System and method for continuous analytics run against a combination of static and real-time data

1. A system for continuous analytics run against a combination of static and real-time data, comprising:

an in-memory storage; and

a processor, the processor being operably connected to the in-memory storage, the processor being programmed to:

receive, in a query engine, from a client, a query that indicates an analytic function to be performed on a combination of static data and real-time data;

in response to receipt of the query that indicates the analytic function to be performed on the combination of static data and real-time data:

load the in-memory storage from a first source external to the processor with data which was stored as the static data;

at the same time that the in-memory storage is already loaded with the static data, continuously receive real-time data as it is being generated by a second source external to the processor, the real-time data being ephemeral;

in response to the real-time data which is continuously received subsequent to receipt of the query:

temporally correlate the real-time data with existing static data in the in-memory storage, and

continuously run the analytic function from the query against, in combination, both the real-time data which is being continuously received and the existing static data which is loaded in the in-memory storage and which is temporally correlated to the real-time data, to continuously produce a result of the analytic function, wherein

the first source of the static data is from a different source than the second source of the real-time data,

the combination of each of the static data and the real-time data is referenced in the query as a single variable, and

the processor is further configured to determine a source of the data, the data being referenced in the single variable, and to process the data differently based on the source of the data;

wherein the combination of static and real-time data indicated in the query which is received and on which the analytic function is performed, indicates at least one of: (1) a combination of different types of static data, (2) combinations of different types of real-time data, and (3) combinations of different types of static data and real-time data;

wherein the processor is further configured to: normalize the at least one of: (1) the combination of different types of static data, (2) the combinations of different types of real-time data, and (3) the combinations of different types of static data and real-time data, into normalized data which is stored in the in-memory storage in the form of a tuple; and

wherein the analytic function which is run is applied against the normalized data stored in the in-memory storage.

2. The system of claim 1 , wherein the static data has a data structure different from the real-time data.

3. The system of claim 1 , wherein at least one of the static data and the real-time data is originated by the first or second sources respectively in a hierarchical format.

4. The system of claim 1 , wherein the processor is further configured to:

analyze the real-time data and the existing static data which are temporally correlated, in a moving window of the real-time data, as streaming data; and

discard the real-time data which has been analyzed and temporally correlated to make room for the real-time data which continues to be received.

5. The system of claim 1 , wherein the processor is further configured to store information about a running calculation being made by the analytic function, to re-use the information about the running calculation in continuously performing the analytic function with the real-time data which is newly received.

6. The system of claim 1 , wherein the processor is further configured to

store the result of the analytic function in the in-memory storage as an analytic cube for use in subsequent queries together with a time stamp in association with the result of the analytic function, as part of the analytic cube; and

in response to a subsequent analytic function for the combination of static data and real-time data having a time period which includes the time stamp, re-use the result of the analytic function from the in-memory storage based on the time stamp associated therewith, as a source of data for the subsequent analytic function.

7. A method for continuous analytics run against a combination of static and real-time data, comprising:

receiving, in a query engine, from a client, a query that indicates an analytic function to be performed on a combination of static data and real-time data;

in response to receiving the query that indicates the analytic function to be performed on the combination of static data and real-time data:

loading, by a processor, an in-memory storage from a first source external to the processor with data which was stored as the static data;

at the same time that the in-memory storage is already loaded with the static data, continuously receiving, by the processor, real-time data as it is being generated by a second source external to the processor, the real-time data being ephemeral;

in response to the real-time data which is continuously received subsequent to receipt of the query:

temporally correlating, by the processor, the real-time data with existing static data in the in-memory storage; and

continuously running, by the processor, the analytic function from the query against, in combination, both the real-time data which is being continuously received and the existing static data which is loaded in the in-memory storage and which is temporally correlated to the real-time data, to continuously produce a result of the analytic function, wherein

the first source of the static data is from a different source than the second source of the real-time data,

the combination of each of the static data and the real-time data is referenced in the query as a single variable, and

further comprising determining, by the processor, a source of the data, the data being referenced in the single variable; and processing, by the processor, the data differently based on the source of the data;

wherein the combination of static and real-time data indicated in the query which is received and on which the analytic function is performed, indicates at least one of: (1) a combination of different types of static data, (2) combinations of different types of real-time data, and (3) combinations of different types of static data and real-time data; and

further comprising:

normalizing, by the processor, the at least one of: (1) the combination of different types of static data, (2) the combinations of different types of real-time data, and (3) the combinations of different types of static data and real-time data, into normalized data which is stored in the in-memory storage in the form of a tuple; and

wherein the analytic function which is run is applied against the normalized data stored in the in-memory storage.

8. The method of claim 7 , wherein the static data has a data structure different from the real-time data.

9. The method of claim 7 , wherein at least one of the static data and the real-time data is originated by the first or second sources respectively in a hierarchical format.

10. The method of claim 7 , further comprising

analyzing the real-time data and the existing static data which are temporally correlated, in a moving window of the real-time data, as streaming data; and

discarding the real-time data which has been analyzed and temporally correlated to make room for the real-time data which continues to be received.

11. The method of claim 7 , further comprising storing information about a running calculation being made by the analytic function, and re-using the information about the running calculation in continuously performing the analytic function with the real-time data which is newly received.

12. The method of claim 7 , further comprising

storing the result of the analytic function in the in-memory storage as an analytic cube for use in subsequent queries together with a time stamp in association with the result of the analytic function, as part of the analytic cube; and

in response to a subsequent analytic function for the combination of static data and real-time data having a time period which includes the time stamp, re-using the result of the analytic function from the in-memory storage based on the time stamp associated therewith, as a source of data for the subsequent analytic function.

13. A method for continuous analytics run against a combination of static and real-time data, comprising:

by a processor, in response to a command that indicates an analytic function to be performed on at least real-time data:

continuously receiving, by the processor, real-time data as it is being generated by a source external to the processor, the real-time data being ephemeral;

in response to the real-time data which is continuously received subsequent to the command:

continuously running, by the processor, the analytic function from the command against the at least real-time data which is being continuously received, to continuously produce a result of the analytic function;

storing, by the processor, the result of the analytic function in an in-memory storage as an analytic cube for use in subsequent calculations together with a time stamp in association with the result of the analytic function, as part of the analytic cube; and

in response to a subsequent calculation for the real-time data having a time period which includes the time stamp, re-using, by the processor, the result of the analytic function from the in-memory storage based on the time stamp associated therewith, together with the real-time data which is newly received, as a source of data for the subsequent calculation, wherein

the command indicates both the analytic function to be performed, and a combination of static data and real-time data on which to perform the analytic function,

a source of the static data is different from a source of the real-time data,

the combination of each of the static data and the real-time data is referenced in the command as a single variable, and

further comprising determining, by the processor, a source of the data being analyzed by the analytic function, the data being referenced in the single variable; and

processing, by the processor, the data differently based on the source of the data;

wherein the combination of static and real-time data indicated in the query which is received and on which the analytic function is performed, indicates at least one of: (1) a combination of different types of static data, (2) combinations of different types of real-time data, and (3) combinations of different types of static data and real-time data;

further comprising, by the processor, normalizing the at least one of: (1) the combination of different types of static data, (2) the combinations of different types of real-time data, and (3) the combinations of different types of static data and real-time data, into normalized data which is stored in the in-memory storage in the form of a tuple; and

wherein the analytic function which is run is applied against the normalized data stored in the in-memory storage.

14. The method of claim 13 , wherein the subsequent calculation is a running calculation being made by the analytic function, further comprising continuously performing the analytic function.

15. The method of claim 13 , wherein the subsequent calculation is made in response to a subsequent command that indicates a second analytic function to be performed on the at least real-time data.