Data continuous SQL process

1. A method, comprising:

repeatedly triggering a User Defined Function (UDF) that generates a data stream;

applying, with a computer, a data continuous Structured Query Language (SQL) query to the data stream to construct a data continuous SQL process (DCSP);

modeling the DCSP as a graph of stations specified with triggering conditions and outgoing pipes, the outgoing pipes defined with a relation schema for type-preservation and with a stream key for identifying stream elements, wherein relations returned from the UDF are replicated to multiple pipes for multiple destination stations; and

executing, in a database engine located in a database, the DCSP, wherein the UDF includes relational operators in the SQL query and expresses a relational transformation since the UDF includes an input value as a relation and an output value as a relation.

2. The method of claim 1 , wherein the UDF is repeatedly triggered by stream inputs, timers, and event conditions.

3. The method of claim 1 further comprising:

specifying data-stream-driven processes with SQL queries;

executing the data-stream-driven processes directly at a database management system (DBMS) level.

4. The method of claim 1 further comprising, executing UDFs under streamed Input/Outputs.

5. The method of claim 1 , wherein the DCSP is data-stream driven and continuously running.

6. The method of claim 1 further comprising, constructing the DSCP from stations and pipes recursively as a Data Continuous Query (DCQ).

7. The method of claim 6 further comprising, using multiple correlated DCQs to represent the DSCP, wherein data flows are naturally expressed by DCQs and execution ordering is based on a DCQ station defined before being referred to in other DCQs.

8. The method of claim 1 wherein the UDFs have as input a list of relations and return value as a relation called Relation Valued Functions (RVFs).

9. The method of claim 1 wherein a producer RVF inserts an element identifiable by a stream key value, and a consumer RVF de-queues the inserted element.

10. A non-transitory computer readable storage medium having instructions for causing a computer to execute a method, comprising:

executing a continuous data stream process with three functions that include an extract, transform, load (ETL) process, an aggregation process, and reporting process;

specifying the continuous data stream process with Structured Query Language (SQL) queries;

executing the SQL queries at a database management system (DBMS) level, wherein the SQL queries include User Defined Functions (UDFs) that perform relational transformations like a relational operator since the UDFs include input values as relations and output values as relations; and

identifying stations with triggering conditions and outgoing pipes, the outgoing pipes defined with a relation schema for type-preservation and with a stream key for identifying stream elements, wherein relations returned from the UDF are replicated to multiple pipes for multiple destination stations.

11. The non-transitory computer readable storage medium of claim 10 , wherein the ETL process, the aggregation process, and the reporting process execute in different cycles with the ETL process executing more frequently than the reporting process.

12. The non-transitory computer readable storage medium of claim 10 further comprising, pushing down the continuous data stream process to the DBMS level to avoid round-trip traffic in data access and utilize parallel database communications to increase performance of executing the SQL queries.

13. The non-transitory computer readable storage medium of claim 10 , wherein the ETL process, the aggregation process, and the reporting process are not cascaded on a performance execution basis since for every given number of plural executions of the ETL process the aggregate process executes only once.

14. A computer system, comprising:

a computer that generates a data continuous Structured Query Language (SQL) query to a continuous data stream to construct a data continuous SQL process (DCSP);

a database in communication with the computer, the database including a database engine that executes the DCSP in the database, wherein the DCSP is constructed from User Defined Functions (UDFs) that include relational operators in the SQL query and that express a relational transformation since the UDFs include an input value as a relation and an output value as a relation; and

wherein the DCSP includes stations specified with triggering conditions and outgoing pipes, the outgoing pipes defined with a relation schema for type-preservation and with a stream key for identifying stream elements, wherein relations returned from the UDF are replicated to multiple pipes for multiple destination stations.

15. The computer system of claim 14 , wherein the UDFs are continuously running.

16. The computer system of claim 14 , wherein execution of the DCSP occurs in the database to increase performance of executing queries to the database.

17. The computer system of claim 14 , wherein the UDFs are triggered to repeatedly run by stream inputs to generate a data stream that is deposited to a stream table.

18. The computer system of claim 14 , wherein the UDFs are triggered to repeatedly run by stream inputs to generate a data stream that is fed into other UDFs.

19. The computer system of claim 14 , wherein the UDFs are triggered to repeatedly run by stream inputs and are not composed on a one-execution basis but coupled asynchronously together.

20. The computer system of claim 14 further comprising:

stations that host the UDFs that are continuously executed;

pipes that function as first-in-first-out containers that connect the stations.