Flink Kafka Doris实战demo
环境：
- Flink 1.12
- Doris 0.12
- Kafka 1.0.1+kafka3.1.1
一：编译doris
参考官网Docker编译：https://github.com/apache/incubator-doris/wiki/Doris-Install
1.1 注意问题：
需要把fe/pom.xml中下载的Repository地址改下
cloudera-thirdparty
https://repository.cloudera.com/content/repositories/third-party/ 改为：cloudera-public https://repository.cloudera.com/artifactory/public/
cloudera-plugins
https://repository.cloudera.com/content/groups/public/ 改为：cloudera-public https://repository.cloudera.com/artifactory/public/
1.2 编译：
直接编译就行
1.3 如果不想编译，直接下载编译好的部署包（0.12,0.11版本）
https://download.csdn.net/download/leng91060404/16661347
https://download.csdn.net/download/leng91060404/16655427
二：部署doris(单机版测试)
参考：https://github.com/apache/incubator-doris/wiki/Doris-Install#3-%E9%83%A8%E7%BD%B2
2.1 注意
FE:
在fe目录下创建doris-meta目录;
根据需要修改priority_networks = ip 参数
BE:
修改参数storage_root_path = /home/disk1/doris;/home/disk2/doris；并创建目录；根据需要修改priority_networks = ip 参数
2.2 启动
有问题直接查看log日志，进行分析解决
2.3 查看状态
BE节点需要先在FE中添加，才可加入集群。
可以使用 mysql-client 连接到 FE： ./mysql-client -h host-P port -uroot 其中 host 为 FE 所在节点 ip；port 为 fe/conf/fe.conf 中的 query_port；默认使用 root 账户，无密码登录。
FE状态查看：
用户可以通过 mysql 客户端登陆 Master FE。通过:
SHOW PROC '/frontends';
来查看当前 FE 的节点情况。
也可以通过前端页面连接：http://fe_hostname:fe_http_port/frontend 或者 http://fe_hostname:fe_http_port/system?path=//frontends 来查看 FE 节点的情况。
mysql> SHOW PROC '/frontends';
+--------------------------------+-------------+-----------+-------------+----------+-----------+---------+----------+----------+-----------+------+-------+-------------------+---------------------+----------+--------+
| Name | IP | HostName | EditLogPort | HttpPort | QueryPort | RpcPort | Role | IsMaster | ClusterId | Join | Alive | ReplayedJournalId | LastHeartbeat | IsHelper | ErrMsg |
+--------------------------------+-------------+-----------+-------------+----------+-----------+---------+----------+----------+-----------+------+-------+-------------------+---------------------+----------+--------+
| 172.16.3.76_9011_1618481783037 | xxxxxxxxx | xxxxxxxx | 9011 | 8030 | 9030 | 9020 | FOLLOWER | true | 502881269 | true | true | 24505 | 2021-04-16 16:03:57 | true | |
+--------------------------------+-------------+-----------+-------------+----------+-----------+---------+----------+----------+-----------+------+-------+-------------------+---------------------+----------+--------+
1 row in set (0.02 sec)
BE状态查看：
用户可以通过 mysql-client 登陆 Leader FE。通过:
SHOW PROC '/backends';
来查看当前 BE 的节点情况。
也可以通过前端页面连接：http://fe_hostname:fe_http_port/backend 或者 http://fe_hostname:fe_http_port/system?path=//backends 来查看 BE 节点的情况。
mysql> SHOW PROC '/backends';
+-----------+-----------------+-------------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+---------------------+
| BackendId | Cluster | IP | HostName | HeartbeatPort | BePort | HttpPort | BrpcPort | LastStartTime | LastHeartbeat | Alive | SystemDecommissioned | ClusterDecommissioned | TabletNum | DataUsedCapacity | AvailCapacity | TotalCapacity | UsedPct | MaxDiskUsedPct | ErrMsg | Version |
+-----------+-----------------+-------------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+---------------------+
| 10002 | default_cluster | xxxxxxxx | xxxxxx | 9050 | 9060 | 8040 | 8060 | 2021-04-15 18:17:38 | 2021-04-16 16:02:57 | true | false | false | 13 | 55.108 KB | 64.740 GB | 165.915 GB | 60.98 % | 60.98 % | | 0.12.0-rc03-Unknown |
+-----------+-----------------+-------------+-----------+---------------+--------+----------+----------+---------------------+---------------------+-------+----------------------+-----------------------+-----------+------------------+---------------+---------------+---------+----------------+--------+---------------------+
1 row in set (0.00 sec)
三：flink程序（source：kafka、transfer：flink、sink：kafka）
3.1 数据实体类
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Item {
private int id;
private String name;
private int counts;
private Timestamp ts;
@Override
public String toString() {
return "{" +
"\"id\":" + "\"" + id + "\"" +
",\"name\":" + "\"" + name + "\"" +
",\"counts\":" + "\"" + counts + "\"" +
",\"ts\":" + "\"" + ts + "\"" +
"}";
}
3.2 模拟数据到source-kafka
{
while (true) {
Item item = generateItem();
long startTime = System.currentTimeMillis();
if (isAsync) {
producer.send(new ProducerRecord(topic, item.toString()), new DemoCallBack(startTime, item.toString()));
System.out.println("Sent message: (" + ", " + item.toString() + ")");
try {
Thread.sleep(2000);
} catch (InterruptedException e) {
e.printStackTrace();
}
} else {
try {
producer.send(new ProducerRecord(topic, item)).get();
System.out.println("Sent message: (" + ", " + item + ")");
} catch (InterruptedException | ExecutionException e) {
e.printStackTrace();
}
}
}
}
数据：
{"id":"75392","name":"TIE4","counts":"77098","ts":"2021-04-16 11:40:48.423"}
{"id":"40904","name":"TIE3","counts":"26613","ts":"2021-04-16 11:40:52.436"}
{"id":"18363","name":"SHOE4","counts":"56329","ts":"2021-04-16 11:40:56.446"}
{"id":"17240","name":"TIE4","counts":"32312","ts":"2021-04-16 11:41:00.461"}
3.3 flink处理运行(source+transfer+sink)
sql:
public static final String KAFKA_SQL_EVEN_CREATE = "CREATE TABLE even (\n" +
" `id` INTEGER,\n" +
" `name` STRING,\n" +
" `counts` INTEGER,\n" +
" `ts` TIMESTAMP(3)," +
" WATERMARK FOR ts as ts - INTERVAL '5' SECOND \n" +
") WITH (\n" +
" 'connector' = 'kafka',\n" +
" 'topic' = 'flink_sql_table_test_datas',\n" +
" 'properties.bootstrap.servers' = 'xxxxxxxxxxxxx:9092',\n" +
" 'properties.group.id' = 'testGroup',\n" +
" 'scan.startup.mode' = 'earliest-offset',\n" +
" 'format' = 'json'\n" +
")";
sql :
public static final String QUERY_EVEN_AGG_SQL =
"SELECT\n"
+ " id as even_id,name as even_name,\n"
+ " COUNT(counts) even_cnt \n"
+ "FROM even \n"
+ "GROUP BY TUMBLE(ts, INTERVAL '20' SECOND),id,name";
deal :
{
// set up execution environment
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
EnvironmentSettings settings = EnvironmentSettings.newInstance().inStreamingMode().useBlinkPlanner().build();
StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env, settings);
//create table op
tableEnv.executeSql(KAFKA_SQL_EVEN_CREATE);
tableEnv.executeSql(KAFKA_SQL_ODD_CREATE);
// windows aggregate count op
Table resultEven = tableEnv.sqlQuery(QUERY_EVEN_AGG_SQL);
resultEven.printSchema();
Table resultOdd = tableEnv.sqlQuery(QUERY_ODD_AGG_SQL);
resultOdd.printSchema();
//sql join op
Table joinTable = resultEven.join(resultOdd)
.where(
$("even_name").isEqual($("odd_name")))
.select(
$("even_id").as("id"),
$("even_name").as("name"),
$("even_cnt").as("counts"),
$("ts"));
joinTable.printSchema();
//sink to kafka 1
DataStream<ItemSink> sinkResultStream = tableEnv.toAppendStream(joinTable, ItemSink.class);
//kafka connector
Properties props = new Properties();
props.put("bootstrap.servers", KafkaProperties.KAFKA_SERVER_URL + ":" + KafkaProperties.KAFKA_SERVER_PORT);
props.put("client.id", KafkaProperties.CLIENT_ID);
FlinkKafkaProducer<ItemSink> myProducer = new FlinkKafkaProducer<>(
KafkaProperties.TOPIC_SINK,
new ProducerStringSerializationSchema(KafkaProperties.TOPIC_SINK),
props,
FlinkKafkaProducer.Semantic.EXACTLY_ONCE);
sinkResultStream.addSink(myProducer);
//run
env.execute("Streaming Window SQL Job");
}
sink-kafka数据：
41219,HAT9,1,2021-04-16 11:32:08.524
41219,HAT9,1,2021-04-16 11:33:30.846
41219,HAT9,1,2021-04-16 11:40:36.387
41219,HAT9,1,2021-04-14 19:21:46.738
四：kafka load to doris（flink上面已经sink到kafka）
4.1 建库
CREATE DATABASE example_db;
4.2 建表
CREATE TABLE item
(
id INTEGER,
name VARCHAR(256) DEFAULT '',
ts DATETIME,
counts BIGINT SUM DEFAULT '0'
)
AGGREGATE KEY(id, name, ts)
DISTRIBUTED BY HASH(id) BUCKETS 3
PROPERTIES("replication_num" = "1");
4.3 加载Kafka2Doris任务
CREATE ROUTINE LOAD example_db.task1 ON item
COLUMNS TERMINATED BY ",",
COLUMNS(id, name, counts, ts)
PROPERTIES
(
"desired_concurrent_number"="1",
"max_batch_interval" = "20",
"max_batch_rows" = "300000",
"max_batch_size" = "209715200",
"strict_mode" = "false"
)
FROM KAFKA
(
"kafka_broker_list" = "xxxxxxx:9092",
"kafka_topic" = "sinkTopic",
"property.group.id" = "1234",
"property.client.id" = "12345",
"kafka_partitions" = "0,1,2",
"kafka_offsets" = "0,0,0"
);
4.4 查看任务
SHOW ROUTINE LOAD FOR example_db.task1;
mysql> SHOW ROUTINE LOAD FOR flink_kafka_db.task1;
+-------+-------+---------------------+-----------+---------+--------------------------------+-----------+---------+----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------+-----------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------+----------------------+--------------+----------+
| Id | Name | CreateTime | PauseTime | EndTime | DbName | TableName | State | DataSourceType | CurrentTaskNum | JobProperties | DataSourceProperties | CustomProperties | Statistic | Progress | ReasonOfStateChanged | ErrorLogUrls | OtherMsg |
+-------+-------+---------------------+-----------+---------+--------------------------------+-----------+---------+----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------+-----------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------+----------------------+--------------+----------+
| 10037 | task1 | 2021-04-16 11:27:39 | N/A | N/A | default_cluster:flink_kafka_db | item | RUNNING | KAFKA | 1 | {"partitions":"*","columnToColumnExpr":"id,name,counts,ts","maxBatchIntervalS":"20","whereExpr":"*","maxBatchSizeBytes":"209715200","columnSeparator":"','","maxErrorNum":"0","currentTaskConcurrentNum":"1","maxBatchRows":"300000"} | {"topic":"flink_sql_table_test_sink","currentKafkaPartitions":"0,1,2","brokerList":"172.16.2.148:9092"} | {"group.id":"1234","client.id":"12345"} | {"receivedBytes":726452,"errorRows":0,"committedTaskNum":159,"loadedRows":20118,"loadRowsRate":0,"abortedTaskNum":629,"totalRows":20118,"unselectedRows":0,"receivedBytesRate":0,"taskExecuteTimeMs":3247070} | {"0":"6059","1":"6915","2":"7141"} | | | |
+-------+-------+---------------------+-----------+---------+--------------------------------+-----------+---------+----------------+----------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------+-----------------------------------------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------------------------------------+----------------------+--------------+----------+
1 row in set (0.00 sec)
SHOW ROUTINE LOAD TASK WHERE JobName = "task1";
mysql> SHOW ROUTINE LOAD TASK WHERE JobName = "task1";
+-----------------------------------+-------+-----------+-------+---------------------+---------------------+---------+-------+------------------------------+
| TaskId | TxnId | TxnStatus | JobId | CreateTime | ExecuteStartTime | Timeout | BeId | DataSourceProperties |
+-----------------------------------+-------+-----------+-------+---------------------+---------------------+---------+-------+------------------------------+
| 56543bac022d4fdb-bb5944617d6480ac | 788 | UNKNOWN | 10037 | 2021-04-16 15:56:50 | 2021-04-16 15:56:50 | 40 | 10002 | {"0":6060,"1":6916,"2":7142} |
+-----------------------------------+-------+-----------+-------+---------------------+---------------------+---------+-------+------------------------------+
4.5 通过mysql查看数据
./mysql-client -h host -P port -uroot
mysql> select * from item order by id desc limit 10;
+-------+-------+---------------------+--------+
| id | name | ts | counts |
+-------+-------+---------------------+--------+
| 99995 | SHOE2 | 2021-04-16 11:34:45 | 3 |
| 99995 | SHOE2 | 2021-04-15 19:05:59 | 4 |
| 99995 | SHOE2 | 2021-04-16 11:35:59 | 3 |
| 99995 | SHOE2 | 2021-04-16 11:35:05 | 3 |
| 99995 | SHOE2 | 2021-04-14 19:22:06 | 4 |
| 99995 | SHOE2 | 2021-04-16 11:35:57 | 3 |
| 99995 | SHOE2 | 2021-04-16 11:38:45 | 3 |
| 99995 | SHOE2 | 2021-04-16 11:38:11 | 3 |
| 99995 | SHOE2 | 2021-04-14 19:22:24 | 4 |
| 99995 | SHOE2 | 2021-04-14 19:21:12 | 4 |
+-------+-------+---------------------+--------+
10 rows in set (0.01 sec)
