance implications of doing it this way that is >>>>>>>> different from the out-of-the-box 1.11 solution? >>>>>>>> >>>>>>>> On Fri, Aug 21, 2020 at 2:28 AM Marta Paes Moreira < >>>>>>>> ma...@ververica.com> wrote: >>>>>>>> >>>>>>>>> Hi, Rex. >>>>>>>>> >>>>>>>>> Part of what enabled CDC support in Flink 1.11 was the refactoring >>>>>>>>> of the table source interfaces (FLIP-95 [1]), and the new >>>>>>>>> ScanTableSource >>>>>>>>> [2], which allows to emit bounded/unbounded streams with insert, >>>>>>>>> update and >>>>>>>>> delete rows. >>>>>>>>> >>>>>>>>> In theory, you could consume data generated with Debezium as >>>>>>>>> regular JSON-encoded events before Flink 1.11 — there just wasn't a >>>>>>>>> convenient way to really treat it as "changelog". As a workaround, >>>>>>>>> what you >>>>>>>>> can do in Flink 1.10 is process these messages as JSON and extract the >>>>>>>>> "after" field from the payload, and then apply de-duplication [3] to >>>>>>>>> keep >>>>>>>>> only the last row. >>>>>>>>> >>>>>>>>> The DDL for your source table would look something like: >>>>>>>>> >>>>>>>>> CREATE TABLE tablename ( *... * after ROW(`field1` DATATYPE, >>>>>>>>> `field2` DATATYPE, ...) ) WITH ( 'connector' = 'kafka', 'format' = >>>>>>>>> 'json', ... ); >>>>>>>>> Hope this helps! >>>>>>>>> >>>>>>>>> Marta >>>>>>>>> >>>>>>>>> [1] >>>>>>>>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-95%3A+New+TableSource+and+TableSink+interfaces >>>>>>>>> [2] >>>>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.11/api/java/org/apache/flink/table/connector/source/ScanTableSource.html >>>>>>>>> [3] >>>>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.10/dev/table/sql/queries.html#deduplication >>>>>>>>> >>>>>>>>> >>>>>>>>> On Fri, Aug 21, 2020 at 10:28 AM Chesnay Schepler < >>>>>>>>> ches...@apache.org> wrote: >>>>>>>>> >>>>>>>>>> @Jark Would it be possible to use the 1.11 debezium support in >>>>>>>>>> 1.10? >>>>>>>>>> >>>>>>>>>> On 20/08/2020 19:59, Rex Fenley wrote: >>>>>>>>>> >>>>>>>>>> Hi, >>>>>>>>>> >>>>>>>>>> I'm trying to set up Flink with Debezium CDC Connector on AWS >>>>>>>>>> EMR, however, EMR only supports Flink 1.10.0, whereas Debezium >>>>>>>>>> Connector >>>>>>>>>> arrived in Flink 1.11.0, from looking at the documentation. >>>>>>>>>> >>>>>>>>>> https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-flink.html >>>>>>>>>> >>>>>>>>>> https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/table/connectors/formats/debezium.html >>>>>>>>>> >>>>>>>>>> I'm wondering what alternative solutions are available for >>>>>>>>>> connecting Debezium to Flink? Is there an open source Debezium >>>>>>>>>> connector >>>>>>>>>> that works with Flink 1.10.0? Could I potentially pull the code out >>>>>>>>>> for the >>>>>>>>>> 1.11.0 Debezium connector and compile it in my project using Flink >>>>>>>>>> 1.10.0 >>>>>>>>>> api? >>>>>>>>>> >>>>>>>>>> For context, I plan on doing some fairly complicated long lived >>>>>>>>>> stateful joins / materialization using the Table API over data >>>>>>>>>> ingested >>>>>>>>>> from Postgres and possibly MySQL. >>>>>>>>>> >>>>>>>>>> Appreciate any help, thanks! >>>>>>>>>> >>>>>>>>>> -- >>>>>>>>>> >>>>>>>>>> Rex Fenley | Software Engineer - Mobile and Backend >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> Remind.com <https://www.remind.com/> | BLOG >>>>>>>>>> <http://blog.remind.com/> | FOLLOW US >>>>>>>>>> <https://twitter.com/remindhq> | LIKE US >>>>>>>>>> <https://www.facebook.com/remindhq> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>> >>>>>>>> -- >>>>>>>> >>>>>>>> Rex Fenley | Software Engineer - Mobile and Backend >>>>>>>> >>>>>>>> >>>>>>>> Remind.com <https://www.remind.com/> | BLOG >>>>>>>> <http://blog.remind.com/> | FOLLOW US >>>>>>>> <https://twitter.com/remindhq> | LIKE US >>>>>>>> <https://www.facebook.com/remindhq> >>>>>>>> >>>>>>> >>>>>> >>>>>> -- >>>>>> >>>>>> Rex Fenley | Software Engineer - Mobile and Backend >>>>>> >>>>>> >>>>>> Remind.com <https://www.remind.com/> | BLOG >>>>>> <http://blog.remind.com/> | FOLLOW US >>>>>> <https://twitter.com/remindhq> | LIKE US >>>>>> <https://www.facebook.com/remindhq> >>>>>> >>>>> >>>> >>>> -- >>>> >>>> Rex Fenley | Software Engineer - Mobile and Backend >>>> >>>> >>>> Remind.com <https://www.remind.com/> | BLOG <http://blog.remind.com/> >>>> | FOLLOW US <https://twitter.com/remindhq> | LIKE US >>>> <https://www.facebook.com/remindhq> >>>> >>> >>> >>> -- >>> >>> Rex Fenley | Software Engineer - Mobile and Backend >>> >>> >>> Remind.com <https://www.remind.com/> | BLOG <http://blog.remind.com/> >>> | FOLLOW US <https://twitter.com/remindhq> | LIKE US >>> <https://www.facebook.com/remindhq> >>> >> > > -- > > Rex Fenley | Software Engineer - Mobile and Backend > > > Remind.com <https://www.remind.com/> | BLOG <http://blog.remind.com/> | > FOLLOW US <https://twitter.com/remindhq> | LIKE US > <https://www.facebook.com/remindhq> > -- Arvid Heise | Senior Java Developer <https://www.ververica.com/> Follow us @VervericaData -- Join Flink Forward <https://flink-forward.org/> - The Apache Flink Conference Stream Processing | Event Driven | Real Time -- Ververica GmbH | Invalidenstrasse 115, 10115 Berlin, Germany -- Ververica GmbH Registered at Amtsgericht Charlottenburg: HRB 158244 B Managing Directors: Timothy Alexander Steinert, Yip Park Tung Jason, Ji (Toni) Cheng
