Progressive query computation using streaming architectures

Patent metadata

Field	Value
Publication number	US-10140358-B2
Application number	US-201715432270-A
Country	US
Kind code	B2
Filing date	Feb 14, 2017
Priority date	Jul 12, 2012
Publication date	Nov 27, 2018
Grant date	Nov 27, 2018

Abstract

The described implementations relate to processing of electronic data. One implementation is manifest as a technique that can include obtaining a relational query that references one or more data items and associating progress intervals with the data items. The technique can also include converting the relational query into a corresponding streaming query, and providing the streaming query and the data items with the progress intervals to a stream engine that produces incremental results of the query. For example, the progress intervals can be based on row numbers of a relational database table. The progress intervals can be used to define event lifetimes of streaming events that are provided as inputs to the stream engine.

First claim

The invention claimed is:

1. A method comprising:
obtaining a relational query that references relational data items from a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table; and
adapting the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items, the explicit temporal data comprising different lifetimes.

2. The method of claim 1 , further comprising:
receiving code; and
processing the code to derive the relational query.

3. The method of claim 1 , further comprising:
assigning the different lifetimes to stream events processed by the stream engine, the stream events corresponding to individual rows of the relational data table.

4. The method of claim 3 , further comprising:
creating the different lifetimes based at least on row numbers of the relational data table.

5. The method of claim 4 , wherein the different lifetimes include different end times for at least some of the relational data items.

6. The method of claim 1 , further comprising:
grouping multiple rows of data items together into a first set of multiple first rows of data items and a second set of multiple second rows of data items; and
adapting the multiple rows of data items for processing by the stream engine by:
assigning a first progress interval to the first set of multiple first rows; and
assigning a second progress interval to the second set of multiple second rows.

7. A system comprising:
one or more processors; and
one or more computer-readable storage media comprising instructions which, when executed by the one or more processors, cause the one or more processors to:
access relational data items from a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table; and
adapt the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items.

8. The system of claim 7 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
adapt the relational data items by defining different lifetimes for different sets of relational data items.

9. The system of claim 8 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
assign different begin lifetimes to each set of relational data items; and
assign a common end lifetime to the different sets of relational data items.

10. The system of claim 7 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
identify a partitioning attribute, other than a row number, of a query that references the relational data items;
group the relational data items into different sets of relational data items, each relational data item in a given set sharing the same value for the partitioning attribute; and
use the partitioning attribute as a progress attribute for the stream engine.

11. The system of claim 10 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
use the partitioning attribute as the progress attribute by assigning different lifetimes to each set of relational data items.

12. The system of claim 11 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
assign different begin lifetimes to each set of relational data items.

13. The system of claim 12 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
assign different end lifetimes to each set of relational data items.

14. The system of claim 13 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to:
assign a common end lifetime for results provided by the stream engine when processing the relational data items.

15. A hardware computer-readable storage media storing instructions which, when executed by one or more hardware processors, cause the one or more hardware processors to perform acts comprising:
obtaining a relational query that references relational data items from a relational data table that lacks an explicit temporal attribute for ordering the relational data items of the relational data table; and
adapting the relational data items for processing by a stream engine by associating explicit temporal data with the relational data items.

16. The hardware computer-readable storage media of claim 15 , the explicit temporal data defining lifetime windows for the stream engine to process the relational data items.

17. The hardware computer-readable storage media of claim 16 , the lifetime windows having different begin lifetimes and a shared end lifetime.

18. The hardware computer-readable storage media of claim 17 , the shared end lifetime being infinity.

19. The hardware computer-readable storage media of claim 17 , the acts further comprising:
setting a first begin lifetime for multiple first rows of the relational data items; and
setting a second begin lifetime for multiple second rows of the relational data items.

20. The hardware computer-readable storage media of claim 15 , the acts further comprising:
deriving the relational query from script code.

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Fisher Danyel A
• Drucker Steven M
• Goldstein Jonathan D
• Chandramouli Badrish
• Deline Robert A
• Platt John C
• Barnett Mike

Classifications

• G06F16/24568 Primary

  Data stream processing; Continuous queries · CPC title

• G06F16/285 Primary

  Clustering or classification · CPC title

• G06F17/30867

  Physics · mapped topic

• G06F17/3053

  Physics · mapped topic

• G06F17/30486

  Physics · mapped topic