WO2019202368A1 - Temporal analytics for in-memory data stores - Google Patents
Temporal analytics for in-memory data stores Download PDFInfo
- Publication number
- WO2019202368A1 WO2019202368A1 PCT/IB2018/052705 IB2018052705W WO2019202368A1 WO 2019202368 A1 WO2019202368 A1 WO 2019202368A1 IB 2018052705 W IB2018052705 W IB 2018052705W WO 2019202368 A1 WO2019202368 A1 WO 2019202368A1
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- WO
- WIPO (PCT)
- Prior art keywords
- main memory
- here
- data
- temporal
- objects
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
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Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2477—Temporal data queries
Definitions
- In-Memory data stores like database, key- value store, object store, etc. or an Object Caching Service holding ephemeral data objects in main memory for consumers and later these objects are deleted from main memory in addition to storing them in persistent storage like disk for historical data processing.
- a temporal database consisting of the object and its temporal characteristics like timestamp at which object got created, time interval the object was in main memory for consumer and number of times it was used by the consumer, timestamp the object was deleted or removed from main memory, etc.
- a B+ tree consisting of different timestamps as the keys which helps us to do range queries to get different data objects that were used in a given interval of time and how many times each data object was used in that interval.
- the above analytics is very useful for data objects that are repeatedly used over a period of time.
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computational Linguistics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Here we have In-Memory data stores holding ephemeral data objects in main memory for consumers and later these objects are deleted from main memory in addition to storing them in persistent storage like disk for historical data processing. Here we build a temporal database consisting of the object and its temporal characteristics like timestamp at which object got created, time interval the object was in main memory for consumer and number of times it was used by the consumer, timestamp the object was deleted or removed from main memory, etc. Here we build a B+ tree consisting of different timestamps as the keys which helps us to do range queries to get different data objects that were used in a given interval of time.
Description
Temporal Analytics for In-Memory Data Stores
In this invention we have In-Memory data stores like database, key- value store, object store, etc. or an Object Caching Service holding ephemeral data objects in main memory for consumers and later these objects are deleted from main memory in addition to storing them in persistent storage like disk for historical data processing. Here we build a temporal database consisting of the object and its temporal characteristics like timestamp at which object got created, time interval the object was in main memory for consumer and number of times it was used by the consumer, timestamp the object was deleted or removed from main memory, etc. Here we build a B+ tree consisting of different timestamps as the keys which helps us to do range queries to get different data objects that were used in a given interval of time and how many times each data object was used in that interval. The above analytics is very useful for data objects that are repeatedly used over a period of time.
Claims
1. In this invention we have In-Memory data stores like database, key-value store, object store, etc. or an Object Caching Service holding ephemeral data objects in main memory for consumers and later these objects are deleted from main memory in addition to storing them in persistent storage like disk for historical data processing. Here we build a temporal database consisting of the object and its temporal characteristics like timestamp at which object got created, time interval the object was in main memory for consumer and number of times it was used by the consumer, timestamp the object was deleted or removed from main memory, etc. Here we build a B+ tree consisting of different timestamps as the keys which helps us to do range queries to get different data objects that were used in a given interval of time and how many times each data object was used in that interval. The above analytics is very useful for data objects that are repeatedly used over a period of time. The above novel technique of providing Temporal Analytics for data objects held by In-Memory Data Stores is the claim for this invention.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/IB2018/052705 WO2019202368A1 (en) | 2018-04-19 | 2018-04-19 | Temporal analytics for in-memory data stores |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/IB2018/052705 WO2019202368A1 (en) | 2018-04-19 | 2018-04-19 | Temporal analytics for in-memory data stores |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2019202368A1 true WO2019202368A1 (en) | 2019-10-24 |
Family
ID=68240000
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/IB2018/052705 Ceased WO2019202368A1 (en) | 2018-04-19 | 2018-04-19 | Temporal analytics for in-memory data stores |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2019202368A1 (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7257689B1 (en) * | 2004-10-15 | 2007-08-14 | Veritas Operating Corporation | System and method for loosely coupled temporal storage management |
-
2018
- 2018-04-19 WO PCT/IB2018/052705 patent/WO2019202368A1/en not_active Ceased
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7257689B1 (en) * | 2004-10-15 | 2007-08-14 | Veritas Operating Corporation | System and method for loosely coupled temporal storage management |
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