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Posted to user-zh@flink.apache.org by 曹武 <14...@163.com> on 2020/07/16 12:04:16 UTC
flink 1.11 checkpoint使用
我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
从checkpoint恢复以后,新来op=d的数据会删除失败
重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
.useBlinkPlanner()
.inStreamingMode()
.build();
StreamExecutionEnvironment env =
StreamExecutionEnvironment.getExecutionEnvironment();
env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
最大允许同时出现几个CheckPoint
env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
最小得间隔时间
env.getCheckpointConfig().setPreferCheckpointForRecovery(true); //
是否倾向于用CheckPoint做故障恢复
env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1); //
容忍多少次CheckPoint失败
//Checkpoint文件清理策略
env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
//Checkpoint外部文件路径
env.setStateBackend(new FsStateBackend(new
URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
settings);
String sourceDDL = String.format(
"CREATE TABLE debezium_source (" +
" id INT NOT NULL," +
" name STRING," +
" description STRING," +
" weight Double" +
") WITH (" +
" 'connector' = 'kafka-0.11'," +
" 'topic' = '%s'," +
" 'properties.bootstrap.servers' = '%s'," +
" 'scan.startup.mode' = 'group-offsets'," +
" 'format' = 'debezium-json'" +
")", "ddd", " 172.22.20.206:9092");
String sinkDDL = "CREATE TABLE sink (" +
" id INT NOT NULL," +
" name STRING," +
" description STRING," +
" weight Double," +
" PRIMARY KEY (id,name, description,weight) NOT ENFORCED " +
") WITH (" +
" 'connector' = 'jdbc'," +
" 'url' =
'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
" 'table-name' = 'products'," +
" 'driver'= 'com.mysql.cj.jdbc.Driver'," +
" 'username'='DataPip'," +
" 'password'='DataPip'" +
")";
String dml = "INSERT INTO sink SELECT id,name ,description, weight
FROM debezium_source GROUP BY id,name ,description, weight";
tEnv.executeSql(sourceDDL);
tEnv.executeSql(sinkDDL);
tEnv.executeSql(dml);
--
Sent from: http://apache-flink.147419.n8.nabble.com/
Re: flink 1.11 checkpoint使用
Posted by 曹武 <14...@163.com>.
如果去掉group by会抛出异常,请问有没有关这个异常的解决方式:
Exception in thread "main" org.apache.flink.table.api.TableException:
Provided trait [BEFORE_AND_AFTER] can't satisfy required trait
[ONLY_UPDATE_AFTER]. This is a bug in planner, please file an issue.
Current node is TableSourceScan(table=[[default_catalog, default_database,
ddd]], fields=[id, age])
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.$anonfun$visitChildren$2(FlinkChangelogModeInferenceProgram.scala:626)
at
scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at scala.collection.Iterator.foreach(Iterator.scala:937)
at scala.collection.Iterator.foreach$(Iterator.scala:937)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1425)
at scala.collection.IterableLike.foreach(IterableLike.scala:70)
at scala.collection.IterableLike.foreach$(IterableLike.scala:69)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike.map(TraversableLike.scala:233)
at scala.collection.TraversableLike.map$(TraversableLike.scala:226)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.visitChildren(FlinkChangelogModeInferenceProgram.scala:614)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.$anonfun$visitSink$1(FlinkChangelogModeInferenceProgram.scala:690)
at
scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:240)
godfrey he wrote
> 为什么要 GROUP BY id,name ,description, weight ？
> 直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
> debezium_source" 不能满足需求？
>
> 曹武 <
> 14701319164@
>> 于2020年7月16日周四 下午9:30写道：
>
>> 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
>> 从checkpoint恢复以后,新来op=d的数据会删除失败
>> 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
>>
>> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
>> 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
>> .useBlinkPlanner()
>> .inStreamingMode()
>> .build();
>>
>> StreamExecutionEnvironment env =
>> StreamExecutionEnvironment.getExecutionEnvironment();
>>
>> env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
>> env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
>> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
>> 最大允许同时出现几个CheckPoint
>> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
>> 最小得间隔时间
>> env.getCheckpointConfig().setPreferCheckpointForRecovery(true);
>> //
>> 是否倾向于用CheckPoint做故障恢复
>> env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
>> //
>> 容忍多少次CheckPoint失败
>> //Checkpoint文件清理策略
>>
>>
>> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
>> //Checkpoint外部文件路径
>> env.setStateBackend(new FsStateBackend(new
>> URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
>> TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
>> StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
>> settings);
>> String sourceDDL = String.format(
>> "CREATE TABLE debezium_source (" +
>> " id INT NOT NULL," +
>> " name STRING," +
>> " description STRING," +
>> " weight Double" +
>> ") WITH (" +
>> " 'connector' = 'kafka-0.11'," +
>> " 'topic' = '%s'," +
>> " 'properties.bootstrap.servers' = '%s'," +
>> " 'scan.startup.mode' = 'group-offsets'," +
>> " 'format' = 'debezium-json'" +
>> ")", "ddd", " 172.22.20.206:9092");
>> String sinkDDL = "CREATE TABLE sink (" +
>> " id INT NOT NULL," +
>> " name STRING," +
>> " description STRING," +
>> " weight Double," +
>> " PRIMARY KEY (id,name, description,weight) NOT ENFORCED
>> "
>> +
>> ") WITH (" +
>> " 'connector' = 'jdbc'," +
>> " 'url' =
>> 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
>> " 'table-name' = 'products'," +
>> " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
>> " 'username'='DataPip'," +
>> " 'password'='DataPip'" +
>> ")";
>> String dml = "INSERT INTO sink SELECT id,name ,description,
>> weight
>> FROM debezium_source GROUP BY id,name ,description, weight";
>> tEnv.executeSql(sourceDDL);
>> tEnv.executeSql(sinkDDL);
>> tEnv.executeSql(dml);
>>
>>
>>
>> --
>> Sent from: http://apache-flink.147419.n8.nabble.com/
>>
--
Sent from: http://apache-flink.147419.n8.nabble.com/
Re: flink 1.11 checkpoint使用
Posted by Leonard Xu <xb...@gmail.com>.
Hi， 曹武
这是一个已知bug，这个在1.11.1和1.12.0里已经修复，
如果着急使用，可以自己编译下release-1.11分支。
祝好
Leonard Xu
https://issues.apache.org/jira/browse/FLINK-18461 <https://issues.apache.org/jira/browse/FLINK-18461>
> 在 2020年7月17日，17:12，曹武 <14...@163.com> 写道：
>
> 感觉好像是应为从checkpoint启动失败或者是checkpiont文件里面不包含groupby的中间结果,这个怎么排查呀!
>
> godfrey he wrote
>> 为什么要 GROUP BY id,name ,description, weight ？
>> 直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
>> debezium_source" 不能满足需求？
>>
>> 曹武 <
>
>> 14701319164@
>
>>> 于2020年7月16日周四 下午9:30写道：
>>
>>> 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
>>> 从checkpoint恢复以后,新来op=d的数据会删除失败
>>> 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
>>>
>>> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
>>> 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
>>> .useBlinkPlanner()
>>> .inStreamingMode()
>>> .build();
>>>
>>> StreamExecutionEnvironment env =
>>> StreamExecutionEnvironment.getExecutionEnvironment();
>>>
>>> env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
>>> env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
>>> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
>>> 最大允许同时出现几个CheckPoint
>>> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
>>> 最小得间隔时间
>>> env.getCheckpointConfig().setPreferCheckpointForRecovery(true);
>>> //
>>> 是否倾向于用CheckPoint做故障恢复
>>> env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
>>> //
>>> 容忍多少次CheckPoint失败
>>> //Checkpoint文件清理策略
>>>
>>>
>>> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
>>> //Checkpoint外部文件路径
>>> env.setStateBackend(new FsStateBackend(new
>>> URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
>>> TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
>>> StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
>>> settings);
>>> String sourceDDL = String.format(
>>> "CREATE TABLE debezium_source (" +
>>> " id INT NOT NULL," +
>>> " name STRING," +
>>> " description STRING," +
>>> " weight Double" +
>>> ") WITH (" +
>>> " 'connector' = 'kafka-0.11'," +
>>> " 'topic' = '%s'," +
>>> " 'properties.bootstrap.servers' = '%s'," +
>>> " 'scan.startup.mode' = 'group-offsets'," +
>>> " 'format' = 'debezium-json'" +
>>> ")", "ddd", " 172.22.20.206:9092");
>>> String sinkDDL = "CREATE TABLE sink (" +
>>> " id INT NOT NULL," +
>>> " name STRING," +
>>> " description STRING," +
>>> " weight Double," +
>>> " PRIMARY KEY (id,name, description,weight) NOT ENFORCED
>>> "
>>> +
>>> ") WITH (" +
>>> " 'connector' = 'jdbc'," +
>>> " 'url' =
>>> 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
>>> " 'table-name' = 'products'," +
>>> " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
>>> " 'username'='DataPip'," +
>>> " 'password'='DataPip'" +
>>> ")";
>>> String dml = "INSERT INTO sink SELECT id,name ,description,
>>> weight
>>> FROM debezium_source GROUP BY id,name ,description, weight";
>>> tEnv.executeSql(sourceDDL);
>>> tEnv.executeSql(sinkDDL);
>>> tEnv.executeSql(dml);
>>>
>>>
>>>
>>> --
>>> Sent from: http://apache-flink.147419.n8.nabble.com/
>>>
>
>
>
>
>
> --
> Sent from: http://apache-flink.147419.n8.nabble.com/ <http://apache-flink.147419.n8.nabble.com/>
Re: flink 1.11 checkpoint使用
Posted by 曹武 <14...@163.com>.
感觉好像是应为从checkpoint启动失败或者是checkpiont文件里面不包含groupby的中间结果,这个怎么排查呀!
godfrey he wrote
> 为什么要 GROUP BY id,name ,description, weight ？
> 直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
> debezium_source" 不能满足需求？
>
> 曹武 <
> 14701319164@
>> 于2020年7月16日周四 下午9:30写道：
>
>> 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
>> 从checkpoint恢复以后,新来op=d的数据会删除失败
>> 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
>>
>> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
>> 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
>> .useBlinkPlanner()
>> .inStreamingMode()
>> .build();
>>
>> StreamExecutionEnvironment env =
>> StreamExecutionEnvironment.getExecutionEnvironment();
>>
>> env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
>> env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
>> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
>> 最大允许同时出现几个CheckPoint
>> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
>> 最小得间隔时间
>> env.getCheckpointConfig().setPreferCheckpointForRecovery(true);
>> //
>> 是否倾向于用CheckPoint做故障恢复
>> env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
>> //
>> 容忍多少次CheckPoint失败
>> //Checkpoint文件清理策略
>>
>>
>> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
>> //Checkpoint外部文件路径
>> env.setStateBackend(new FsStateBackend(new
>> URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
>> TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
>> StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
>> settings);
>> String sourceDDL = String.format(
>> "CREATE TABLE debezium_source (" +
>> " id INT NOT NULL," +
>> " name STRING," +
>> " description STRING," +
>> " weight Double" +
>> ") WITH (" +
>> " 'connector' = 'kafka-0.11'," +
>> " 'topic' = '%s'," +
>> " 'properties.bootstrap.servers' = '%s'," +
>> " 'scan.startup.mode' = 'group-offsets'," +
>> " 'format' = 'debezium-json'" +
>> ")", "ddd", " 172.22.20.206:9092");
>> String sinkDDL = "CREATE TABLE sink (" +
>> " id INT NOT NULL," +
>> " name STRING," +
>> " description STRING," +
>> " weight Double," +
>> " PRIMARY KEY (id,name, description,weight) NOT ENFORCED
>> "
>> +
>> ") WITH (" +
>> " 'connector' = 'jdbc'," +
>> " 'url' =
>> 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
>> " 'table-name' = 'products'," +
>> " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
>> " 'username'='DataPip'," +
>> " 'password'='DataPip'" +
>> ")";
>> String dml = "INSERT INTO sink SELECT id,name ,description,
>> weight
>> FROM debezium_source GROUP BY id,name ,description, weight";
>> tEnv.executeSql(sourceDDL);
>> tEnv.executeSql(sinkDDL);
>> tEnv.executeSql(dml);
>>
>>
>>
>> --
>> Sent from: http://apache-flink.147419.n8.nabble.com/
>>
--
Sent from: http://apache-flink.147419.n8.nabble.com/
Re: flink 1.11 checkpoint使用
Posted by 曹武 <14...@163.com>.
如果去掉group by会抛出异常,请问有没有关这个异常的解决方式:
Exception in thread "main" org.apache.flink.table.api.TableException:
Provided trait [BEFORE_AND_AFTER] can't satisfy required trait
[ONLY_UPDATE_AFTER]. This is a bug in planner, please file an issue.
Current node is TableSourceScan(table=[[default_catalog, default_database,
ddd]], fields=[id, age])
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.$anonfun$visitChildren$2(FlinkChangelogModeInferenceProgram.scala:626)
at
scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at scala.collection.Iterator.foreach(Iterator.scala:937)
at scala.collection.Iterator.foreach$(Iterator.scala:937)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1425)
at scala.collection.IterableLike.foreach(IterableLike.scala:70)
at scala.collection.IterableLike.foreach$(IterableLike.scala:69)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike.map(TraversableLike.scala:233)
at scala.collection.TraversableLike.map$(TraversableLike.scala:226)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.visitChildren(FlinkChangelogModeInferenceProgram.scala:614)
at
org.apache.flink.table.planner.plan.optimize.program.FlinkChangelogModeInferenceProgram$SatisfyUpdateKindTraitVisitor.$anonfun$visitSink$1(FlinkChangelogModeInferenceProgram.scala:690)
at
scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:240)
Jark wrote
> Hi,
>
> 能确认一下 kafka 中有完整的全量数据吗？ 也就是 这个 DELETE 消息之前，有对应的 INSERT 消息吗？
> 如果没有的话，是可能会发生这个现象的（DELETE 在 group by 节点会被认为脏数据而丢掉）。
> 当然也可以像 godfrey 建议的那样，不 groupby，直接全部字段 INSERT INTO sink，DELETE 就不会被丢弃掉。
>
> Best,
> Jark
>
> On Thu, 16 Jul 2020 at 21:56, godfrey he <
> godfreyhe@
> > wrote:
>
>> 为什么要 GROUP BY id,name ,description, weight ？
>> 直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
>> debezium_source" 不能满足需求？
>>
>> 曹武 <
> 14701319164@
>> 于2020年7月16日周四 下午9:30写道：
>>
>> > 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
>> > 从checkpoint恢复以后,新来op=d的数据会删除失败
>> > 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
>> >
>> >
>> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
>> > 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
>> > .useBlinkPlanner()
>> > .inStreamingMode()
>> > .build();
>> >
>> > StreamExecutionEnvironment env =
>> > StreamExecutionEnvironment.getExecutionEnvironment();
>> >
>> > env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
>> > env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
>> > env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
>> > 最大允许同时出现几个CheckPoint
>> > env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L);
>> //
>> > 最小得间隔时间
>> > env.getCheckpointConfig().setPreferCheckpointForRecovery(true);
>> //
>> > 是否倾向于用CheckPoint做故障恢复
>> >
>> env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
>> > //
>> > 容忍多少次CheckPoint失败
>> > //Checkpoint文件清理策略
>> >
>> >
>> >
>> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
>> > //Checkpoint外部文件路径
>> > env.setStateBackend(new FsStateBackend(new
>> > URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
>> > TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
>> > StreamTableEnvironment tEnv =
>> StreamTableEnvironment.create(env,
>> > settings);
>> > String sourceDDL = String.format(
>> > "CREATE TABLE debezium_source (" +
>> > " id INT NOT NULL," +
>> > " name STRING," +
>> > " description STRING," +
>> > " weight Double" +
>> > ") WITH (" +
>> > " 'connector' = 'kafka-0.11'," +
>> > " 'topic' = '%s'," +
>> > " 'properties.bootstrap.servers' = '%s'," +
>> > " 'scan.startup.mode' = 'group-offsets'," +
>> > " 'format' = 'debezium-json'" +
>> > ")", "ddd", " 172.22.20.206:9092");
>> > String sinkDDL = "CREATE TABLE sink (" +
>> > " id INT NOT NULL," +
>> > " name STRING," +
>> > " description STRING," +
>> > " weight Double," +
>> > " PRIMARY KEY (id,name, description,weight) NOT
>> ENFORCED
>> "
>> > +
>> > ") WITH (" +
>> > " 'connector' = 'jdbc'," +
>> > " 'url' =
>> > 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
>> > " 'table-name' = 'products'," +
>> > " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
>> > " 'username'='DataPip'," +
>> > " 'password'='DataPip'" +
>> > ")";
>> > String dml = "INSERT INTO sink SELECT id,name ,description,
>> weight
>> > FROM debezium_source GROUP BY id,name ,description, weight";
>> > tEnv.executeSql(sourceDDL);
>> > tEnv.executeSql(sinkDDL);
>> > tEnv.executeSql(dml);
>> >
>> >
>> >
>> > --
>> > Sent from: http://apache-flink.147419.n8.nabble.com/
>> >
>>
--
Sent from: http://apache-flink.147419.n8.nabble.com/
Re: flink 1.11 checkpoint使用
Posted by Jark Wu <im...@gmail.com>.
Hi,
能确认一下 kafka 中有完整的全量数据吗？ 也就是 这个 DELETE 消息之前，有对应的 INSERT 消息吗？
如果没有的话，是可能会发生这个现象的（DELETE 在 group by 节点会被认为脏数据而丢掉）。
当然也可以像 godfrey 建议的那样，不 groupby，直接全部字段 INSERT INTO sink，DELETE 就不会被丢弃掉。
Best,
Jark
On Thu, 16 Jul 2020 at 21:56, godfrey he <go...@gmail.com> wrote:
> 为什么要 GROUP BY id,name ,description, weight ？
> 直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
> debezium_source" 不能满足需求？
>
> 曹武 <14...@163.com> 于2020年7月16日周四 下午9:30写道：
>
> > 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
> > 从checkpoint恢复以后,新来op=d的数据会删除失败
> > 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
> >
> >
> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
> > 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
> > .useBlinkPlanner()
> > .inStreamingMode()
> > .build();
> >
> > StreamExecutionEnvironment env =
> > StreamExecutionEnvironment.getExecutionEnvironment();
> >
> > env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
> > env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
> > env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
> > 最大允许同时出现几个CheckPoint
> > env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
> > 最小得间隔时间
> > env.getCheckpointConfig().setPreferCheckpointForRecovery(true);
> //
> > 是否倾向于用CheckPoint做故障恢复
> > env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
> > //
> > 容忍多少次CheckPoint失败
> > //Checkpoint文件清理策略
> >
> >
> >
> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
> > //Checkpoint外部文件路径
> > env.setStateBackend(new FsStateBackend(new
> > URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
> > TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
> > StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
> > settings);
> > String sourceDDL = String.format(
> > "CREATE TABLE debezium_source (" +
> > " id INT NOT NULL," +
> > " name STRING," +
> > " description STRING," +
> > " weight Double" +
> > ") WITH (" +
> > " 'connector' = 'kafka-0.11'," +
> > " 'topic' = '%s'," +
> > " 'properties.bootstrap.servers' = '%s'," +
> > " 'scan.startup.mode' = 'group-offsets'," +
> > " 'format' = 'debezium-json'" +
> > ")", "ddd", " 172.22.20.206:9092");
> > String sinkDDL = "CREATE TABLE sink (" +
> > " id INT NOT NULL," +
> > " name STRING," +
> > " description STRING," +
> > " weight Double," +
> > " PRIMARY KEY (id,name, description,weight) NOT ENFORCED
> "
> > +
> > ") WITH (" +
> > " 'connector' = 'jdbc'," +
> > " 'url' =
> > 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
> > " 'table-name' = 'products'," +
> > " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
> > " 'username'='DataPip'," +
> > " 'password'='DataPip'" +
> > ")";
> > String dml = "INSERT INTO sink SELECT id,name ,description,
> weight
> > FROM debezium_source GROUP BY id,name ,description, weight";
> > tEnv.executeSql(sourceDDL);
> > tEnv.executeSql(sinkDDL);
> > tEnv.executeSql(dml);
> >
> >
> >
> > --
> > Sent from: http://apache-flink.147419.n8.nabble.com/
> >
>
Re: flink 1.11 checkpoint使用
Posted by godfrey he <go...@gmail.com>.
为什么要 GROUP BY id,name ,description, weight ？
直接 "INSERT INTO sink SELECT id,name ,description, weight FROM
debezium_source" 不能满足需求？
曹武 <14...@163.com> 于2020年7月16日周四 下午9:30写道：
> 我在使用flink 1.11.0中得ddl 部分 采用debezium-json做cdc得时候
> 从checkpoint恢复以后,新来op=d的数据会删除失败
> 重启命令:./bin/flink run -m yarn-cluster /root/bigdata-flink-1.0.jar -s
>
> hdfs://prehadoop01:8020/flink/checkpoints/4cc5df8b96e90c1c2a4d3719a77f51d1/chk-819/_metadata
> 代码: EnvironmentSettings settings = EnvironmentSettings.newInstance()
> .useBlinkPlanner()
> .inStreamingMode()
> .build();
>
> StreamExecutionEnvironment env =
> StreamExecutionEnvironment.getExecutionEnvironment();
>
> env.enableCheckpointing(1000, CheckpointingMode.EXACTLY_ONCE);
> env.getCheckpointConfig().setCheckpointTimeout(6000L); // 超时时间
> env.getCheckpointConfig().setMaxConcurrentCheckpoints(1); //
> 最大允许同时出现几个CheckPoint
> env.getCheckpointConfig().setMinPauseBetweenCheckpoints(10L); //
> 最小得间隔时间
> env.getCheckpointConfig().setPreferCheckpointForRecovery(true); //
> 是否倾向于用CheckPoint做故障恢复
> env.getCheckpointConfig().setTolerableCheckpointFailureNumber(1);
> //
> 容忍多少次CheckPoint失败
> //Checkpoint文件清理策略
>
>
> env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
> //Checkpoint外部文件路径
> env.setStateBackend(new FsStateBackend(new
> URI("hdfs://172.22.20.205:8020/flink/checkpoints"), false));
> TimeUnit.MINUTES), Time.of(10, TimeUnit.SECONDS)));
> StreamTableEnvironment tEnv = StreamTableEnvironment.create(env,
> settings);
> String sourceDDL = String.format(
> "CREATE TABLE debezium_source (" +
> " id INT NOT NULL," +
> " name STRING," +
> " description STRING," +
> " weight Double" +
> ") WITH (" +
> " 'connector' = 'kafka-0.11'," +
> " 'topic' = '%s'," +
> " 'properties.bootstrap.servers' = '%s'," +
> " 'scan.startup.mode' = 'group-offsets'," +
> " 'format' = 'debezium-json'" +
> ")", "ddd", " 172.22.20.206:9092");
> String sinkDDL = "CREATE TABLE sink (" +
> " id INT NOT NULL," +
> " name STRING," +
> " description STRING," +
> " weight Double," +
> " PRIMARY KEY (id,name, description,weight) NOT ENFORCED "
> +
> ") WITH (" +
> " 'connector' = 'jdbc'," +
> " 'url' =
> 'jdbc:mysql://172.27.4.22:3306/test?autoReconnect=true'," +
> " 'table-name' = 'products'," +
> " 'driver'= 'com.mysql.cj.jdbc.Driver'," +
> " 'username'='DataPip'," +
> " 'password'='DataPip'" +
> ")";
> String dml = "INSERT INTO sink SELECT id,name ,description, weight
> FROM debezium_source GROUP BY id,name ,description, weight";
> tEnv.executeSql(sourceDDL);
> tEnv.executeSql(sinkDDL);
> tEnv.executeSql(dml);
>
>
>
> --
> Sent from: http://apache-flink.147419.n8.nabble.com/
>