Automated database query tuning

Information

  • Patent Grant
  • 10762085
  • Patent Number
    10,762,085
  • Date Filed
    Monday, October 17, 2016
    8 years ago
  • Date Issued
    Tuesday, September 1, 2020
    4 years ago
  • CPC
    • G06F16/24545
    • G06F16/217
    • G06F16/221
    • G06F16/2228
    • G06F16/24542
    • G06F16/24544
    • G06F16/24578
  • Field of Search
    • CPC
    • G06F17/30442
    • G06F17/30474
    • G06F16/2453
    • G06F16/24549
    • G06F16/24542
    • G06F16/217
    • G06F16/221
    • G06F16/24544
    • G06F16/24578
    • G06F16/24545
  • International Classifications
    • G06F7/00
    • G06F16/2453
    • G06F16/21
    • G06F16/22
    • G06F16/2457
    • G06F17/00
    • Term Extension
      42
Abstract
Automated query tuning. A database query to be executed against a database is received. The database query is analyzed to determine one or more potential indexes to be evaluated. The one or more potential indexes are evaluated to determine if an optimization utilizing a selected potential index provides improved performance over performing the database query without the selected potential index. The one or more potential indexes are scored based on results of the evaluating. A recommendation of one or more of the potential indexes is provided to a source of the database query.
Description
TECHNICAL FIELD

Embodiments relate to database management. More particularly, embodiments relate to techniques for efficiently tuning database queries.


BACKGROUND

Traditional database query tuning techniques include, for example, use of statistics to determine a most efficient path and/or use of optimized indexes. Other techniques can also but utilized. However, current techniques can only provide partial improvement. More efficient query optimization is desirable to provide a more efficient database environment.





BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements.



FIG. 1 is a flow diagram of one embodiment for a technique to provide query tuning recommendations with a query tuning recommendations engine.



FIG. 2 is an example graphical user interface in which query tuning recommendations for top queries can be presented.



FIG. 3 is an example graphical user interface in which query tuning recommendations for long running queries can be presented.



FIG. 4 is an example graphical user interface in which query tuning recommendations can be presented.



FIG. 5 illustrates a block diagram of an environment where an on-demand database service might be used.



FIG. 6 illustrates a block diagram of an environment where an on-demand database service might be used.





DETAILED DESCRIPTION

In the following description, numerous specific details are set forth. However, embodiments of the invention may be practiced without these specific details. In other instances, well-known structures and techniques have not been shown in detail in order not to obscure the understanding of this description.


Various embodiments of tuning recommendation engines are described herein. In one embodiment, tuning recommendations can be utilized via a query plan interface. For example, when using the salesforce cloud environment, the tuning recommendations can be run/managed/accessed via a query plan user interface (e.g., Explain Query Plan page). In alternate embodiments, the tuning recommendations can be invoked separately and/or provides as a background process.


As described in greater detail below, a tuning query recommendation engine can be provided via the query plan user interface in a mode that also considers potential indexes. In one embodiment, potential indexes are the set of all custom indexes and native skinny indexes that could be built on columns that are filtered or sorted on in the query.


In general, an index is a data structure that can be utilized to improve the performance of data retrieval operations on a database table and usually have an associated cost of additional writes and/or storage space utilization to maintain the index. These indexes can provide the ability to locate data without having to search every row of the database each time a database table is accessed. A skinny table generally refers to a database table having a reduced number of columns (e.g., 2 columns, one of which is a primary key).



FIG. 1 is a flow diagram of one embodiment for a technique to provide query tuning recommendations with a query tuning recommendations engine. A set of one or more potential indexes to consider can be determined, 110. In one embodiment, the potential indexes are the set of all custom indexes and native skinny indexes that could be built on the columns that are filtered or sorted in the query to be optimized. In one embodiment, redundant indexes, for example, indexes covering the same set of columns as an existing index, but with different ordering, are excluded.


One or more of the potential indexes are evaluated, 120. In one embodiment, for each potential index, sampled pre-queries are used to estimate the selectivity of the index. In one embodiment, any available optimizations that could be applied to the indexes can be utilized. In one embodiment, if any of the potential index optimizations would perform better than the existing best option based on existing indexes, that potential optimization can be flagged/reserved/saved for recommendation and/or use.


In one embodiment, if one or more of the potential indexes provides an improvement, the potential index can be built (or a recommendation to build the index can be generated). In one embodiment, once built a potential index can be used directly. In one embodiment, an index join involving one or more potential indexes and zero or more existing indexes can be performed. In one embodiment, one or more sort optimizations can be performed. Other optimizations involving one or more potential indexes and zero or more existing indexes can be performed.


In one embodiment, selectivity can be determined by running a sampled query that tests selectivity on a sample set of a fixed size (e.g., 400 rows) and computes the fraction of rows that would be matched using the new index (or combination of indexes) for the potential new optimization. In one embodiment, one or more of the potential indexes can be scored based on the selectivity, 130.


In one embodiment, potential optimizations can be sorted with existing index optimizations to determine the best plan for the query. If a potential index optimization is determined to be the best option, any potential indexes needed for that optimization are recommended to be built. One or more of these recommendations can be provided for use, 140. The query tuning recommendation engine can report the recommended index(es) for a user to evaluate (e.g., via a graphical user interface) and/or may build the recommended index(es) automatically.



FIG. 2 is an example graphical user interface in which query tuning recommendations for top queries can be presented. In one embodiment, the query tuning recommendations can be presented, for example, in association with a query plan interface or other mechanism for creating or initiating query plans. In one embodiment, the interface of FIG. 2 can be utilized with top database queries as identified in the manner described with respect to FIG. 1.


In one embodiment, query tuning interface 200 can include one or more of the graphical elements described with respect to FIG. 2 to allow a user (or other entity) to select recommended options that can improve query performance. In one embodiment, checkboxes 210 are provided for each recommendation to allow a user a simple (e.g., 1-click) option for query tuning. In one embodiment, interface 200 includes description 220 for each or the query tuning recommendations presented to via interface 200.


In one embodiment, interface 200 can also provide tables 230 to which the various recommendations apply. In one embodiment, interface 200 can also provide fields 240 to which the various recommendations apply. This can allow the user some insight into which aspects of the query are being tuned with the corresponding recommendation.


In one embodiment, interface 200 provides cardinality 250 and table size 260 for the tables to which the recommendation corresponds. In one embodiment, interface 200 further provides threshold selectivity 270 for the tables to which the recommendation corresponds. In one embodiment, interface 200 can provide index type 280, which can indicate whether the corresponding custom index is active or potential. This can provide a user with the status of the custom index. In one embodiment, create index buttons 290 (or other interface elements) can allow a user to cause creation of the corresponding custom index.



FIG. 3 is an example graphical user interface in which query tuning recommendations for long running queries can be presented. In one embodiment, the query tuning recommendations can be presented, for example, in association with a query plan interface or other mechanism for creating or initiating query plans. In one embodiment, the interface of FIG. 3 can be utilized with long running queries as identified in the manner described with respect to FIG. 1.


In one embodiment, a timestamp (310), an organization ID (315), a user ID (320), a query statement ID (325) and an elapsed time (330) is provided for each long running query. In one embodiment, a recommended index (340) can be provided for one or more of the long running queries.


In one embodiment, additional information can be provided via interface 300. For example, a query type (350) and/or a primary entity (355). Further, a query ID (360) can be provided. In one embodiment, some or all of the query statement text (365, 370) can be provided. In one embodiment, the request URI (375) and/or the request ID (380) and/or the source database ID (385) can be provided.



FIG. 4 is an example graphical user interface in which query tuning recommendations can be presented. In one embodiment, the query tuning recommendations can be presented, for example, in association with a query plan interface or other mechanism for creating or initiating query plans.


In one embodiment, interface 400 provides one or more recommended indexes that can be created and/or applied in response to user input. In one embodiment, interface 400 provides an organization ID (405) and/or an entity ID (410) for each recommended index. In one embodiment, interface 400 also provides the columns (420) to which the corresponding custom index can be applied.


In one embodiment, interface 400 can provide an index type (430), a status (440) and/or a number of times recommended (450) for each corresponding custom index. In one embodiment, interface 400 can provide an elapsed time (460) and/or an estimated time savings (470) for using the corresponding custom index. In one embodiment, one or more of the recommended custom indexes can have a corresponding Create Index button (or other interface component) to allow a user to cause the custom index to be created.


Various embodiments of the techniques described herein can be utilized in an on-demand database service environment. Various embodiments of on-demand database service environments are described in greater detail below.



FIG. 5 illustrates a block diagram of an environment 510 wherein an on-demand database service might be used. Environment 510 may include user systems 512, network 514, system 516, processor system 517, application platform 518, network interface 520, tenant data storage 522, system data storage 524, program code 526, and process space 528. In other embodiments, environment 510 may not have all of the components listed and/or may have other elements instead of, or in addition to, those listed above.


Environment 510 is an environment in which an on-demand database service exists. User system 512 may be any machine or system that is used by a user to access a database user system. For example, any of user systems 512 can be a handheld computing device, a mobile phone, a laptop computer, a work station, and/or a network of computing devices. As illustrated in herein FIG. 5 (and in more detail in FIG. 6) user systems 512 might interact via a network 514 with an on-demand database service, which is system 516.


An on-demand database service, such as system 516, is a database system that is made available to outside users that do not need to necessarily be concerned with building and/or maintaining the database system, but instead may be available for their use when the users need the database system (e.g., on the demand of the users). Some on-demand database services may store information from one or more tenants stored into tables of a common database image to form a multi-tenant database system (MTS). Accordingly, “on-demand database service 516” and “system 516” will be used interchangeably herein. A database image may include one or more database objects. A relational database management system (RDMS) or the equivalent may execute storage and retrieval of information against the database object(s). Application platform 518 may be a framework that allows the applications of system 516 to run, such as the hardware and/or software, e.g., the operating system. In an embodiment, on-demand database service 516 may include an application platform 518 that enables creation, managing and executing one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 512, or third party application developers accessing the on-demand database service via user systems 512.


The users of user systems 512 may differ in their respective capacities, and the capacity of a particular user system 512 might be entirely determined by permissions (permission levels) for the current user. For example, where a salesperson is using a particular user system 512 to interact with system 516, that user system has the capacities allotted to that salesperson. However, while an administrator is using that user system to interact with system 516, that user system has the capacities allotted to that administrator. In systems with a hierarchical role model, users at one permission level may have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users will have different capabilities with regard to accessing and modifying application and database information, depending on a user's security or permission level.


Network 514 is any network or combination of networks of devices that communicate with one another. For example, network 514 can be any one or any combination of a LAN (local area network), WAN (wide area network), telephone network, wireless network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. As the most common type of computer network in current use is a TCP/IP (Transfer Control Protocol and Internet Protocol) network, such as the global internetwork of networks often referred to as the “Internet” with a capital “I,” that network will be used in many of the examples herein. However, it should be understood that the networks that one or more implementations might use are not so limited, although TCP/IP is a frequently implemented protocol.


User systems 512 might communicate with system 516 using TCP/IP and, at a higher network level, use other common Internet protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTP is used, user system 512 might include an HTTP client commonly referred to as a “browser” for sending and receiving HTTP messages to and from an HTTP server at system 516. Such an HTTP server might be implemented as the sole network interface between system 516 and network 514, but other techniques might be used as well or instead. In some implementations, the interface between system 516 and network 514 includes load sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a plurality of servers. At least as for the users that are accessing that server, each of the plurality of servers has access to the MTS' data; however, other alternative configurations may be used instead.


In one embodiment, system 516, shown in FIG. 5, implements a web-based customer relationship management (CRM) system. For example, in one embodiment, system 516 includes application servers configured to implement and execute CRM software applications as well as provide related data, code, forms, webpages and other information to and from user systems 512 and to store to, and retrieve from, a database system related data, objects, and Webpage content. With a multi-tenant system, data for multiple tenants may be stored in the same physical database object, however, tenant data typically is arranged so that data of one tenant is kept logically separate from that of other tenants so that one tenant does not have access to another tenant's data, unless such data is expressly shared. In certain embodiments, system 516 implements applications other than, or in addition to, a CRM application. For example, system 516 may provide tenant access to multiple hosted (standard and custom) applications, including a CRM application. User (or third party developer) applications, which may or may not include CRM, may be supported by the application platform 518, which manages creation, storage of the applications into one or more database objects and executing of the applications in a virtual machine in the process space of the system 516.


One arrangement for elements of system 516 is shown in FIG. 5, including a network interface 520, application platform 518, tenant data storage 522 for tenant data 523, system data storage 524 for system data 525 accessible to system 516 and possibly multiple tenants, program code 526 for implementing various functions of system 516, and a process space 528 for executing MTS system processes and tenant-specific processes, such as running applications as part of an application hosting service. Additional processes that may execute on system 516 include database indexing processes.


Several elements in the system shown in FIG. 5 include conventional, well-known elements that are explained only briefly here. For example, each user system 512 could include a desktop personal computer, workstation, laptop, PDA, cell phone, or any wireless access protocol (WAP) enabled device or any other computing device capable of interfacing directly or indirectly to the Internet or other network connection. User system 512 typically runs an HTTP client, e.g., a browsing program, such as Microsoft's Internet Explorer browser, Netscape's Navigator browser, Opera's browser, or a WAP-enabled browser in the case of a cell phone, PDA or other wireless device, or the like, allowing a user (e.g., subscriber of the multi-tenant database system) of user system 512 to access, process and view information, pages and applications available to it from system 516 over network 514. Each user system 512 also typically includes one or more user interface devices, such as a keyboard, a mouse, trackball, touch pad, touch screen, pen or the like, for interacting with a graphical user interface (GUI) provided by the browser on a display (e.g., a monitor screen, LCD display, etc.) in conjunction with pages, forms, applications and other information provided by system 516 or other systems or servers. For example, the user interface device can be used to access data and applications hosted by system 516, and to perform searches on stored data, and otherwise allow a user to interact with various GUI pages that may be presented to a user. As discussed above, embodiments are suitable for use with the Internet, which refers to a specific global internetwork of networks. However, it should be understood that other networks can be used instead of the Internet, such as an intranet, an extranet, a virtual private network (VPN), a non-TCP/IP based network, any LAN or WAN or the like.


According to one embodiment, each user system 512 and all of its components are operator configurable using applications, such as a browser, including computer code run using a central processing unit such as an Intel Pentium® processor or the like. Similarly, system 516 (and additional instances of an MTS, where more than one is present) and all of their components might be operator configurable using application(s) including computer code to run using a central processing unit such as processor system 517, which may include an Intel Pentium® processor or the like, and/or multiple processor units. A computer program product embodiment includes a machine-readable storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the embodiments described herein. Computer code for operating and configuring system 516 to intercommunicate and to process webpages, applications and other data and media content as described herein are preferably downloaded and stored on a hard disk, but the entire program code, or portions thereof, may also be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disk (DVD), compact disk (CD), microdrive, and magneto-optical disks, and magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, e.g., over the Internet, or from another server, as is well known, or transmitted over any other conventional network connection as is well known (e.g., extranet, VPN, LAN, etc.) using any communication medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for implementing embodiments can be implemented in any programming language that can be executed on a client system and/or server or server system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).


According to one embodiment, each system 516 is configured to provide webpages, forms, applications, data and media content to user (client) systems 512 to support the access by user systems 512 as tenants of system 516. As such, system 516 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (e.g., in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (e.g., one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically and/or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to include a computer system, including processing hardware and process space(s), and an associated storage system and database application (e.g., OODBMS or RDBMS) as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database object described herein can be implemented as single databases, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and might include a distributed database or storage network and associated processing intelligence.



FIG. 6 also illustrates environment 510. However, in FIG. 6 elements of system 516 and various interconnections in an embodiment are further illustrated. FIG. 6 shows that user system 512 may include processor system 512A, memory system 512B, input system 512C, and output system 512D. FIG. 6 shows network 514 and system 516. FIG. 6 also shows that system 516 may include tenant data storage 522, tenant data 523, system data storage 524, system data 525, User Interface (UI) 630, Application Program Interface (API) 632, PL/SOQL 634, save routines 636, application setup mechanism 638, applications servers 6001-400N, system process space 602, tenant process spaces 604, tenant management process space 610, tenant storage area 612, user storage 614, and application metadata 616. In other embodiments, environment 510 may not have the same elements as those listed above and/or may have other elements instead of, or in addition to, those listed above.


User system 512, network 514, system 516, tenant data storage 522, and system data storage 524 were discussed above in FIG. 5. Regarding user system 512, processor system 512A may be any combination of one or more processors. Memory system 512B may be any combination of one or more memory devices, short term, and/or long term memory. Input system 512C may be any combination of input devices, such as one or more keyboards, mice, trackballs, scanners, cameras, and/or interfaces to networks. Output system 512D may be any combination of output devices, such as one or more monitors, printers, and/or interfaces to networks. As shown by FIG. 6, system 516 may include a network interface 520 (of FIG. 5) implemented as a set of HTTP application servers 600, an application platform 518, tenant data storage 522, and system data storage 524. Also shown is system process space 602, including individual tenant process spaces 604 and a tenant management process space 610. Each application server 600 may be configured to tenant data storage 522 and the tenant data 523 therein, and system data storage 524 and the system data 525 therein to serve requests of user systems 512. The tenant data 523 might be divided into individual tenant storage areas 612, which can be either a physical arrangement and/or a logical arrangement of data. Within each tenant storage area 612, user storage 614 and application metadata 616 might be similarly allocated for each user. For example, a copy of a user's most recently used (MRU) items might be stored to user storage 614. Similarly, a copy of MRU items for an entire organization that is a tenant might be stored to tenant storage area 612. A UI 630 provides a user interface and an API 632 provides an application programmer interface to system 516 resident processes to users and/or developers at user systems 512. The tenant data and the system data may be stored in various databases, such as one or more Oracle™ databases.


Application platform 518 includes an application setup mechanism 638 that supports application developers' creation and management of applications, which may be saved as metadata into tenant data storage 522 by save routines 636 for execution by subscribers as one or more tenant process spaces 604 managed by tenant management process 610 for example. Invocations to such applications may be coded using PL/SOQL 634 that provides a programming language style interface extension to API 632. A detailed description of some PL/SOQL language embodiments is discussed in commonly owned U.S. Pat. No. 7,730,478 entitled, “Method and System for Allowing Access to Developed Applicants via a Multi-Tenant Database On-Demand Database Service”—issued Jun. 1, 2010 to Craig Weissman, which is incorporated in its entirety herein for all purposes. Invocations to applications may be detected by one or more system processes, which manage retrieving application metadata 616 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.


Each application server 600 may be communicably coupled to database systems, e.g., having access to system data 525 and tenant data 523, via a different network connection. For example, one application server 6001 might be coupled via the network 514 (e.g., the Internet), another application server 600N-1 might be coupled via a direct network link, and another application server 600N might be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are typical protocols for communicating between application servers 600 and the database system. However, it will be apparent to one skilled in the art that other transport protocols may be used to optimize the system depending on the network interconnect used.


In certain embodiments, each application server 600 is configured to handle requests for any user associated with any organization that is a tenant. Because it is desirable to be able to add and remove application servers from the server pool at any time for any reason, there is preferably no server affinity for a user and/or organization to a specific application server 600. In one embodiment, therefore, an interface system implementing a load balancing function (e.g., an F5 Big-IP load balancer) is communicably coupled between the application servers 600 and the user systems 512 to distribute requests to the application servers 600. In one embodiment, the load balancer uses a least connections algorithm to route user requests to the application servers 600. Other examples of load balancing algorithms, such as round robin and observed response time, also can be used. For example, in certain embodiments, three consecutive requests from the same user could hit three different application servers 600, and three requests from different users could hit the same application server 600. In this manner, system 516 is multi-tenant, wherein system 516 handles storage of, and access to, different objects, data and applications across disparate users and organizations.


As an example of storage, one tenant might be a company that employs a sales force where each salesperson uses system 516 to manage their sales process. Thus, a user might maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (e.g., in tenant data storage 522). In an example of a MTS arrangement, since all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system having nothing more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, if a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates as to that customer while waiting for the customer to arrive in the lobby.


While each user's data might be separate from other users' data regardless of the employers of each user, some data might be organization-wide data shared or accessible by a plurality of users or all of the users for a given organization that is a tenant. Thus, there might be some data structures managed by system 516 that are allocated at the tenant level while other data structures might be managed at the user level. Because an MTS might support multiple tenants including possible competitors, the MTS should have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that may be implemented in the MTS. In addition to user-specific data and tenant specific data, system 516 might also maintain system level data usable by multiple tenants or other data. Such system level data might include industry reports, news, postings, and the like that are sharable among tenants.


In certain embodiments, user systems 512 (which may be client systems) communicate with application servers 600 to request and update system-level and tenant-level data from system 516 that may require sending one or more queries to tenant data storage 522 and/or system data storage 524. System 516 (e.g., an application server 600 in system 516) automatically generates one or more SQL statements (e.g., one or more SQL queries) that are designed to access the desired information. System data storage 524 may generate query plans to access the requested data from the database.


Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined categories. A “table” is one representation of a data object, and may be used herein to simplify the conceptual description of objects and custom objects. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or record of a table contains an instance of data for each category defined by the fields. For example, a CRM database may include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table might describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some multi-tenant database systems, standard entity tables might be provided for use by all tenants. For CRM database applications, such standard entities might include tables for Account, Contact, Lead, and Opportunity data, each containing pre-defined fields. It should be understood that the word “entity” may also be used interchangeably herein with “object” and “table”.


In some multi-tenant database systems, tenants may be allowed to create and store custom objects, or they may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. U.S. patent application Ser. No. 10/817,161, filed Apr. 2, 2004, entitled “Custom Entities and Fields in a Multi-Tenant Database System”, and which is hereby incorporated herein by reference, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In certain embodiments, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.


Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.


While the invention has been described in terms of several embodiments, those skilled in the art will recognize that the invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. The description is thus to be regarded as illustrative instead of limiting.

Claims
  • 1. A method comprising: receiving, with a computing platform having one or more processors coupled with at least one physical memory device, a database query to be executed on the computing platform against a database;analyzing the database query with at least a tuning query recommendation engine provided at least by the one or more processors to determine one or more potential indexes to be evaluated, wherein the one or more potential indexes comprise a set of custom indexes and native skinny indexes that could be built on columns that are filtered or sorted on in the query;evaluating, with the tuning query recommendation engine, the one or more potential indexes to determine if an optimization utilizing a selected potential index provides improved performance over performing the database query without the selected potential index by performing, for each potential index, an evaluation with sampled pre-queries to estimate selectivity of the corresponding potential index;scoring the one or more potential indexes based on results of the evaluating with the tuning query recommendation engine;providing, with the tuning query recommendation engine, a recommendation of one or more of the potential indexes to a source of the database query via a query plan user interface configured to receive user input, wherein the user interface provides at least a cardinality and a table size for the tables to which recommendations correspond and one or more recommended potential indexes that would perform better than an existing best option based on existing indexes, wherein the user interface further provides indications of which tables various recommendations can be applied and indications of which fields to which various recommendations can be applied; andbuilding, with the tuning query recommendation engine, at least one of the one or more potential indexes in response to a received indication.
  • 2. The method of claim 1 wherein the one or more potential indexes comprise a set of all custom indexes and skinny indexes that can be built from columns that are filtered or sorted on in the database query.
  • 3. The method of claim 1 wherein evaluating the selected potential index comprises using a sampled pre-query against a fixed size portion of the database table to estimate a selectivity of the selected potential index.
  • 4. The method of claim 1 wherein providing the recommendation comprises providing a graphical recommendation via a graphical user interface corresponding to the source of the database query.
  • 5. The method of claim 1 wherein providing the recommendation comprises automatically building the recommended potential indexes.
  • 6. The method of claim 1 wherein evaluating the selected potential index comprises evaluating an index that is a result of an index join of one or more potential indexes and zero or more existing indexes.
  • 7. A non-transitory computer-readable medium having stored thereon instructions that, when executed by one or more processors, are configurable to cause the one or more processors to: receive a database query to be executed on the computing platform against a database;analyze the database query with at least a tuning query recommendation engine provided at least by the one or more processors to determine one or more potential indexes to be evaluated, wherein the one or more potential indexes comprise a set of custom indexes and native skinny indexes that could be built on columns that are filtered or sorted on in the query;evaluate, with the tuning query recommendation engine, the one or more potential indexes to determine if an optimization utilizing a selected potential index provides improved performance over performing the database query without the selected potential index by performing, for each potential index, an evaluation with sampled pre-queries to estimate selectivity of the corresponding potential index;score the one or more potential indexes based on results of the evaluating with the tuning query recommendation engine;provide, with the tuning query recommendation engine, a recommendation of one or more of the potential indexes to a source of the database query via a query plan user interface configured to receive user input, wherein the user interface provides at least a cardinality and a table size for the tables to which recommendations correspond and one or more recommended potential indexes that would perform better than an existing best option based on existing indexes, wherein the user interface further provides indications of which tables various recommendations can be applied and indications of which fields to which various recommendations can be applied; andbuild, with the tuning query recommendation engine, at least one of the one or more potential indexes in response to a received indication.
  • 8. The non-transitory computer-readable medium of claim 7 wherein the one or more potential indexes comprise a set of all custom indexes and skinny indexes that can be built from columns that are filtered or sorted on in the database query.
  • 9. The non-transitory computer-readable medium of claim 7 wherein evaluating the selected potential index comprises using a sampled pre-query against a fixed size portion of the database table to estimate a selectivity of the selected potential index.
  • 10. The non-transitory computer-readable medium of claim 7 wherein providing the recommendation comprises providing a graphical recommendation via a graphical user interface corresponding to the source of the database query.
  • 11. The non-transitory computer-readable medium of claim 7 wherein providing the recommendation comprises automatically building the recommended potential indexes.
  • 12. The non-transitory computer-readable medium of claim 7 wherein evaluating the selected potential index comprises evaluating an index that is a result of an index join of one or more potential indexes and zero or more existing indexes.
  • 13. A system comprising: at least one memory device;one or more processors coupled with the at least one memory device, the one or more processors to execute code configurable to receive a database query to be executed on the computing platform against a database, to analyze the database query with at least a tuning query recommendation engine provided at least by the one or more processors to determine one or more potential indexes to be evaluated, wherein the one or more potential indexes comprise a set of custom indexes and native skinny indexes that could be built on columns that are filtered or sorted on in the query, to evaluating, with the tuning query recommendation engine, the one or more potential indexes to determine if an optimization utilizing a selected potential index provides improved performance over performing the database query without the selected potential index by performing, for each potential index, an evaluation with sampled pre-queries to estimate selectivity of the corresponding potential index, to score the one or more potential indexes based on results of the evaluating with the tuning query recommendation engine, to provide, with the tuning query recommendation engine, a recommendation of one or more of the potential indexes to a source of the database query via a query plan user interface configured to receive user input, wherein the user interface provides at least a cardinality and a table size for the tables to which recommendations correspond and one or more recommended potential indexes that would perform better than an existing best option based on existing indexes, wherein the user interface further provides indications of which tables various recommendations can be applied and indications of which fields to which various recommendations can be applied, and to build, with the tuning query recommendation engine, at least one of the one or more potential indexes in response to a received indication.
  • 14. The system of claim 13 wherein the one or more potential indexes comprise a set of all custom indexes and skinny indexes that can be built from columns that are filtered or sorted on in the database query.
  • 15. The system of claim 13 wherein evaluating the selected potential index comprises using a sampled pre-query against a fixed size portion of the database table to estimate a selectivity of the selected potential index.
  • 16. The system of claim 13 wherein providing the recommendation comprises providing a graphical recommendation via a graphical user interface corresponding to the source of the database query.
  • 17. The system of claim 13 wherein providing the recommendation comprises automatically building the recommended potential indexes.
  • 18. The system of claim 13 wherein evaluating the selected potential index comprises evaluating an index that is a result of an index join of one or more potential indexes and zero or more existing indexes.
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Number Date Country
20180107714 A1 Apr 2018 US