Abstract: Systems and methods for generating a machine-learning (ML) model for extracting information from one or more electronic documents, where the ML model can be used as a data object, which can be part of a database command or as part of a document information extraction process that is continuously running (e.g., document information extraction pipeline).

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

Abstract: Systems, methods, and devices for sharing materialized views in multiple tenant database systems. A method includes defining a materialized view over a source table that is associated with a first account of a multiple tenant database. The method includes defining cross-account access rights to the materialized view to a second account such that that second account can read the materialized view without copying the materialized view. The method includes modifying the source table for the materialized view. The method includes identifying whether the materialized view is stale with respect to the source table by merging the materialized view and the source table.

Abstract: Systems and methods for an organization-level account for an organization on a data platform, users of which can possess administrative or management privileges with respect to the organization and across one or more others accounts of the organization.

Abstract: Techniques for identity resolution and data enrichment include configuring, during an onboarding process at an account of a data provider, at least one parameter associated with access to identity resolution functions by an account of a data consumer. A first shared data object is generated at the account of the data provider. The first shared data object corresponds to a second shared data object at the account of the data consumer. The second shared data object at the account of the data consumer is enabled for sharing of log data associated with an application executing at the account of the data consumer. The application is enabled for an identity resolution process based on the detecting of the second shared data object. Source data associated with the identity resolution functions is encoded for communication to the application at the account of the data consumer based on the enabling.

Abstract: Provided herein are systems and methods for configuring trace events. A system includes at least one hardware processor coupled to a memory and configured to instantiate a user code runtime to execute user-defined function (UDF) code. The user code runtime is instantiated within a sandbox process of an execution node. An application programming interface (API) call is detected during execution of the UDF code. The API call includes one or more configurations of a trace event. Telemetry information is collected based on the one or more configurations. The telemetry information is associated with the trace event using a telemetry API. The telemetry API corresponds to the API call. The telemetry information is formatted using the telemetry API, to generate structured telemetry information. The at least one hardware processor causes ingestion of the structured telemetry information into an event table.

Abstract: Sub-plans are executed in parallel using a plurality of execution nodes, which can be part of a data platform. In particular, various embodiments identify sub-plans (e.g., fragments or portions of one or more child operators) of a root operator in a query plan such that the identified sub-plans that are candidates for execution on a single execution node, determine a cost estimate for causing the candidate sub-plans to be executed in parallel using multiple execution nodes, and cause the candidate sub-plans to be executed in parallel based on the cost estimate.

Abstract: The subject technology receives a command to commit a table in a different table format on an external volume. The subject technology generates a first snapshot of the table on internal storage. The subject technology generates a first list of metadata files on the internal storage. The subject technology generates, based on the first list of metadata files, a first set of metadata files on the internal storage. The subject technology generates a second snapshot of the table on the external volume. The subject technology generates a second list of metadata files on the external volume. The subject technology generates, based on the second list of metadata files, a second set of metadata files on the external volume. The subject technology generates a first set of data files in a different file format on the external volume.

Abstract: The subject technology inserts, by a first transaction, a new version of an object, the first transaction including a first statement to perform an update operation to a row in a first table, the object corresponding to data in the row to be updated, the first statement including information comprising an object key associated with the object. The subject technology performs, by a second transaction, a range read, the range read including information indicating the object key. The subject technology receives a set of conflicting transactions from the range read. The subject technology determines that a conflict occurred between the first transaction and a third transaction from the set of conflicting transactions. The subject technology performs a restart of the first transaction in response to determining that the conflict occurred.

Abstract: The subject technology provides embodiments for enabling derivation of predicates not only from other predicates but also from metadata such as expression properties. In examples, predicates are derived, avoiding unwanted impact on cardinality estimation. In other examples, predicates are derived, avoiding artificial runtime errors and providing a way to avoid security issues with secure views.

Abstract: A source table organized into a set of batch units is accessed. The source table comprises a column of data corresponding to a semi-structured data type. One or more indexing transformations for an object in the column are generated. The generating of the one or more indexing transformation includes converting the object to one or more stored data types. A pruning index is generated for the source table based in part on the one or more indexing transformations. The pruning index comprises a set of filters that index distinct values in each column of the source table, and each filter corresponds to a batch unit in the set of batch units. The pruning index is stored in a database with an association with the source table.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for sharing, on a distributed database, a database application to a first user of the distributed database, the database application generated by a second user of the distributed database. The training dataset includes a first database training dataset from the first user of the distributed database and a second database training dataset from the second user of the distributed database, the first database training dataset and the second database training dataset including non-overlapping dataset features. The database application further identifies a query from the second user to train the machine learning model on the training dataset and generates a trained machine learning model by training the machine learning model on a joined dataset according to the query. The database application generates outputs from the trained machine learning model by applying the trained machine learning model on new data.

Abstract: A streaming ingest platform can improve latency and expense issues related to uploading data into a cloud data system. The streaming ingest platform can organize the data to be ingested into per-table chunks and per-account blobs. This data may be committed and may be made available for query processing before it is ingested into the target source tables. This significantly improves latency issues. The streaming ingest platform can also accommodate uploading data from various sources with different processing and communication capabilities, such as Internet of Things (IOT) devices.

Abstract: Techniques are described for budget tracking in a differentially private security system. A request to perform a query of a private database system is received by a privacy device from a client device. The request is associated with a level of differential privacy. A privacy budget corresponding to the received request is accessed by the privacy device. The privacy budget includes a cumulative privacy spend and a maximum privacy spend, the cumulative privacy spend representative of previous queries of the private database system. A privacy spend associated with the received request is determined by the privacy device based at least in part on the level of differential privacy associated with the received request. If a sum of the determined privacy spend and the cumulative privacy spend is less than the maximum privacy spend, the query is performed. Otherwise a security action is performed based on a security policy.

Abstract: A method of implementing object tagging framework starts with the processor receiving a tag creation command including a tag name. In response to the tag creation command, the processor creates a current tag. The processor then receives an association command, the tag name and a source object identifier. The processor determines a source object associated with the source object identifier. The source object includes a tag value. The processor associates the current tag with the source object. The processor receives a replication command including the source object and a target object. The processor causes replication of the source object to the target object that comprises replicating the current tag with the tag name and the tag value in the source object to the target object. Other embodiments are also described herein.

Abstract: A process of fulfilling a database deployment request for a data platform. A compute service manager of the data platform scans one or more accounts of a consumer region of the data platform for a pending listing fulfillment request, where the pending listing request includes a request for deployment of a consumer database and an associated share of grant metadata of the consumer database within the consumer region. When the compute service manager determines that an account of the one or more accounts has a pending listing fulfillment request, the compute service manager determines a listing for the pending listing fulfillment request based on listing data of the account. The compute service manager determines that no other fulfillment task is scheduled for the pending listing fulfillment request and schedules a background fulfillment task to perform the fulfillment process for the pending listing fulfillment request.

Abstract: An in-database application package and application instance for a data platform. The data platform creates an application instance of an application package having a versioned schema, creates one or more system roles for the application instance, creates a user role and an administrator role for the application instance, creates one or more objects of the application instance based on a versioned schema, and grants one or more use privileges to the one or more roles. Application instances of the application package are upgraded or patched on the data platform based on application package versions. To ensure a proper upgrade or patch, the data platform tracks versions of executing objects of application instances in a call context.

Abstract: A top K query directed at a table is received. The table is organized into multiple storage units. The top K query comprises a first clause to sort a result set in order and a second clause that specifies a limit on a number of results provided in response to the query. A table scan operator identifies a first set of rows from the table based on a scan set determined for the table and provides the first set of rows to a top K operator. The top K operator determines a current boundary based on the first set of rows and provides the current boundary to the table scan operator. The table scan operator prunes the scan set based on the current boundary and identifies a second set of rows from the table based on the pruning.

Abstract: Various embodiments provide for tag-based application of a masking policy, which can be used in connection with a data platform. In particular, various embodiments enable enforcement of one or more masking policies against an entity (e.g., object) of a data platform, such as a database, a table, a row, or a column, based on one or more tags associated with the entity.

Abstract: The subject technology receives, from a metadata database, information related to a base table. The subject technology determines a table object associated with the base table, the table object including a first set of metadata. The subject technology generates a nested object based on a second set of metadata, the second set of metadata including information linking the nested object to the table object. The subject technology generates a second table object associated with the nested object, the second table object representing a secondary index of the base table, the second table object including information linking the second table object to the nested object. The subject technology establishes a link between the second table object to the base table based on the nested object. The subject technology stores, in the metadata database, the nested object and the second table object.