System and method for investigating large amounts of data

• US 10,423,582 B2
• Filed: 11/28/2017
• Issued: 09/24/2019
• Est. Priority Date: 06/23/2011
• Status: Active Grant

• Current Assignee: Palantir Technologies Incorporated
• Original Assignee: Palantir Technologies Incorporated
• Inventors: Stowe, Geoffrey, Fischer, Chris, George, Paul, Bingham, Eli, Hill, Rosco
• Primary Examiner(s): Fleurantin, Jean B
• Application Number:
  US15/824,096
• Publication Number:
  US 20180081896A1
• Time in Patent Office: 665 Days
• Field of Search: 707692, 707 69, 707694
• CPC Class Codes: G06F 11/2025 using centralised failover control functionality
• CPC Class Codes: G06F 16/10 File systems; File servers
• CPC Class Codes: G06F 16/13 File access structures, e.g. distributed indices arrangements of input from, or output to, record carriers G06F3/06
• CPC Class Codes: G06F 16/148 File search processing
• CPC Class Codes: G06F 16/17 Details of further file system functions
• CPC Class Codes: G06F 16/1744 using compression, e.g. sparse files
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/258 Data format conversion from or to a database
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/902 using more than one table in sequence, i.e. systems with three or more layers
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00

Abstract

A data analysis system is proposed for providing fine-grained low latency access to high volume input data from possibly multiple heterogeneous input data sources. The input data is parsed, optionally transformed, indexed, and stored in a horizontally-scalable key-value data repository where it may be accessed using low latency searches. The input data may be compressed into blocks before being stored to minimize storage requirements. The results of searches present input data in its original form. The input data may include access logs, call data records (CDRs), e-mail messages, etc. The system allows a data analyst to efficiently identify information of interest in a very large dynamic data set up to multiple petabytes in size. Once information of interest has been identified, that subset of the large data set can be imported into a dedicated or specialized data analysis system for an additional in-depth investigation and contextual analysis.

Claims

1. A computer-implemented method comprising:

receiving a search parameter;

deriving a search criterion from the search parameter;

using the search criterion to obtain one or more first values from a first-key value family of a key-value data repository, the first key-value family mapping keys to data block identifiers;

using the one or more first values to obtain one or more compressed values from a second key-value family of the key-value data repository, the second key-value family mapping data block identifiers to data blocks;

uncompressing the one or more compressed values to produce one or more uncompressed values;

using the search criterion to identify one or more portions of the one or more uncompressed values; and

returning the one or more portions of the one or more uncompressed values as search results, the one or more portions comprising a byte sequential portion of the one or more uncompressed values.

2. The method of claim 1, wherein at least one of the one or more first values comprises an identifier of a compressed value of the one or more compressed values.

3. The method of claim 1, wherein at least one of the one or more first values comprises a key of the second key-value family.

4. The method of claim 1, wherein using the search criterion to identify one or more portions of the one or more uncompressed values comprises using the search criterion to obtain one or more second values from the first-key value family of the key-value data repository, wherein the one or more second values identify a byte sequential portion of one of the one or more uncompressed values.

5. The method of claim 1, wherein each key of the first key-value family is unique at least amongst all keys of the first key-value family.

6. The method of claim 1, wherein the first key-value family comprises at least one million unique keys.

7. The method of claim 1, wherein using the search criterion to obtain the one or more first values includes selecting a key from the first key-value family that equals the search criterion.

8. The method of claim 1:

wherein the key-value data repository comprises a cluster of a plurality of computing nodes;

wherein at least one key of the first key-value family is mastered by at least one node of the plurality nodes and at least one other key of the first key-value family is mastered by at least one other node of the plurality of nodes;

wherein each and every node of the cluster of nodes is configured to obtain values for any key of the first key-value family.

9. A computer system comprising:

a key-value data repository comprising a first key-value family mapping keys to data block identifiers and a second key-value family mapping data block identifiers to data blocks;

one or more processors configured to;

receive a search parameter;

derive a search criterion from the search parameter by at least one of transforming, converting, encoding, and canonicalizing the search parameter to produce the search criterion;

use the search criterion to obtain one or more first values from the first-key value family;

use the one or more first values to obtain one or more compressed values from the second key-value family;

uncompress the one or more compressed values to produce one or more uncompressed values;

use the search criterion to identify one or more portions of the one or more uncompressed values;

return the one or more portions of the one or more uncompressed values as search results, the one or more portions comprising a byte sequential portion of the one or more uncompressed values.

10. The computer system of claim 9, wherein at least one of the one or more first values comprises an identifier of a compressed value of the one or more compressed values.

11. The computer system of claim 9, wherein at least one of the one or more first values comprises a key of the second key-value family.

12. The computer system of claim 9, wherein the one or more processors are configured to use the search criterion to identify one or more portions of the one or more uncompressed values by using the search criterion to obtain one or more second values from the first-key value family of the key-value data repository, wherein the one or more second values identify a byte sequential portion of one of the one or more uncompressed values.

13. The computer system of claim 9, wherein at least one of the one or more first values comprises information identifying a byte sequential portion of one of the one or more uncompressed values.

14. The computer system of claim 9, wherein each key of the first key-value family is unique at least amongst all keys of the first key-value family.

15. The computer system of claim 9, wherein the key-value family is unique at least amongst all keys of the first key-value family.

16. The computer system of claim 9, wherein the one or more processors are configured to use the search criterion to obtain the one or more first values by selecting a key from the first key-value family that equals the search criterion.

17. The computer system of claim 9:

wherein the key-value data repository comprises a cluster of a plurality of computing nodes;

wherein at least one key of the first key-value family is mastered by at least one node of the plurality nodes and at least one other key of the first key-value family is mastered by at least one other node of the plurality of nodes;

wherein each and every node of the cluster of nodes is configured to obtain values for any key of the first key-value family.