Log messages are compressed, searched, and decompressed. A dictionary is used to store non-numeric expressions found in log messages. Both numeric and non-numeric expressions found in log messages are represented by placeholders in a string of log “type” information. Another dictionary is used to store the log type information. A compressed log message contains a key to the log-type dictionary and a sequence of values that are keys to the non-numeric dictionary and/or numeric values. Searching may be performed by parsing a search query into subqueries that target the dictionaries and/or content of the compressed log messages. A dictionary may reference segments that contain a number of log messages, so that all log message need not be considered for some searches.

In a multi-cloud computing environment comprising a plurality of cloud platforms with each cloud platform comprising one or more nodes, a method maintains a decentralized metadata database framework, wherein each node comprises a decentralized metadata database component operatively coupled to each other decentralized metadata database component of the framework and wherein each of at least two of the decentralized metadata database components stores a set of metadata records corresponding to protected data stored across the plurality of cloud platforms. Further, the method manages one or more access requests directed to the protected data through one or more of the decentralized metadata database components of the framework.

The described method and system enables a client at a branch office to retrieve data from a local hosted cache instead of an application server over a WAN to improve latency and reduce overall WAN traffic. A server at the data center may be adapted to provide either a list of hashes or the requested data based on whether a hosted cache system is enabled. A hosted cache at the client side may provide the data to the client based on the hashes. The hashes may be generated to provide a fingerprint of the data which may be used to index the data in an efficient manner.

The present invention gives the methods and processes for automatically servicing user driven requests to find place-holder fields, fill them in with relevant data in a secure manner and securely communicating the data related thereto to the appropriate Android™ device and/or application. More particularly, it relates to the methods and processes for authenticated users to automatically obtain and use the correct filled-in data that allows them to access or use any of a multiple number of Android™ applications and/or services at any time.

Described are methods, systems and computer readable media for performance logging of complex query operations.

Systems and methods are disclosed for generation of a representative data structure. A computing device can receive data including various data items. The computing device can generate logical rows that include the data items. The computing device can convert the logical rows into nodes and store the nodes into logical rows of a first logical table. The computing device can generate logical rows for a second logical table including row identifiers and a link to one of the logical rows from the first logical table.

An example method is provided in according with one implementation of the present disclosure. The method comprises generating, via a processor, a set of hashes for each of a plurality of objects. The method also comprises computing, via the processor, a high-dimensional sparse vector for each object, where the vector represents the set of hashes for each object. The method further comprises computing, via the processor, a combined high-dimensional sparse vector from the high-dimensional sparse vectors for all objects and computing a hash suppression threshold. The method also comprises determining, via the processor, a group of hashes to be suppressed by using the hash suppression threshold, and suppressing, via the processor, the group of selected hashes when performing an action.

Described are methods, systems and computer readable media for data source refreshing.

A key-value storage system is described herein for interacting with key-value entries in a content store using a resource-efficient index. The index provides a data structure that includes a plurality of hash buckets. Each hash bucket includes a linked list of hash bucket units. The key-value storage system stores hash entries in each linked list of hash bucket units in a distributed manner between an in-memory index store and a secondary index store, based on time of their creation. The key-value storage system is further configured to store hash entries in a particular collection of linked hash bucket units in a chronological order to reflect time of their creation. The index further includes various tunable parameters that affect the performance of the key-value storage system.

In an example, a processing device of a database system may identify a set of machine learning features; generate a first hash map of said set of machine learning features and a second different hash map of said set of machine learning features. The processing device may generate a memory compact model for an online machine learning system using the first and second hash maps, and store the memory compact model in the memory device.