[
https://issues.apache.org/jira/browse/FLINK-20370?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Jark Wu updated FLINK-20370:
----------------------------
Description:
Both sources are upsert-kafka which synchronizes the changes from MySQL tables
(source_city, source_customer). The sink is another MySQL table which is in
upsert mode with "city_name" primary key. The join key is "city_id".
In this case, the result will be wrong when updating {{source_city.city_name}}
column in MySQL, as the UPDATE_BEFORE is ignored and the old city_name is
retained in the sink table.
{code}
Sink(table=[default_catalog.default_database.sink_kafka_count_city],
fields=[city_name, count_customer, sum_gender], changelogMode=[NONE])
+- Calc(select=[city_name, CAST(count_customer) AS count_customer,
CAST(sum_gender) AS sum_gender], changelogMode=[I,UA,D])
+- Join(joinType=[InnerJoin], where=[=(city_id, id)], select=[city_id,
count_customer, sum_gender, id, city_name],
leftInputSpec=[JoinKeyContainsUniqueKey],
rightInputSpec=[JoinKeyContainsUniqueKey], changelogMode=[I,UA,D])
:- Exchange(distribution=[hash[city_id]], changelogMode=[I,UA,D])
: +- GlobalGroupAggregate(groupBy=[city_id], select=[city_id,
COUNT_RETRACT(count1$0) AS count_customer, SUM_RETRACT((sum$1, count$2)) AS
sum_gender], changelogMode=[I,UA,D])
: +- Exchange(distribution=[hash[city_id]], changelogMode=[I])
: +- LocalGroupAggregate(groupBy=[city_id], select=[city_id,
COUNT_RETRACT(*) AS count1$0, SUM_RETRACT(gender) AS (sum$1, count$2)],
changelogMode=[I])
: +- Calc(select=[city_id, gender], changelogMode=[I,UB,UA,D])
: +- ChangelogNormalize(key=[customer_id],
changelogMode=[I,UB,UA,D])
: +- Exchange(distribution=[hash[customer_id]],
changelogMode=[UA,D])
: +- MiniBatchAssigner(interval=[3000ms],
mode=[ProcTime], changelogMode=[UA,D])
: +- TableSourceScan(table=[[default_catalog,
default_database, source_customer]], fields=[customer_id, city_id, age, gender,
update_time], changelogMode=[UA,D])
+- Exchange(distribution=[hash[id]], changelogMode=[I,UA,D])
+- ChangelogNormalize(key=[id], changelogMode=[I,UA,D])
+- Exchange(distribution=[hash[id]], changelogMode=[UA,D])
+- MiniBatchAssigner(interval=[3000ms], mode=[ProcTime],
changelogMode=[UA,D])
+- TableSourceScan(table=[[default_catalog, default_database,
source_city]], fields=[id, city_name], changelogMode=[UA,D])
{code}
We have suggested users to use the same key of the query as the primary key on
sink in the documentation:
https://ci.apache.org/projects/flink/flink-docs-master/dev/table/sql/queries.html#deduplication.
We should make this attention to be more highlight in CREATE TABLE page.
was:
Both sources are upsert-kafka which synchronizes the changes from MySQL tables
(source_city, source_customer). The sink is another MySQL table which is in
upsert mode with "city_name" primary key. The join key is "city_id".
In this case, the result will be wrong when updating {{source_city.city_name}}
column in MySQL, as the UPDATE_BEFORE is ignored and the old city_name is
retained in the sink table.
{code}
Sink(table=[default_catalog.default_database.sink_kafka_count_city],
fields=[city_name, count_customer, sum_gender], changelogMode=[NONE])
+- Calc(select=[city_name, CAST(count_customer) AS count_customer,
CAST(sum_gender) AS sum_gender], changelogMode=[I,UA,D])
+- Join(joinType=[InnerJoin], where=[=(city_id, id)], select=[city_id,
count_customer, sum_gender, id, city_name],
leftInputSpec=[JoinKeyContainsUniqueKey],
rightInputSpec=[JoinKeyContainsUniqueKey], changelogMode=[I,UA,D])
:- Exchange(distribution=[hash[city_id]], changelogMode=[I,UA,D])
: +- GlobalGroupAggregate(groupBy=[city_id], select=[city_id,
COUNT_RETRACT(count1$0) AS count_customer, SUM_RETRACT((sum$1, count$2)) AS
sum_gender], changelogMode=[I,UA,D])
: +- Exchange(distribution=[hash[city_id]], changelogMode=[I])
: +- LocalGroupAggregate(groupBy=[city_id], select=[city_id,
COUNT_RETRACT(*) AS count1$0, SUM_RETRACT(gender) AS (sum$1, count$2)],
changelogMode=[I])
: +- Calc(select=[city_id, gender], changelogMode=[I,UB,UA,D])
: +- ChangelogNormalize(key=[customer_id],
changelogMode=[I,UB,UA,D])
: +- Exchange(distribution=[hash[customer_id]],
changelogMode=[UA,D])
: +- MiniBatchAssigner(interval=[3000ms],
mode=[ProcTime], changelogMode=[UA,D])
: +- TableSourceScan(table=[[default_catalog,
default_database, source_customer]], fields=[customer_id, city_id, age, gender,
update_time], changelogMode=[UA,D])
+- Exchange(distribution=[hash[id]], changelogMode=[I,UA,D])
+- ChangelogNormalize(key=[id], changelogMode=[I,UA,D])
+- Exchange(distribution=[hash[id]], changelogMode=[UA,D])
+- MiniBatchAssigner(interval=[3000ms], mode=[ProcTime],
changelogMode=[UA,D])
+- TableSourceScan(table=[[default_catalog, default_database,
source_city]], fields=[id, city_name], changelogMode=[UA,D])
{code}
> Result is wrong when sink primary key is not the same with query
> ----------------------------------------------------------------
>
> Key: FLINK-20370
> URL: https://issues.apache.org/jira/browse/FLINK-20370
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / Planner
> Affects Versions: 1.12.0
> Reporter: Jark Wu
> Priority: Major
>
> Both sources are upsert-kafka which synchronizes the changes from MySQL
> tables (source_city, source_customer). The sink is another MySQL table which
> is in upsert mode with "city_name" primary key. The join key is "city_id".
> In this case, the result will be wrong when updating
> {{source_city.city_name}} column in MySQL, as the UPDATE_BEFORE is ignored
> and the old city_name is retained in the sink table.
> {code}
> Sink(table=[default_catalog.default_database.sink_kafka_count_city],
> fields=[city_name, count_customer, sum_gender], changelogMode=[NONE])
> +- Calc(select=[city_name, CAST(count_customer) AS count_customer,
> CAST(sum_gender) AS sum_gender], changelogMode=[I,UA,D])
> +- Join(joinType=[InnerJoin], where=[=(city_id, id)], select=[city_id,
> count_customer, sum_gender, id, city_name],
> leftInputSpec=[JoinKeyContainsUniqueKey],
> rightInputSpec=[JoinKeyContainsUniqueKey], changelogMode=[I,UA,D])
> :- Exchange(distribution=[hash[city_id]], changelogMode=[I,UA,D])
> : +- GlobalGroupAggregate(groupBy=[city_id], select=[city_id,
> COUNT_RETRACT(count1$0) AS count_customer, SUM_RETRACT((sum$1, count$2)) AS
> sum_gender], changelogMode=[I,UA,D])
> : +- Exchange(distribution=[hash[city_id]], changelogMode=[I])
> : +- LocalGroupAggregate(groupBy=[city_id], select=[city_id,
> COUNT_RETRACT(*) AS count1$0, SUM_RETRACT(gender) AS (sum$1, count$2)],
> changelogMode=[I])
> : +- Calc(select=[city_id, gender], changelogMode=[I,UB,UA,D])
> : +- ChangelogNormalize(key=[customer_id],
> changelogMode=[I,UB,UA,D])
> : +- Exchange(distribution=[hash[customer_id]],
> changelogMode=[UA,D])
> : +- MiniBatchAssigner(interval=[3000ms],
> mode=[ProcTime], changelogMode=[UA,D])
> : +- TableSourceScan(table=[[default_catalog,
> default_database, source_customer]], fields=[customer_id, city_id, age,
> gender, update_time], changelogMode=[UA,D])
> +- Exchange(distribution=[hash[id]], changelogMode=[I,UA,D])
> +- ChangelogNormalize(key=[id], changelogMode=[I,UA,D])
> +- Exchange(distribution=[hash[id]], changelogMode=[UA,D])
> +- MiniBatchAssigner(interval=[3000ms], mode=[ProcTime],
> changelogMode=[UA,D])
> +- TableSourceScan(table=[[default_catalog,
> default_database, source_city]], fields=[id, city_name], changelogMode=[UA,D])
> {code}
> We have suggested users to use the same key of the query as the primary key
> on sink in the documentation:
> https://ci.apache.org/projects/flink/flink-docs-master/dev/table/sql/queries.html#deduplication.
> We should make this attention to be more highlight in CREATE TABLE page.
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