Aggregation/evaluation of heterogenic time series data

• US 10,311,045 B2
• Filed: 01/26/2015
• Issued: 06/04/2019
• Est. Priority Date: 01/26/2015
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation), Microsoft Technology Limited, LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Croft, Jeffrey Deane
• Primary Examiner(s): Nguyen, Phong H
• Application Number:
  US14/605,801
• Publication Number:
  US 20160217160A1
• Time in Patent Office: 1,590 Days
• Field of Search: 707756
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/2477 Temporal data queries

Abstract

The collection and aggregation of time series data from a variety of heterogenic time series data sources. This may be accomplished through the use of multiple collector modules, each configured to gather time series data from a different time series data source, and translate that time series data from its original format into a common format. An evaluation module applies one or more expressions against the time series data in the common format in order to identify one or more operations to perform, such as alerting, reporting, actuating, and so forth. Accordingly, the principles describe herein allow real world information to be gather and acted upon even when the time series data is gathered from disparate sources. Furthermore, different systems can rely upon the actions being consistent based on access to the same underlying data.

Claims

1. A method of improving the efficiency of a computing system using time series data to determine one or more actions to be taken based on the time series data, wherein the method is performed by one or more processors executing computer-executable instructions for the method, and the method comprising acts of:

performing a single translation of a first time series data of a first type at a first collector module;

performing a single translation of a second time series data of a second type at a second collector module; and

wherein;

the first and second types of time series data are obtained from different heterogenic data sources that use different formats;

the first and second types of time series data are translated from respective first and second formats used by the different heterogenic data sources from which the first and second types of time series data are obtained, into corresponding time series data that are searchable based on having a common format;

the translated first and second types of time series data are then ready for storage without further translation; and

the first and second collector modules are dynamically linked and each comprise a schema used to translate the corresponding first and second formats of the first and second collector modules into the common format for the searchable time series data;

storing the corresponding searchable time series data having the common format in a data pool;

based on input from a user, generating one or more expressions applied to at least some of the stored corresponding searchable time series data, wherein the one or more expressions are generated based on the common format in order to facilitate building the expressions in a more intuitive way and without reference to the different formats used by the different heterogenic data sources;

based on the one or more applied expressions retrieving from the data pool at least some of the corresponding searchable time series data having the common format; and

using the one or more expressions, evaluating the retrieved searchable time series data using the common format of the time series data to determine one or more resulting actions to perform;

wherein the evaluation of the time series data is performed without reference to the different formats used by the different heterogenic data sources in order to reduce inconsistent results; and

performing one or more of the resulting actions.

2. The method in accordance with claim 1, further comprising acts of:

gathering from a third heterogenic data source time series data of a third type and having a third format;

translating the time series data of the third type from the third format into corresponding searchable time series data having the common format, and storing the searchable corresponding time series data for the third type of time series data in the data pool; and

wherein evaluating the retrieved time series data comprises evaluating at least some the third corresponding time series data for the third type of time series data.

3. The method in accordance with claim 1, wherein the one or more resulting actions comprise generating an alert.

4. The method in accordance with claim 1, wherein the one or more resulting actions comprise generating a report.

5. The method in accordance with claim 1, wherein the schema comprises a first schema used to configure the first type of times series data gathered prior to translation of the first type of time series data, and a second schema used to configure the second type of time series data gathered prior to translation of the second type of time series data.

6. The method in accordance with claim 1, wherein at least one of the first and second types of time series data is external to an enterprise system in which the first and second collector modules operate.

7. The method in accordance with claim 5, wherein the first collection module and the second collection module use the respective first and second schemas to translate the first and second types of time series data, respectively, into the common format.

8. The method in accordance with claim 1, wherein the input from the user generating one or more expression to be applied is input at a user interface, and wherein evaluating the retrieved first and second plurality of time series data provided by the first and second collector modules to determine the one or more resulting actions is performed by an evaluation module that receives the one or more expressions input by the user at the user interface.

9. The method in accordance with claim 1, wherein at least one of the first and second types of time series data is live data.

10. The method in accordance with claim 1, wherein at least one of the first and second types of time series data is historical data.

11. The method in accordance with claim 1, wherein at least one of the first and second types of time series data are change history records.

12. The method in accordance with claim 1, wherein at least one of the first and second types of time series data are log records.

13. A computer program product comprising one or more computer-readable storage media having thereon computer-executable instructions that are structured such that, when executed by one or more processors of a computing system, cause the computing system to perform a method of improving the efficiency of a computing system using time series data to determine one or more actions to be taken based on the time series data, wherein the method is performed by one or more processors executing computer-executable instructions for the method, and the method comprising acts of:

performing a single translation of a first time series data of a first type at a first collector module;

performing a single translation of a second time series data of a second type at a second collector module; and

wherein;

the first and second types of time series data are obtained from different heterogenic data sources that use different formats;

the first and second types of time series data are translated from respective first and second formats used by the different heterogenic data sources from which the first and second types of time series data are obtained, into corresponding time series data that are searchable based on having a common format;

the translated first and second types of time series data are then ready for storage without further translation; and

the first and second collector modules are dynamically linked and each comprise a schema used to translate the corresponding first and second formats of the first and second collector modules into the common format for the searchable time series data;

storing the corresponding searchable time series data having the common format in a data pool;

based on input from a user, generating one or more expressions applied to at least some of the stored corresponding searchable time series data, wherein the one or more expressions are generated based on the common format in order to facilitate building the expressions in a more intuitive way and without reference to the different formats used by the different heterogenic data sources;

based on the one or more applied expressions retrieving from the data pool at least some of the corresponding searchable time series data having the common format; and

using the one or more expressions, evaluating the retrieved searchable time series data using the common format of the time series data to determine one or more resulting actions to perform;

wherein the evaluation of the time series data is performed without reference to the different formats used by the different heterogenic data sources in order to reduce inconsistent results; and

performing one or more of the resulting actions.

14. A computing system comprising:

one or more processors;

a memory containing computer-executable instructions which, when executed by the one or more processors, cause the computing system to operate with an architecture for a collection and evaluation environment that performs a method of improving the efficiency of a computing system using time series data to determine one or more actions to be taken based on the time series data, and wherein the method performed by the architecture comprises;

performing a single translation of a first time series data of a first type at a first collector module;

performing a single translation of a second time series data of a second type at a second collector module; and

wherein;

the first and second types of time series data are obtained from different heterogenic data sources that use different formats;

the first and second types of time series data are translated from respective first and second formats used by the different heterogenic data sources from which the first and second types of time series data are obtained, into corresponding time series data that are searchable based on having a common format;

the translated first and second types of time series data are then ready for storage without further translation; and

the first and second collector modules are dynamically linked and each comprise a schema used to translate the corresponding first and second formats of the first and second collector modules into the common format for the searchable time series data;

storing the corresponding searchable time series data having the common format in a data pool;

based on input from a user, generating one or more expressions applied to at least some of the stored corresponding searchable time series data, wherein the one or more expressions are generated based on the common format in order to facilitate building the expressions in a more intuitive way and without reference to the different formats used by the different heterogenic data sources;

based on the one or more applied expressions retrieving from the data pool at least some of the corresponding searchable time series data having the common format; and

using the one or more expressions, evaluating the retrieved searchable time series data using the common format of the time series data to determine one or more resulting actions to perform;

wherein the evaluation of the time series data is performed without reference to the different formats used by the different heterogenic data sources in order to reduce inconsistent results; and

performing one or more of the resulting actions.

15. The system in accordance with claim 14, wherein the method performed by the architecture further comprises:

gathering from a third heterogenic data source time series data of a third type and having a third format;

translating at the one or more collector modules the time series data of the third type from the third format into searchable corresponding time series data having the common format, and storing the searchable corresponding time series data for the third type of time series data in the data pool; and

wherein evaluating the retrieved time series data at the evaluation module comprises evaluating at least some the third corresponding time series data for the third type of time series data.

16. The system in accordance with claim 14, wherein the schema comprises a first schema used to configure the first type of times series data gathered prior to translation of the first type of time series data, and a second schema used to configure the second type of time series data gathered prior to translation of the second type of time series data.

17. The system in accordance with claim 16, wherein the first collection module and the second collection module use the respective first and second schemas to configure the first and second types of time series data, respectively.