Systems and methods are disclosed for generating a distributed execution model with untrusted commands. The system can receive a query, and process the query to identify the untrusted commands. The system can use data associated with the untrusted command to identify one or more files associated with the untrusted command. Based on the files, the system can generate a data structure and include one or more identifiers associated with the data structure in the distributed execution model. The system can distribute the distributed execution model to one or more nodes in a distributed computing environment for execution.

Systems and methods are disclosed for making space available in a local storage of a data intake and query system. A cache manager of the data intake and query system may determine an amount of storage space of a local data store that is available for use to perform a query. The cache manager may then use one or more eviction policies associated with content stored at the local data store to purge content items to evict from the local storage. The system may then retrieve content for performing the query from a remote storage and store the retrieved content at the local storage.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a template for a content item. In one aspect, a method includes receiving a content item request that includes context data. A content item that is eligible to be presented in response to the content item request is identified. A determination is made that the content item includes a template variable that is resolved based on the context data. A template feed including a set of templates is identified based on the template variable. A template is selected from the template feed for the content item. The template can be selected based on the context data. The selected template is populated with content for the content item to create a formatted content item. The formatted content item is provided in response to the content item request.

When a DBMS receives a suspend instruction in which a suspend completion time of query processing is a future time and between receipt of the suspend instruction and the suspend completion time, if there is a target object (at least a processing object whose execution is in progress upon receipt of the suspend instruction) whose predicted completion time is at or precedes the suspend completion time, the DBMS changes the state of the target object to a state signifying a snapshot suspend. If there is a processing object whose state signifies a snapshot suspend, the DBMS executes the processing object at or before the suspend completion time.

A method for detecting a traffic ramp-up rule violation includes receiving data element retrieval requests from an information retrieval system and determining a requests per second (RPS) for a key range. The method also includes determining a moving average of RPS for the key range. The method also includes determining a number of delta violations, each delta violation comprising a respective beginning instance in time when the RPS exceeded a delta RPS limit. For each delta violation, the method includes determining a maximum conforming load for the key range over and determining whether the RPS exceeded the maximum conforming load for the key range based on the beginning instance in time of the respective delta violation. When the RPS has exceeded the maximum conforming load, the method includes determining that the delta violation corresponds to a full-history violation indicative of a degradation of performance of the information retrieval system.

A processing system including at least one processor may obtain a first set of performance records of a database system, train a machine learning model in accordance with the first set of performance records, where the machine learning model that is trained in accordance with the first set of performance records is configured to predict a latency of a query transaction for a designated time period, present a user interface with a plurality of settings of the database system that are user-adjustable, where the plurality of settings is associated with at least a portion of the first set of performance records, calculate a first predicted latency of a query transaction at the designated time period via the machine learning model in accordance with a set of values of the plurality of settings, and present the first predicted latency via the user interface.

A computer-implemented method provides application-based query transformations. The method includes determining an application is initiated. The method includes identifying a set of execution units included in the application. The execution units are based on of a set of queries in the application and a set of actions in the application. The method also includes building a query dependency graph (QDG) comprising a plurality of nodes, wherein each node of the plurality of nodes is correlated to an execution unit, and each node is linked to at least one additional node, the link indicating a relative execution order and a common attribute each node and the additional node. The method includes merging, based on a performance architecture, two or more of the set of execution units into a section. The method includes processing the application according to the QDG.

Provided are methods and systems for searching event sequences. An example method includes receiving a request including a sequence of queries, the sequence of queries including a first query and a second query, the second query succeeding the first query in the sequence; executing the first query over a first dataset to determine a first event; executing the second query over a second dataset to determine a second event, the second event occurring after the first event; and generating, in response to the request, a further sequence including the first event and the second event. The method may include executing the first query over the first dataset to determine a third event and verifying that the third event has occurred after the second event.

A method is disclosed, involving converting each structured text document stored in a database into a vector, building a search index using the one or more vectors of the structured text documents stored in the database, then receiving a new structured text document, converting the structured text document into a vector, then searching the search index using the one or more vectors of the new structured text document, and generating a list of N structured text document from the database similar to the new structured text document based on said search

According to examples, an apparatus may include a processor and a memory on which are stored machine-readable instructions that when executed by the processor cause the processor to receive parameters for a partition range for a partition key associated with a table. The table may have a vertical table structure. The processor may generate an index of vertical table columns based on the received parameters for the partition range. The generated index may be a physical store for data from the table and may have a subset of rows of the table correlating to the partition range. The processor may receive a query having a predicate associated with the partition key associated with the table and, based on a determination that the predicate included in the received query is within a partition range for the generated index, the processor may execute the query using the generated index.