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.

A method includes receiving from a transmitting data interface, a data stream mapping of a data input into data shards for transmission in a data stream over a data stream communication channel. Data capacity for a data producing software application from a plurality of data producing software applications is adjusted by increasing or decreasing a number of data shards in the data stream assigned to the data producing software application. An updated data stream mapping of the data input into the plurality of data shards is generated by updating a start hash key and an end hash key in a range for each of the data shards assigned to the data producing software application. The updated data stream mapping is sent to the transmitting data interface for adjusting the data capacity in the data stream transmitted over the data stream communication channel of the data producing software application.

Example embodiments relate to a system to generate and cause display of a specially configured graphical user interface to receive and present collections of images. According to certain example embodiments, an image analysis system: receives an image file from a client device; generates a hash value based on the image file; performs a comparison of the hash value with a list that comprises a collection of hash values; identifies a match to the hash value among the collection of hash values; assigns a label to the image file in response to identifying the match among the collection of image files from the list; and indexes the image file at a memory location identified by the label assigned to the image file.

An embodiment relates to a computer-implemented data processing system and method for storing a data set at a plurality of data centers. The data centers and hosts within the data centers may, for example, be organized according to a multi-tiered ring arrangement. A hashing arrangement may be used to implement the ring arrangement to select the data centers and hosts where the writing and reading of the data sets occurs. Version histories may also be written and read at the hosts and may be used to evaluate causal relationships between the data sets after the reading occurs.

A method may include inserting, into a hash trie, data records from a database table. The inserting may include traversing the hash trie to identify, for each data record included in the database table, a corresponding node at which to insert the data record. The hash trie may be traversed based on a hash of a key value associated with each data record. The node at which to insert a data record may be identified based on an offset forming a binary representation of the hash of a key value associated with that data record. The offset may include a portion of a plurality of binary digits forming the binary representation. A data record may be inserted at a corresponding node by updating a data structure included at the node. A database operation may be performed based on the hash trie filled with the data records from the database table.

The present disclosure provides a method for automatically collecting and matching laboratory data, including: obtaining a creation time of experimental data, determining target experimental data corresponding to a target time in accordance with the creation time, segmenting the target experimental data into a plurality data blocks, generating a data block index table, including at least one data block identifier, according to the data blocks, selecting a target matching mode from a plurality of predetermined matching modes according to the data block index table, obtaining the data block identifier upon determining the target experimental data in a storage node is loaded, and extracting data content in the target experimental data corresponding to the data block identifier by the target matching mode. This method may greatly reduce the number of string matching and may reduce the complexity of the algorithm.

Described are methods, systems and computer readable media for dynamic updating of query result displays.

A shared-nothing database system is provided in which parallelism and workload balancing are increased by assigning the rows of each table to “slices”, and storing multiple copies (“duplicas”) of each slice across the persistent storage of multiple nodes of the shared-nothing database system. When the data for a table is distributed among the nodes of a shared-nothing system in this manner, requests to read data from a particular row of the table may be handled by any node that stores a duplica of the slice to which the row is assigned. For each slice, a single duplica of the slice is designated as the “primary duplica”. All DML operations (e.g. inserts, deletes, updates, etc.) that target a particular row of the table are performed by the node that has the primary duplica of the slice to which the particular row is assigned. The changes made by the DML operations are then propagated from the primary duplica to the other duplicas (“secondary duplicas”) of the same slice.

Systems and methods are described for providing rapid access to data objects stored in a cache. Rather than storing data objects directly, each object can be broken into a number of parts via erasure coding, which enables the object to be generated from less than all parts. When servicing a request for the data object, a device can attempt to retrieve all parts, but begin to generate the data object as soon as a sufficient number of parts is retrieved, even if requests for other parts are outstanding. In this way, the data object can be retrieved without delay due to the slowest requests. For example, where one or more requests timeout, such as due to failure of cache devices, this timeout may have no effect on time required to retrieve the data object from the cache.

Object service receives communication of fingerprints stream, corresponding to file segments, from file source, and identifies sequential fingerprints in fingerprints stream as fingerprints group. Object service identifies group identifier for fingerprints group, and communicates fingerprints group to deduplication service associated with group identifier range including group identifier. Deduplication service identifies fingerprints in fingerprints group which are missing from fingerprint storage, and communicates identified fingerprints to object service, which communicates request for file segments, corresponding to identified fingerprints, to file source. Deduplication service receives communication of requested segments from file source, and stores requested segments. System identifies generation identifier associated with time of communicating by object service or deduplication service and identifies generation identifier associated with another time of communicating by object service or deduplication service. If generation identifier associated with time differs from generation identifier associated with other time, object service or deduplication service restarts communication.