Flink问题解决及性能调优-【Flink不同并行度引起sink2es报错问题】

最近需求，仅想提高sink2es的qps，所以仅调节了sink2es的并行度，但在调节不同算子并行度时遇到一些问题，找出问题的根本原因解决问题，并分析整理。

实例代码

--SET table.exec.state.ttl=86400s; --24 hour,默认: 0 ms
SET table.exec.state.ttl=2592000s; --30 days,默认: 0 ms

CREATE TABLE kafka_table (
     mid bigint,
     db string,
     sch string,
     tab string,
     opt string,
     ts bigint,
     ddl string,
     err string,
     src map<string,string>,
     cur map<string,string>,
     cus map<string,string>,
     account_id AS IF(cur['account_id'] IS NOT NULL , cur['account_id'], src ['account_id']),
     publish_time AS IF(cur['publish_time'] IS NOT NULL , cur['publish_time'], src ['publish_time']),
     msg_status AS IF(cur['msg_status'] IS NOT NULL , cur['msg_status'], src ['msg_status']),
     send_type AS IF(cur['send_type'] IS NOT NULL , cur['send_type'], src ['send_type'])
     --event_time as cast(IF(cur['update_time'] IS NOT NULL , cur['update_time'], src ['update_time']) AS TIMESTAMP(3)), -- TIMESTAMP(3)/TIMESTAMP_LTZ(3)
     --WATERMARK FOR event_time AS event_time - INTERVAL '1' MINUTE     --SECOND
) WITH (
  'connector' = 'kafka',
  'topic' = 't1',
  'properties.bootstrap.servers' = 'xx.xx.xx.xx:9092',
  'properties.group.id' = 'g1',
  'scan.startup.mode' = 'earliest-offset',  --group-offsets/earliest-offset/latest-offset
   --  'properties.enable.auto.commit',= 'true' -- default:false, 如果为false，则在发生checkpoint时触发offset提交
  'format' = 'json'
);



CREATE TABLE es_sink(
     send_type      STRING
    ,account_id     STRING
    ,publish_time   STRING
    ,grouping_id       INTEGER
    ,init           INTEGER
    ,init_cancel    INTEGER
    ,push          INTEGER
    ,succ           INTEGER
    ,fail           INTEGER
    ,init_delete    INTEGER
    ,update_time    STRING
    ,PRIMARY KEY (group_id,send_type,account_id,publish_time) NOT ENFORCED
)
with (
    'connector' = 'elasticsearch-6',
    'index' = 'es_sink',
    'document-type' = 'es_sink',
    'hosts' = 'http://xxx:9200',
    'format' = 'json',
    'filter.null-value'='true',
    'sink.bulk-flush.max-actions' = '1000',
    'sink.bulk-flush.max-size' = '10mb'
);

CREATE view  tmp as
select
    send_type,
    account_id,
    publish_time,
    msg_status,
    case when UPPER(opt) = 'INSERT' and msg_status='0'  then 1 else 0 end AS init,
    case when UPPER(opt) = 'UPDATE' and send_type='1' and msg_status='4' then 1 else 0 end AS init_cancel,
    case when UPPER(opt) = 'UPDATE' and msg_status='3' then 1 else 0 end AS push,
    case when UPPER(opt) = 'UPDATE' and (msg_status='1' or msg_status='5') then 1 else 0 end AS succ,
    case when UPPER(opt) = 'UPDATE' and (msg_status='2' or msg_status='6') then 1 else 0 end AS fail,
    case when UPPER(opt) = 'DELETE' and send_type='1' and msg_status='0' then  1 else 0 end AS init_delete,
    event_time,
    opt,
    ts
FROM kafka_table
where (UPPER(opt) = 'INSERT' and msg_status='0' )
or        (UPPER(opt) = 'UPDATE' and msg_status in ('1','2','3','4','5','6'))
or        (UPPER(opt) = 'DELETE' and send_type='1' and msg_status='0');


--send_type=1          send_type=0
--初始化->0             初始化->0
--取消->4
--推送->3               推送->3
--成功->1               成功->5
--失败->2               失败->6

CREATE view  tmp_groupby as
select
 COALESCE(send_type,'N') AS send_type
,COALESCE(account_id,'N') AS account_id
,COALESCE(publish_time,'N') AS publish_time
,case when send_type is null and account_id is null and publish_time is null then 1
         when send_type is not null and account_id is null and publish_time is null then 2
         when send_type is not null and account_id is not null and publish_time is null then 3
         when send_type is not null and account_id is not null and publish_time is not null then 4
         end grouping_id
,sum(init) as init
,sum(init_cancel) as init_cancel
,sum(push) as push
,sum(succ) as succ
,sum(fail) as fail
,sum(init_delete) as init_delete
from tmp
--GROUP BY GROUPING SETS ((send_type,account_id,publish_time), (send_type,account_id),(send_type), ())
GROUP BY ROLLUP (send_type,account_id,publish_time); --等同于以上

INSERT INTO es_sink
select
     send_type
    ,account_id
    ,publish_time
    ,grouping_id
    ,init
    ,init_cancel
    ,push
    ,succ
    ,fail
    ,init_delete
    ,CAST(LOCALTIMESTAMP AS STRING) as update_time
from tmp_groupby

发现问题

由于groupby或join聚合等算子操作的并行度与sink2es算子操作的并行度不同，上游算子同一个key的数据可能会下发到下游多个不同算子中。
导致sink2es出现多个subtask同时操作同一个key(这里key作为主键id)，报错如下：

...
	Caused by: [test1/cfPTBYhcRIaYTIh3oavCvg][[test1][2]] ElasticsearchException[Elasticsearch exception [type=version_conflict_engine_exception, reason=[test1][4_1_92_2024-01-15 16:30:00]: version conflict, required seqNo [963], primary term [1]. current document has seqNo [964] and primary term [1]]]
		at org.elasticsearch.ElasticsearchException.innerFromXContent(ElasticsearchException.java:510)
		at org.elasticsearch.ElasticsearchException.fromXContent(ElasticsearchException.java:421)
		at org.elasticsearch.action.bulk.BulkItemResponse.fromXContent(BulkItemResponse.java:135)
		at org.elasticsearch.action.bulk.BulkResponse.fromXContent(BulkResponse.java:198)
		at org.elasticsearch.client.RestHighLevelClient.parseEntity(RestHighLevelClient.java:653)
		at org.elasticsearch.client.RestHighLevelClient.lambda$performRequestAsyncAndParseEntity$3(RestHighLevelClient.java:549)
		at org.elasticsearch.client.RestHighLevelClient$1.onSuccess(RestHighLevelClient.java:580)
		at org.elasticsearch.client.RestClient$FailureTrackingResponseListener.onSuccess(RestClient.java:621)
		at org.elasticsearch.client.RestClient$1.completed(RestClient.java:375)
		at org.elasticsearch.client.RestClient$1.completed(RestClient.java:366)
		at org.apache.http.concurrent.BasicFuture.completed(BasicFuture.java:122)
		at org.apache.http.impl.nio.client.DefaultClientExchangeHandlerImpl.responseCompleted(DefaultClientExchangeHandlerImpl.java:177)
		at org.apache.http.nio.protocol.HttpAsyncRequestExecutor.processResponse(HttpAsyncRequestExecutor.java:436)
		at org.apache.http.nio.protocol.HttpAsyncRequestExecutor.inputReady(HttpAsyncRequestExecutor.java:326)
		at org.apache.http.impl.nio.DefaultNHttpClientConnection.consumeInput(DefaultNHttpClientConnection.java:265)
		at org.apache.http.impl.nio.client.InternalIODispatch.onInputReady(InternalIODispatch.java:81)
		at org.apache.http.impl.nio.client.InternalIODispatch.onInputReady(InternalIODispatch.java:39)
		at org.apache.http.impl.nio.reactor.AbstractIODispatch.inputReady(AbstractIODispatch.java:114)
		at org.apache.http.impl.nio.reactor.BaseIOReactor.readable(BaseIOReactor.java:162)
		at org.apache.http.impl.nio.reactor.AbstractIOReactor.processEvent(AbstractIOReactor.java:337)
		at org.apache.http.impl.nio.reactor.AbstractIOReactor.processEvents(AbstractIOReactor.java:315)
		at org.apache.http.impl.nio.reactor.AbstractIOReactor.execute(AbstractIOReactor.java:276)
		at org.apache.http.impl.nio.reactor.BaseIOReactor.execute(BaseIOReactor.java:104)
		at org.apache.http.impl.nio.reactor.AbstractMultiworkerIOReactor$Worker.run(AbstractMultiworkerIOReactor.java:588)
		... 1 more
	[CIRCULAR REFERENCE:[test1/cfPTBYhcRIaYTIh3oavCvg][[test1][2]] ElasticsearchException[Elasticsearch exception [type=version_conflict_engine_exception, reason=[test1][4_1_92_2024-01-15 16:30:00]: version conflict, required seqNo [963], primary term [1]. current document has seqNo [964] and primary term [1]]]]

问题原因

Flink中存在八种分区策略，常用Operator Chain链接方式有三种分区器：

• forward：上下游并行度相同，且不发生shuffle,直连的分区器
• hash：将数据按照key的Hash值下发到下游的算子中
• rebalance：数据会被循环或者随机下发到下游算子中，改变并行度若无keyby，默认使用RebalancePartitioner分区策略

rebalance分区器，可能会将上游算子的同一个key随机下发到下游不同算子中，因而引起报错，如下图：
模型如下：

解决方案

• 分组聚合算子与sink2es算子配置成相同的并行度，即使用forward分区器，如下图：
  
  模型如下：
  

• sink2es算子的并行度配置为1，如下图：

模型如下：

总结

归根结底就是需要保证：上游subtask中同一个key只能下发到下游一个subtask中。