Abstract: The subject technology provides embodiments for supporting a unified table which may be a managed table or an unmanaged table. Managed tables are those where the subject technology manages the metastore/catalog for the table, whereas unmanaged tables are tables where an external catalog controls the table and the subject technology integrates with that catalog to work with the table, but does not assume control of the table.

Abstract: A method includes detecting, by at least one hardware processor, a change request for a table of a database, the table comprising a plurality of micro-partitions. A transaction associated with the change request is executed at a first timestamp. The transaction causes replacement of a first micro-partition of the plurality of micro-partitions with a second micro-partition. A change tracking column is generated in the second micro-partition. The change tracking column comprises metadata for the transaction. A delta for the table between the first timestamp and a second timestamp is generated using the metadata in the change tracking column. The delta indicates changes made to one or more rows of the table between the first time stamp and the second timestamp.

Abstract: Systems and methods are provided for controlling the deletion of data in a database system. The system receives input comprising a deletion criterion for a database system. The system applies the deletion criterion to a set of tables of the database system. The system determines that an individual portion of the set of tables satisfies the deletion criterion. In response to determining that the individual portion of the set of tables satisfies the deletion criterion, the system transfers the individual portion of the set of tables to a temporary storage system.

Abstract: Embodiments of the present disclosure related to sharing applications within a data sharing platform. An example method includes replicating a database from a provider account of a data sharing platform to a consumer account of the data sharing platform. The method further includes executing an installation script within the consumer account to install an application in the consumer account of the data sharing platform responsive to the replicating. The method further includes creating, by a processing device, a set of database roles to manage execution of the application in the consumer account, wherein one or more of the set of database roles determine access privileges granted to the application for accessing the database inside the consumer account. The application is to perform a data processing service relative to a data asset in the database.

Abstract: Systems and methods are provided for controlling the deletion of data in a database system. The system receives input comprising a deletion criterion for a database system. The system applies the deletion criterion to a set of tables of the database system. The system determines that an individual portion of the set of tables satisfies the deletion criterion. In response to determining that the individual portion of the set of tables satisfies the deletion criterion, the system transfers the individual portion of the set of tables to a temporary storage system.

Abstract: Provided herein are systems and methods for discrete workload processing using a file processing service. An example method includes retrieving a manifest file from a work queue. The manifest file includes metadata associated with a plurality of workloads. A plurality of processing configurations corresponding to the plurality of workloads is generated. A processing configuration of the plurality of processing configurations is associated with scheduling execution of one or more tasks for a workload of the plurality of workloads. A processing pipeline definition of the manifest file is generated. The processing pipeline definition includes the plurality of processing configurations. The processing pipeline definition is registered with a pipeline definition registry of a network-based database system to generate a definition registration.

Abstract: In one aspect, a computer-implemented method includes detecting a committed version of recurrently executed tasks of a first data pipeline on a primary deployment that is hosted on a first cloud service, and replicating the committed version of the recurrently executed tasks to a second data pipeline on a secondary deployment that is hosted on a second cloud service.

Abstract: The subject technology receives a first set of statements, the first set of statements comprising at least a first statement to create a particular service associated with a container service. Further, the subject technology instantiates the particular service associated with the container service, in response to the first statement, at a first cluster, the first cluster including a first set of worker nodes.

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: Systems and methods are provided for controlling the deletion of data in a database system. The system receives input comprising a deletion criterion for a database system. The system applies the deletion criterion to a set of tables of the database system. The system determines that an individual portion of the set of tables satisfies the deletion criterion. In response to determining that the individual portion of the set of tables satisfies the deletion criterion, the system transfers the individual portion of the set of tables to a temporary storage system.

Abstract: Techniques described herein can accelerate change data capture determinations such as stream reads, which show changes made to a table between two points in time. Three distinct row bitsets that mark deleted, updated, inserted, rows in micro-partitions can be added as metadata for the table. These bitsets can be generated during DML operations and then stored as metadata of the new partition generated by the DML operations. The bitsets can then be used to generate streams showing the changes in the table between two points in time (changes interval).

Abstract: Systems, methods, and devices for tracking a series of changes to database data are disclosed. A method includes executing a transaction to modify data in a micro-partition of a table of a database by generating a new micro-partition that embodies the transaction. The method includes associating transaction data with the new micro-partition, wherein the transaction data comprises a timestamp when the transaction was fully executed, and further includes associating modification data with the new micro-partition that comprises an indication of one or more rows of the table that were modified by the transaction. The method includes joining the transaction data with the modification data to generate joined data and querying the joined data to determine a listing of intermediate modifications made to the table between a first timestamp and a second timestamp.

Abstract: Provided herein are systems and methods for a stream object configuration, including query processing of stream objects using stream expansion. For example, a method includes decoding a query to obtain a first data processing operation and a first stream object. The first stream object is associated with a view on a base table. A first stream expansion on the first stream object is performed. The first stream expansion is based on generating a second stream object on the base table. A second stream expansion of the second stream object is performed. The second stream expansion is based on replacing the second stream object with at least a second data processing operation. The query is executed based on completing the first data processing operation and the at least a second data processing operation.

Abstract: External functions can provide users of a database system the ability to invoke external services while operating from inside the database system. The techniques described herein address may detect throttling by the external system and automatically adjust or modify a request rate accordingly. Also, the techniques described herein may increase the request rate to optimize the use of the resources provided by the external system. These techniques allow the database system to improve efficiency when working with external services, which may or may not be elastic or scalable. Moreover, these techniques can decrease query execution times and reduce costs.

Abstract: Techniques for triggering pipeline execution based on data change (transaction commit) are described. The pipelines can be used for data ingestion or other specified tasks. These tasks can be operational across account, organization, cloud region, and cloud provider boundaries. The tasks can be triggered by commit post-processing. Gates in the tasks can be set up to reference change data capture information. If the gate is satisfied, tasks can be executed to set up data pipelines.

Abstract: System and method for efficiently querying external tables are described herein. In an embodiment, a database platform receives a query that is directed at least in part to external data in an external table stored on a data storage platform that is external to the database platform. The external table includes a plurality of partitions. The database platform identifies, from external-table metadata, a subset of the plurality of partitions of the external table as including data that potentially satisfies the query. The external-table metadata is stored by the database platform. The database platform identifies data that satisfies the query by scanning the identified subset of the partitions, and responds to the query at least in part with the identified data that satisfies the query.

Abstract: Techniques described herein can enable stream replication. A first deployment can store a table including one or more streams. The techniques described herein can be used to replicate the table at a second deployment while replicating the one or more streams associated with the table. Select prior table versions and partitions in the table are copied to the second deployment to enable stream replication.

Abstract: A method includes ingesting, by at least one hardware processor, database data within a staging table of a database. The method further includes generating a task based on at least one data processing statement received from a user account. The method further includes executing the task on the database data in the staging table to generate modified data. The method further includes, in response to the task being fully executed on the database data, storing the modified data in a target table. In some aspects, the target table is configured within the database. The method further includes generating a stream of one or more transactions committed during the execution of the task to generate the modified data.

Abstract: Techniques described herein can accelerate change data capture determinations such as stream reads, which show changes made to a table between two points in time. Three distinct row bitests that mark deleted, updated, inserted, rows in micro-partitions can be added as metadata for the table. These bitsets can be generated during DML operations and then stored as metadata of the new partition generated by the DML operations. The bitsets can then be used to generate streams showing the changes in the table between two points in time (changes interval).

Abstract: A data platform for running a subset of cells in a notebook is provided. The data platform receives a run cells message from a notebook user interface (UI) application specifying the subset of cells to run. For each cell in the subset, the data platform runs the cell to generate a set of results, generates a cell execution stream using the results, stores the stream, and transmits the stream to the notebook UI application. The notebook UI application generates a display for the user using the cell execution stream. The data platform provides an efficient way to run specific cells in a notebook and display the results to the user.