An approach is provided for evaluating a performance of a query. A risk of selecting a low performance access path for a query is determined. The risk is determined to exceed a risk threshold. Based on the risk exceeding the risk threshold and using a machine learning optimizer, first costs of access paths for the query are determined. Using a cost-based database optimizer, second costs of the access paths are determined. Using a strong classifier operating on the first costs and the second costs, a final access path for the query is selected from the access paths.

Methods and systems for analyzing data are described. In one embodiment, a method comprises a processor receiving a data analysis algorithm over a network and executing the data analysis algorithm, the data analysis algorithm analyzing data stored in a database using machine learning to identify a database organizational format, the data analysis algorithm identifying one or more locations for a set of data stored on the database based on identifying the database organizational format, the data analysis algorithm parsing the set of data to identify whether any entries in the database associated with the set of data includes a particular value, and the data analysis algorithm communicating over the network at least a first number of entries in the database that include the particular value and a second number of entries in the database that do not include the particular value.

The present disclosure discloses a task processing method and a distributed computing framework. A specific embodiment of the method includes: parsing an expression corresponding to a distributed computing task, and constructing task description information corresponding to the distributed computing task, the task description information being used to describe a corresponding relationship between an operator and a distributed dataset, and the operator acting on at least one of the distributed dataset or distributed datasets obtained by grouping the distributed dataset; determining, based on the task description information, a distributed dataset the operator acting on; and performing distributed computing on the distributed dataset the operator acting on using the operator. In the distributed computing, the acting scope and nesting relationship of the operator is described by constructing a topology.

Disclosed embodiments include a method performed by server computer(s). The method includes receiving a query and defining a query plan based on the received query. The query plan refers to datasets contained in data sources. The method further includes determining that the received query can be accelerated based on an optimized data structure contained in a memory, where the optimized data structure is derived from a dataset referred to in the query plan. The method further includes modifying the query plan to include the optimized data structure, and executing the modified query plan to obtain query results that satisfy the received query by reading the optimized data structure in lieu of reading at least some data from the data sources.

Network elements are managed with a server to support client data models from heterogeneous data sources. A server receives a first query for configuration data of a network element to be returned in a first model. The server determines a model type for the configuration data of the network element. When the model type is a second model that is not the first model, the server sends a second query to the network element for the configuration data to be returned in the second model and transforms the configuration data received from the network element into the first model. Additionally, the server returns the configuration data in the first model as a response to the first query.

Network elements are managed with a server to support client data models from heterogeneous data sources. A server receives a first query for configuration data of a network element to be returned in a first model. The server determines a model type for the configuration data of the network element. When the model type is a second model that is not the first model, the server sends a second query to the network element for the configuration data to be returned in the second model and transforms the configuration data received from the network element into the first model. Additionally, the server returns the configuration data in the first model as a response to the first query.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for precisely tracking memory usage in a multi-process computing environment. One of the methods includes implementing an instance of a memory usage tracker (MUT) in each process running in a node of a computer system. A MUT can maintain an account of memory usage for each of multiple logical owners running on a process on which the MUT is running. The MUT can determine an actual memory quota for each owner, and enforce the actual memory quota of the owner. Enforcing the actual memory quota of the owner can include receiving each memory allocation request, checking each allocation request and a current state of the account against the actual quota, approving or rejecting each allocation request, communicating the approval or rejection to an underlying memory manager, and updating the owner account for each approved allocation request.

Methods, systems, and devices supporting querying disparate data sources are described. Querying disparate data sources may include receiving an input for data stored at a first data source from a plurality of data sources, selecting a first data connector from a plurality of data connectors, wherein the first data connector corresponds to the first data source, and identifying a first query language corresponding to the first data source from a plurality of query languages. Querying the disparate data sources may further include generating a converted query based at least in part on the first query language and retrieving the data from the first data source using the first data connector based at least in part on the converted query.

Methods, systems, and devices supporting querying disparate data sources are described. Querying disparate data sources may include receiving an input for data stored at a first data source from a plurality of data sources, selecting a first data connector from a plurality of data connectors, wherein the first data connector corresponds to the first data source, and identifying a first query language corresponding to the first data source from a plurality of query languages. Querying the disparate data sources may further include generating a converted query based at least in part on the first query language and retrieving the data from the first data source using the first data connector based at least in part on the converted query.

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform using a plugin system in a user interface to identify each ingredient in an ingredient list of a recipe published on a webpage shown on the user interface; identifying query strings from content on the webpage associated with one or more ingredients of the recipe; identifying one or more respective recipe products and a respective quantity for each of the one or more ingredients; locating a respective catalog product in an online catalog for each of the one or more respective recipe products; automatically generating a list of catalog products; automatically generating a link comprising the list of catalog products; automatically redirecting the user interface to an online retail website; and automatically adding the list of catalog products to an electronic shopping cart. Other embodiments are disclosed.