SYSTEMS AND METHODS OF BLOCK COMPUTATION

• US 20120185460A1
• Filed: 01/14/2011
• Published: 07/19/2012
• Est. Priority Date: 01/14/2011
• Status: Active Grant

• Current Assignee: Micro Focus LLC (Open Text Corporation)
• Original Assignee: entIT Software LLC (Open Text Corporation)
• Inventors: Chen, Qiming, Hsu, Meichun
• Granted Patent: US 9,594,573 B2
• Time in Patent Office: Days
• US Class Current: 707/713
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/2471 Distributed queries
• CPC Class Codes: G06F 16/284 Relational databases
• CPC Class Codes: G06F 16/832 Query formulation
• CPC Class Codes: G06F 9/448 Execution paradigms, e.g. implementations of programming paradigms

Abstract

Systems and methods of block computation are disclosed. An example of a method includes buffering a plurality of tuples in a build phase. The method also includes, after buffering a last of the plurality of tuples, applying a computation to all of the buffered tuples in a compute phase. The method also includes returning results of the computation one tuple at a time to a query processing pipeline in a stream-out phase.

Claims

1. A method of block computation comprising:

buffering a plurality of tuples in a build phase;

after buffering a last of the plurality of tuples, applying a computation to all of the buffered tuples in a compute phase; and

returning results of the computation one tuple at a time to a query processing pipeline in a stream-out phase.

2. The method of claim 1, further comprising:

calling a function for each tuple; and

returning a null for each call.

3. The method of claim 1, wherein the compute phase is executed external to a query engine.

4. The method of claim 1, wherein buffering is dynamic along the query processing pipeline.

5. The method of claim 4, wherein the buffering is chunk-wise.

6. The method of claim 5, wherein chunk-wise buffering is based on number of tuples.

7. The method of claim 5, wherein chunk-wise buffering is based on a time window.

8. The method of claim 5, wherein chunk-wise buffering is based on representing individual objects.

9. The method of claim 1, wherein buffering is by multiple calls.

10. A system of block computation, comprising:

a buffer for holding a plurality of tuples during a build phase;

a computation engine for applying a computation during a compute phase after the build phase finishes; and

a query processing pipeline for returning results from the compute phase one tuple at a time during a stream-out phase.

11. The system of claim 10, wherein the build phase finishes after a last of the plurality of tuples is in the buffer.

12. The system of claim 10, further comprising a Set-In, Set-Out (SISO) user defined function (UDF).

13. The system of claim 12, wherein the SISO UDF is for batch analytic computing.

14. The system of claim 12, wherein the SISO UDF receives vector input data for batch processing.

15. The system of claim 12, wherein the SISO UDF includes set-in, set-out block computation operators.

16. The system of claim 10, wherein a data source of the plurality of tuples is a table.

17. The system of claim 10, wherein a data source of the plurality of tuples is a stream.

18. A system of block computation comprising:

a computation engine for applying a computation to a plurality of tuples after buffering a last of the plurality of tuples;

a user defined function (UDF) defining the computation for the computation engine; and

a query processing pipeline for receiving results from the computation engine one tuple at a time.

19. The system of claim 18, wherein the UDF is set-in, set-out (SISO).

20. The system of claim 18, wherein the UDF has four levels of accessible states:

per-function state, per-chunk state, per-tuple state, and per-return state.