数据血缘，支持spark sql,hive sql,pg sql,presto sql,mysql sql,tidb sql, flink sql, datax血缘,Spark/flink jar 运行命令的血缘解析；支持with语法
- 特别提示：presto和spark均支持with语法
- 目前解析到表级别，可以扩展到字段级别
- 支持datax血缘(mysql/pg/s3)
mvn antlr4:antlr4
mvn clean package
- spark SQL
val sql = "CREATE DATABASE IF NOT EXISTS bigdata"
val statementData = SparkSQLHelper.getStatementData(sql)
println(statementData.statement)- presto SQL
val sql = "INSERT INTO adc.fsfd with recursive t as (select a,b,v from a.x) select a,b,v from t"
val statementData = PrestoSQLHelper.getStatementData(sql)
println(statementData.statement)- Tidb SQL/MySQL
val sql = "insert into bigdata.user select * from users a left outer join address b on a.address_id = b.id"
val statementData = PrestoSQLHelper.getStatementData(sql)
println(statementData.statement)- Flink SQL
val sql = "CREATE SOURCE TABLE student_scores (\n" +
" student_number varchar comment '学号', \n" +
" student_name varchar comment '姓名', \n" +
" subject varchar comment '学科',\n" +
" score INT comment '成绩' \n" +
")\n" +
"WITH (\n" +
" type = \"dis\",\n" +
" kafka.region = \"cn-north-1\"\n" +
") TIMESTAMP BY proctime proctime1"
val statementData = StreamSQLHelper.getStatementData(sql).get(0)
println(statementData.statement)