Distributed database systems including compute nodes and page servers are described herein that enable separating logical and physical storage of database files in a distributed database system. A distributed database system includes a page server and a compute node and is configured to store a logical database file that includes data and is associated with a file identifier. Each page server is configurable to store slices (i.e., subportions) of the logical database file. The compute node is coupled to the plurality of page servers and configured to store the logical database file responsive to a received command. In an aspect, such storage may comprise slicing the data comprising the logical database file into a set of slices with each being associated with a respective page server, maintaining an endpoint mapping for each slice of the first set of slices, and transmitting each slice to the associated for storage thereby.

Method and apparatus for stress management in a searchable data service. The searchable data service may provide a searchable index to a backend data store, and an interface to build and query the searchable index, that enables client applications to search for and retrieve locators for stored entities in the backend data store. Embodiments of the searchable data service may implement a distributed stress management mechanism that may provide functionality including, but not limited to, the automated monitoring of critical resources, analysis of resource usage, and decisions on and performance of actions to keep resource usage within comfort zones. In one embodiment, in response to usage of a particular resource being detected as out of the comfort zone on a node, an action may be performed to transfer at least part of the resource usage for the local resource to another node that provides a similar resource.

Systems, methods, and computer-readable media are disclosed for an improved database. The systems, methods, and computer-readable media described herein may enhance the response time of databases and improve user experiences. In an example method described herein, a database monitoring system may receive instructions to perform one or more data monitoring operations comprising counting an occurrence of a first value within at least a portion of items stored in a database. The method may include determining a length of a first window of time and fetching, from a first location of a data store of the database, data indicative of a total count of the occurrence of the first value at a time associated with the beginning of the first window of time. In turn, the monitoring system may store data representing the first count in the first memory.

Embodiments of the present disclosure provide a data query method and apparatus, which implement a technical effect that data meeting a precision requirement is queried according to a user's requirement of for data precision. The method includes: receiving a query instruction that includes a query condition and query precision; determining a data partition that meets the query condition; determining a data sub-partition corresponding to the query precision from the data partition; and querying data in the data sub-partition to obtain a query result.

A table organized into a set of batch units is accessed. A set of N-grams are generated for a data value in the source table. The set of N-grams include a first N-gram of a first length and a second N-gram of a second length where the first N-gram corresponds to a prefix of the second N-gram. A set of fingerprints are generated for the data value based on the set of N-grams. The set of fingerprints include a first fingerprint generated based on the first N-gram and a second fingerprint generated based on the second N-gram and the first fingerprint. A pruning index that indexes distinct values in each column of the source table is generated based on the set of fingerprints and stored in a database with an association with the source table.

Processing range operation data management statements in a database is provided. The method comprises receiving statements for range operations that specify referenced pages in the database. The range operations are stored in a search structure in a table directory in the database and applied to any referenced pages in a memory buffer pool. Application of the range operations is postponed for any referenced pages not in the memory buffer pool. The database determines if reading the postponed pages into the buffer pool would exceed a specified input/output threshold. If reading the postponed pages into the buffer pool does not exceed the specified threshold, the database reads the postponed pages from disk to the buffer pool asynchronously in parallel, and the range operations are then applied to the postponed pages. Pages modified by the range operations are then written from the buffer pool back to disk.

Provided are a data search method and apparatus, an electronic device and a storage medium. The method includes acquiring search data and a search condition and determining a target data set corresponding to the search data; determining each data distance between the search data and a respective query datum included in the target data set; performing data filtering on the each data distance based on the search condition and writing each filtered data distance as a target data distance into a memory; and reading the target data distance stored in the memory, using a query datum corresponding to the target data distance as a target response datum of the search data and displaying the target response datum.

Systems, methods, and computer-readable media for determining column ordering of a data storage table for search optimization are described herein. In some examples, a computing system is configured to receive input containing statistics of a plurality of queries. The computing system can then determine a new column order (i.e., layout) based at least in part on the statistics. In some example techniques described herein, the computing system can determine the new column order based at least in part on the hardware components storing the data storage table, storage system parameters, and/or user preference information. Example techniques described herein can apply the new column order to data subsequently added to the data storage table. Example techniques described herein can apply the new column order to existing data in the data storage table.

A query directed at a table organized into a set of batch units is received. The query comprises a predicate for which values are unknown prior to runtime. A set of values for the predicate are determined based on the query. An index access plan is created based on the set of values. Based on the index access plan, the set of batch units are pruned using a pruning index associated with the table. The pruning index comprises a set of filters that index distinct values in each column of the table. The pruning of the set of batch units comprises identifying a subset of batch units to scan for data that satisfies the query. The subset of batch units of the table are scanned to identify data that satisfies the query.

The present approach relates generally to systems and methods for outputting metric data from resources with a database accessible by a client instance. The client instance is hosted by one or more data centers and accessible by one or more remote client networks. In accordance with the present approach, a request to track metric data related to a resource is received. Further, a configuration item (CI) is retrieved from a database accessible by the client instance based at least in part on data associated with the request. Further, a type of CI is identified. Even further, a resource type associated with the type of the CI is identified based at least in part on a resource abstraction layer accessible by the client instance. Further still, the resource type is linked to the resource table and metric data associated with the resource is outputted.