Rocketmq Streams SQL 为 Rocketmq Streams 的开发提供了基于SQL的开发体验， 让基于消息队列的流式开发更加容易；
- 采用标准的流式SQL规范，可以与其他的流计算框架如Flink完美兼容；
- 兼容Flink自带的
udf、udaf和udtf，除此之外，用户还可以通过实现相关接口来轻松扩展函数；
import com.alibaba.rsqldb.clients.*;
String sql="CREATE FUNCTION now as 'com.sql.Function';\n"
+ "CREATE TABLE graph_vertex_proc (\n"
+ " `time` varchar,\n"
+ " `uuid` varchar,\n"
+ " aliuid varchar,\n"
+ " pid varchar,\n"
+ " file_path varchar,\n"
+ " cmdline varchar,\n"
+ " tty varchar,\n"
+ " cwd varchar,\n"
+ " perm varchar\n"
+ ") WITH (\n"
+ " type='metaq',\n"
+ " topic='blink_dXXXXXXX',\n"
+ " pullIntervalMs='100',\n"
+ " consumerGroup='CID_BLINK_SOURCE_001',\n"
+ " fieldDelimiter='#'\n"
+ ");\n"
+ "CREATE TABLE graph_proc_label_extend (\n"
+ " `time` varchar,\n"
+ " `uuid` varchar,\n"
+ " aliuid varchar,\n"
+ " pid varchar,\n"
+ " file_path varchar,\n"
+ " cmdline varchar,\n"
+ " tty varchar,\n"
+ " cwd varchar,\n"
+ " perm varchar\n"
+ ") WITH (type = 'print');\n"
+ "INSERT\n"
+ " INTO graph_proc_label_extend\n"
+ "SELECT\n"
+ " `time`,\n"
+ " `uuid`,\n"
+ " aliuid,\n"
+ " pid,\n"
+ " file_path,\n"
+ " cmdline,\n"
+ " tty,\n"
+ " cwd,\n"
+ " perm\n"
+ "FROM\n"
+ " graph_vertex_proc;";
SQLStreamClient sqlStreamClient= new SQLStreamClient("test_namespace", "test_pipeline",sql);
sqlStreamClient.start();
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>rsqldb-clients</artifactId>
<version>1.0.0-SNAPSHOT</version>
</dependency>