Query task processing based on memory allocation and performance criteria

• US 10,565,206 B2
• Filed: 11/14/2016
• Issued: 02/18/2020
• Est. Priority Date: 05/14/2015
• Status: Active Grant

• Current Assignee: Deephaven Data Labs, LLC
• Original Assignee: Deephaven Data Labs, LLC
• Inventors: Teodorescu, Radu, Caudy, Ryan, Kent, IV, David R., Wright, Charles
• Primary Examiner(s): Hershley, Mark E
• Application Number:
  US15/351,429
• Publication Number:
  US 20180137175A1
• Time in Patent Office: 1,191 Days
• Field of Search: 707720
• CPC Class Codes: G06F 11/1451 by selection of backup contents
• CPC Class Codes: G06F 11/1464 for networked environments
• CPC Class Codes: G06F 11/1469 Backup restoration techniques
• CPC Class Codes: G06F 12/0261 using reference counting
• CPC Class Codes: G06F 12/084 with a shared cache
• CPC Class Codes: G06F 12/1483 using an access-table, e.g. matrix or list
• CPC Class Codes: G06F 15/17331 Distributed shared memory [DSM], e.g. remote direct memory access [RDMA]
• CPC Class Codes: G06F 16/113 Details of archiving lifecycle management in storage systems G06F3/0649; backup systems G06F11/1446
• CPC Class Codes: G06F 16/144 Query formulation
• CPC Class Codes: G06F 16/162 Delete operations erasing in storage systems G06F3/0652
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/221 Column-oriented storage; Management thereof
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/2237 Vectors, bitmaps or matrices
• CPC Class Codes: G06F 16/2246 Trees, e.g. B+trees
• CPC Class Codes: G06F 16/2255 Hash tables
• CPC Class Codes: G06F 16/2264 Multidimensional index structures
• CPC Class Codes: G06F 16/2272 Management thereof
• CPC Class Codes: G06F 16/2282 Tablespace storage structures; Management thereof
• CPC Class Codes: G06F 16/2291 : User-Defined Types; Storage management thereof
• CPC Class Codes: G06F 16/23 : Updating
• CPC Class Codes: G06F 16/2308 : Concurrency control transaction processing G06F9/466
• CPC Class Codes: G06F 16/2358 : Change logging, detection, and notification replication G06F16/27
• CPC Class Codes: G06F 16/2365 : Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/2372 : Updates performed during offline database operations
• CPC Class Codes: G06F 16/2379 : Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/242 : Query formulation
• CPC Class Codes: G06F 16/2428 : Query predicate definition using graphical user interfaces, including menus and forms G06F16/2423 takes precedence
• CPC Class Codes: G06F 16/245 : Query processing
• CPC Class Codes: G06F 16/2453 : Query optimisation
• CPC Class Codes: G06F 16/24534 : Query rewriting; Transformation
• CPC Class Codes: G06F 16/24535 : of sub-queries or views
• CPC Class Codes: G06F 16/24537 : of operators
• CPC Class Codes: G06F 16/24539 : using cached or materialised query results
• CPC Class Codes: G06F 16/2455 : Query execution
• CPC Class Codes: G06F 16/24553 : of query operations
• CPC Class Codes: G06F 16/2456 : Join operations
• CPC Class Codes: G06F 16/24561 : Intermediate data storage techniques for performance improvement
• CPC Class Codes: G06F 16/2457 : with adaptation to user needs
• CPC Class Codes: G06F 16/24575 : using context
• CPC Class Codes: G06F 16/248 : Presentation of query results
• CPC Class Codes: G06F 16/254 : Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/27 : Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
• CPC Class Codes: G06F 16/278 : Data partitioning, e.g. horizontal or vertical partitioning
• CPC Class Codes: G06F 16/285 : Clustering or classification
• CPC Class Codes: G06F 16/9024 : Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/907 : Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/951 : Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 : Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 : Presentation of query results
• CPC Class Codes: G06F 16/9566 : URL specific, e.g. using aliases, detecting broken or misspelled links
• CPC Class Codes: G06F 16/9574 : of access to content, e.g. by caching
• CPC Class Codes: G06F 17/40 : Data acquisition and logging for input to computer G06F3/00
• CPC Class Codes: G06F 21/00 : Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
• CPC Class Codes: G06F 21/6209 : to a single file or object, e.g. in a secure envelope, encrypted and accessed using a key, or with access control rules appended to the object itself
• CPC Class Codes: G06F 2201/805 : Real-time
• CPC Class Codes: G06F 2201/84 : Using snapshots, i.e. a logical point-in-time copy of the data
• CPC Class Codes: G06F 2212/1052 : Security improvement
• CPC Class Codes: G06F 2212/154 : Networked environment
• CPC Class Codes: G06F 2212/163 : Server or database system
• CPC Class Codes: G06F 2212/60 : Details of cache memory
• CPC Class Codes: G06F 3/0481 : based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/0482 : Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/0483 : Interaction with page-structured environments, e.g. book metaphor
• CPC Class Codes: G06F 3/04847 : Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G06F 3/0485 : Scrolling or panning
• CPC Class Codes: G06F 3/04895 : Guidance during keyboard input operation, e.g. prompting
• CPC Class Codes: G06F 3/0605 : by facilitating the interaction with a user or administrator
• CPC Class Codes: G06F 3/0656 : Data buffering arrangements
• CPC Class Codes: G06F 3/067 : Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: G06F 40/117 : Tagging; Marking up details of markup languages G06F40/143; Designating a block; Setting of attributes style sheets, e.g. eXtensible Stylesheet Language Transformation [XSLT], G06F40/154
• CPC Class Codes: G06F 40/134 : Hyperlinking
• CPC Class Codes: G06F 40/166 : Editing, e.g. inserting or deleting
• CPC Class Codes: G06F 40/174 : Form filling; Merging
• CPC Class Codes: G06F 40/177 : of tables; using ruled lines
• CPC Class Codes: G06F 40/18 : of spreadsheets form-filling G06F40/174
• CPC Class Codes: G06F 40/183 : Tabulation, i.e. one-dimensional positioning
• CPC Class Codes: G06F 40/216 : using statistical methods
• CPC Class Codes: G06F 40/274 : Converting codes to words; Guess-ahead of partial word inputs
• CPC Class Codes: G06F 8/30 : Creation or generation of source code
• CPC Class Codes: G06F 8/41 : Compilation
• CPC Class Codes: G06F 8/427 : Parsing
• CPC Class Codes: G06F 8/60 : Software deployment
• CPC Class Codes: G06Q 40/04 : Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: H04L 12/18 : for broadcast or conference , e.g. multicast
• CPC Class Codes: H04L 51/046 : Interoperability with other network applications or services
• CPC Class Codes: H04L 51/212 : using filtering or selective blocking
• CPC Class Codes: H04L 61/5069 : for group communication, multicast communication or broadcast communication
• CPC Class Codes: H04L 63/101 : Access control lists [ACL]
• CPC Class Codes: H04L 63/102 : Entity profiles
• CPC Class Codes: H04L 67/01 : Protocols
• CPC Class Codes: H04L 67/1001 : for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/141 : Setup of application sessions admission control or resource allocation in data switching networks H04L47/70
• CPC Class Codes: H04L 67/34 : involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/56 : Provisioning of proxy services store-and-forward switching systems in data switching networks H04L12/54
• CPC Class Codes: H04L 67/566 : Grouping or aggregating service requests, e.g. for unified processing
• CPC Class Codes: H04L 67/568 : Storing data temporarily at an intermediate stage, e.g. caching
• CPC Class Codes: H04L 67/5681 : Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04L 69/16 : Implementation or adaptation of Internet protocol [IP], of transmission control protocol [TCP] or of user datagram protocol [UDP]

Abstract

Described are methods, systems and computer readable media for query task operations based on memory allocation and performance criteria.

Claims

1. A system for maximizing memory and processing efficiencies in a computer system, the system comprising:

one or more processors;

computer readable storage coupled to the one or more processors, the computer readable storage having stored thereon instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including;

sending a digital request from a client computer to a remote query processor on a query server computer;

creating and storing, in a computer storage separate from the computer readable storage, data in a plurality of column sources;

creating and storing in a computer memory a first table object index mapping data in the plurality of column sources to a first table object, the computer memory having faster access time than the computer storage separate from the computer readable storage;

at the remote query processor, providing remote operations including;

an aggregation query operation, the aggregation query operation comprising;

receiving an aggregation query task to create a second table object comprising an updateable aggregation of rows from the first table object;

creating and storing in the computer memory separate from the computer storage, the second table object;

creating a plurality of aggregation states for a plurality of aggregation rows of the second table object, each of the plurality of aggregation rows representing an aggregation of one or more rows of the first table object, each of the plurality of aggregation states being configured to determine an aggregated value for a respective one of the plurality of aggregation rows by executing an aggregation formula;

storing determined aggregated values in the computer memory separate from the computer storage;

creating and starting a listener for the second table object; and

subscribing to receive at the listener an indication of an update to the first table object and, responsive to receiving the indication at the listener, selecting one or more of the aggregation states to update the second table object and accessing a subset of rows of the first table object, wherein the subset of rows is smaller than the first table object,

the computer storage separate from the computer readable storage being remote from the remote query processor and being accessed by the remote query processor via a network, and

the computer memory being local to the remote query processor.

2. The system of claim 1, wherein the aggregated values comprise a collection for each aggregated column of each row of the second table object.

3. The system of claim 2,

wherein a first collection of a first aggregated column of a first row of the second table object is a first ordered collection;

wherein a second collection of a second aggregated column of the first row of the second table object is a second ordered collection; and

wherein the first ordered collection and the second ordered collection have a same ordering.

4. The system of claim 2, wherein the collection comprises a reference to data of the first table object.

5. The system of claim 1, wherein the aggregation function determines a summation and the aggregated values comprise a running sum.

6. The system of claim 1, wherein the aggregation function determines a standard deviation and the aggregated values comprise a running sum, a running sum of squares, and a count.

7. A system for maximizing memory and processing efficiencies in a computer system, the system comprising:

one or more processors;

computer readable storage coupled to the one or more processors, the computer readable storage having stored thereon instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including;

storing a second table object representing an updateable aggregation of rows from a first table object;

creating a plurality of aggregation states for a plurality of aggregation rows of the second table object, each of the plurality of aggregation rows representing an aggregation of one or more rows of the first table object, each of the plurality of aggregation states being configured to determine an aggregated value for a respective one of the plurality of aggregation rows by executing an aggregation formula;

storing determined aggregated values in the computer memory separate from the computer readable storage;

receiving an indication of an update to the first table object; and

responsive to receiving, selecting one or more of the aggregation states to update the second table object and accessing a subset of rows of the first table object.

8. The system of claim 7, wherein the aggregated values comprise a collection for each aggregated column of each row of the second table object.

9. The system of claim 8,

wherein a first collection of a first aggregated column of a first row of the second table object is a first ordered collection;

wherein a second collection of a second aggregated column of the first row of the second table object is a second ordered collection; and

wherein the first ordered collection and the second ordered collection have a same ordering.

10. The system of claim 8, wherein the collection comprises a reference to data of the first table object.

11. The system of claim 8, the operations further comprising:

determining a mapping of a subset of columns and applying the mapping to one or more other columns to create one or more of the collections for the aggregated columns of the second table object.

12. The system of claim 7, wherein the aggregation function determines a weighted average.

13. The system of claim 7, wherein a combination aggregation is determined for a row of the second table object by two or more of the plurality of aggregation states.

14. The system of claim 7,

wherein data of the first table object is stored in a computer storage separate from the computer readable storage that is remote from a computer memory separate from the computer readable storage and the computer storage and is accessed via a network, and

wherein the computer memory separate from the computer readable storage is local to the one or more processors.

15. A nontransitory computer readable medium having stored thereon software instructions that, when executed by one or more processors, cause the one or more processors to perform operations including:

storing, in a computer memory separate from the nontransitory computer readable medium, a second table object representing an updateable aggregation of rows from a first table object;

creating, at a processor coupled to the computer memory, a plurality of aggregation states for a plurality of aggregation rows of the second table object, each of the plurality of aggregation rows representing an aggregation of one or more rows of the first table object, each of the plurality of aggregation states being configured to determine an aggregated value for a respective one of the plurality of aggregation rows by executing an aggregation formula;

storing determined aggregated values in the computer memory;

receiving an indication of an update to the first table object; and

responsive to receiving, selecting one or more of the aggregation states to update the second table object and accessing a subset of rows of the first table object, wherein the subset of rows is smaller than the first table object.

16. The nontransitory computer readable medium of claim 15, wherein the aggregated values comprise a collection for each aggregated column of each row of the second table object.

17. The nontransitory computer readable medium of claim 16,

wherein a first collection of a first aggregated column of a first row of the second table object is a first ordered collection;

wherein a second collection of a second aggregated column of the first row of the second table object is a second ordered collection; and

wherein the first ordered collection and the second ordered collection have a same ordering.

18. The nontransitory computer readable medium of claim 16, wherein the collection comprises a reference to data of the first table object.

19. The nontransitory computer readable medium of claim 16, the operations further comprising:

determining a mapping of a subset of columns and applying the mapping to one or more other columns to create one or more of the collections for the aggregated columns of the second table object.

20. The nontransitory computer readable medium of claim 15, wherein the aggregation function determines a maximum value.

21. The nontransitory computer readable medium of claim 15,

wherein data of the first table object is stored in a computer storage separate from the nontransitory computer readable medium and the computer memory that is remote from the computer memory and is accessed via a network, and

wherein the computer memory is local to the one or more processors.

22. A method for maximizing memory and processing efficiencies in a computer system, the system comprising:

storing, in a computer memory, a second table object representing an updateable aggregation of rows from a first table object;

creating, at a processor coupled to the computer memory, a plurality of aggregation states for a plurality of aggregation rows of the second table object, each of the plurality of aggregation rows representing an aggregation of one or more rows of the first table object, each of the plurality of aggregation states being configured to determine an aggregated value for a respective one of the plurality of aggregation rows;

storing determined aggregated values in the computer memory;

receiving an indication of an update to the first table object; and

responsive to receiving, selecting one or more of the aggregation states to update the second table object and accessing a subset of rows of the first table object.

23. The method of claim 22, wherein the aggregated values comprise a collection for each of one or more aggregated columns of each row of the second table object.

24. The method of claim 23,

wherein a first collection of a first aggregated column of a first row of the second table object is a first ordered collection;

wherein a second collection of a second aggregated column of the first row of the second table object is a second ordered collection; and

wherein the first ordered collection and the second ordered collection have a same ordering.

25. The method of claim 24, wherein the first ordering and the second ordering is determined based on an ordering of the first table object.

26. The method of claim 23, wherein the collection comprises a reference to data of the first table object.

27. The method of claim 23, further comprising:

determining a mapping of a subset of columns and applying the mapping to one or more other columns to create one or more of the collections for the aggregated columns of the second table object.

28. The method of claim 22, further comprising:

detecting a change to an output of an aggregation state of the plurality of aggregation states; and

transmitting, responsive to the detecting, a change notification to a subscriber of the second table object.

29. The method of claim 28, wherein the change notifications can include one of a data add notification, a data modify notification, a data delete notification and a data reindex notification.

30. The method of claim 22, wherein at least one of the plurality of aggregation states is configured to determine an aggregated value based on a new value and an associated previous value of the first table object.