Salesforce Com, Inc.

Salesforce, Inc.

Jesse Yarbro Collins

Jaikumar Bathija

Alan Arbizu

Craig David Weissman

Arup Dutta

Scott Hansma

Hoon Y Kim

Chirag Rajan

Greg Salmon

Prem Veeramani

Simon Y Wong

Ronald Yang

Anant Kumar Verma

Chris Hopkins

Rohitashva Mathur

William Charles Eidson

Andrey Dmitriyevich Gusev

John F O'Brien

Vijayanth Devadhar

Mikhail Chainani

Thomas J Tobin

Olumayokun Obembe

Ashwini Bijwe

Sridevi Gopala Krishnan

Thomas Kim

Chen Liu

Ping-Hsiu Hsieh

Awais Tariq

Eric David Bezar

Walter Macklem

Mark Fischer

Mary Kathryn Scotton

Ted Liu

Youngjin Yu

Donald Tam

Bohan Chen

Sheng Qiao

Seung-Yeoul Yang

Xuerong Tang

Percy Dara Mehta

Karthik Rajan

Jesse S Wang

Kayvaan Ghassemieh

Bing Yang

Dan Soble

Andrea Wildt

Ganesh Maganti

Jeffrey Lallana Freschl

RamaLinga R Penmetsa

Yanan Jiang

Philippe Debaty

RamaLinga Raju Penmetsa

Arup Kumar Dutta

Mang Fu Matthew Wong

Sunghyun Song

Federico Recio

Subhash Uppalapati

Andrey Gusev

Methods and systems for making effective use of system resources. A plurality of requests for access to a resource are received. Each request has an associated group of features. The group of features for each request is analyzed to collect observations about the plurality of requests. A function to predict an outcome of a subsequent request is generated based on the observations. Resources are allocated to service the subsequent request based on the function.

Methods and systems for making effective use of system resources

Systems and methods are described for implementing attribute aware, relationship-based access control by receiving a query to access a relational database from a user, determining if a rule of the relational database is applicable to the query, determining one or more relationships associated with the query based at least in part on the rule, and modifying the query by adding an extra join operation to the query based at least in part on the rule and the one or more relationships. Further, when a type of the rule is row level, a where clause filter is added to the modified query to enforce a condition of the rule, and when the type of the rule is field level, a case column is added to the modified query and a select clause is added to the modified query to wrap the query. The modified query is processed to produce a result.

Attribute aware relationship-based access control on row and field levels in a relational database

Techniques are disclosed relating to creating an index for a database system. In one embodiment, a database system stores data within a plurality of fields in a data table, a subset of the data being associated with a particular one of the plurality of fields. The database system receives a request to index the data table based on the particular field and analyzes the subset of the data. In response to determining, based on the analyzing, that one or more duplicate values are present in the subset of data, the database system sets, in an index table having the particular field, an indication identifying which entries of the index table have a duplicate value for the particular field, and returns a response to the request that specifies the one or more duplicate values. In some embodiments, the response includes a user interface displaying one or more duplicates values.

Detection of duplicate values during index generation

Systems, methods, and computer-readable media for pinning query execution plans are described. A database system may obtain a query, and determine a organization identifier and/or user identifier associated with the query. The database system may identify an optimized plan among a set of query plans that correspond with the query, and may generate a query execution plan based on the query and the optimized plan. The database system may determine a pinned plan that is associated with the optimized plan, and may generate a query execution plan based on the pinned plan when the pinned plan is associated with the optimized plan and corresponds with the organization identifier and/or the user identifier. The database system may generate a query execution plan using optimization functions when the pinned plan is not associated with the pinned plan, or the organization identifier and/or the user identifier. Other embodiments may be described and/or claimed.

Query pin planner

A database query is received at a first time when a database is in a first state. The database query is analyzed to determine whether it has one or more characteristics that fall within a historical top range of database queries. If the database query falls within the historical top range of database queries the query is stored for later query tuning activity. The query is executed against the database in the first state. Query tuning recommendations are generated for stored database queries that fall within the historical top range of database queries. A subsequent request is received at a second time when a database is in a second state. The subsequent database query is executed with at least one of the query tuning recommendations against the database in the second state.

Background processing to provide automated database query tuning

An automated self-healing database system is provided that includes a primary database, an application server that writes data to the primary database and reads data from the primary database when it is available, a standby database that is a replica of the primary database, and a self-healing module (SHM). The SHM can automatically detect unavailability of the primary database, and if the standby database is available, the SHM can automatically enable the standby database as readable and writable, assign the standby database the role of primary database at the primary site to start replicating data to other standby databases, and use a pre-established connection between the application server and the standby database to allow the application server to read data from the standby database and to write data to the standby database resulting in the standby database assuming role of the primary database at the primary site.

Automated self-healing database system and method for implementing the same

Methods and systems for query optimization for a multi-tenant database system are provided. Some embodiments comprise receiving at a network interface of a server in a multi-tenant database system an original query transmitted to the multi-tenant database system by a user associated with a tenant, wherein the original query is associated with data accessible by the tenant, and wherein the multi-tenant database system includes at least a first index and a second index. Metadata associated with the data is retrieved, wherein at least a portion of the data is stored in a common table within the multi-tenant database system. A tenant-selective query syntax is determined by analyzing at least one of metadata generated from information about the tenant or metadata generated from the data accessible by the tenant. An improved query is then generated using the query syntax, wherein the improved query is based at least in part upon the original query and a result of a join between a first number of rows associated with the first index and a second number of rows associated with the second index.

Methods and systems for joining indexes for query optimization in a multi-tenant database

Techniques and architectures to provide multiple application servers each having at least one connection agent and at least one enabler agent and at least one database organized as multiple nodes. An error condition between a first connection agent and a first database node is detected. The first connection agent indicates that the first database node is unavailable to stop attempts to access the first database node by a first application server. A first enabler agent periodically checks availability of the first database node. The first database node is indicated as available in response to a pre-selected number of successful attempts to contact the first database node with the first enabler agent. The first database node is accessed with the application server in response to the indication that the first database node is available.

Techniques and architectures for recovering from a service disruption in a multi-server environment

Methods and systems for query optimization for a multi-tenant database system are provided. Some embodiments comprise receiving, at a network interface of a server computer in a multi-tenant database system, an original query transmitted to the multi-tenant database system by a user associated with a tenant, wherein the original query is associated with data accessible by the tenant, and wherein the multi-tenant database system includes a first two-column custom index. Metadata associated with the data accessible by the tenant is retrieved, using a processor of the server computer, wherein at least a portion of the data accessible by the tenant is stored in a common table within the multi-tenant database system. A tenant-selective query syntax is determined, using the processor, wherein determining comprises analyzing at least one of metadata generated from information about the tenant or metadata generated from the data accessible by the tenant. Finally, using the processor, an improved query is generated using the query syntax, wherein the improved query is based at least in part upon the original query and data stored in the first two-column custom index.

Implementing composite custom indices in a multi-tenant database

Techniques and structures for tuning database queries. Actual statistics associated with data stored are retrieved from at least one memory device. The data is associated with one or more tenants of the multi-tenant database system. The actual statistics include at least one type of statistic maintained for the data. A subset of the actual statistics is selected based on a data trait targeted for optimization. A statistical value is calculated for each actual statistic from the subset of actual statistics across one or more tenants having the data trait targeted for optimization. An optimal query plan is determined based on the original query and the calculated statistical values.

Static query optimization

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.

Automated database query tuning

In an example, a database system may be configured to validate relational database instructions using a plurality of validators. In some examples, validation may be pre-production for relational database instructions based on simulated user inputs and/or file, such as plan files (e.g., PL/SQL (procedural language/structured query language) files). In some examples, validation may be in production for relational database instructions based on system views of a database engine.

Relational database instruction validation

In a computing environment having multiple application servers each having at least one connection agent and at least one pause agent and a database node, detecting an error condition between a first application server from the multiple application servers and the database node. Indicating that the database node is unavailable to stop attempts to access the database node by a first application server. The attempts to access the database node are paused without an indication of the database node being unavailable to a source of the attempt to access the database node. Checking periodically, with the first application server, availability of the database node. Indicating that the database node is available in response to a pre-selected number of successful attempts to contact the database node with the first application server.

Techniques and architectures for managing database failure in a single-node database architecture

Growing community of inventors

Berkeley, CA, United States of America

Jesse Yarbro Collins