Some embodiments of the invention provide a method for defining code-based policies. The method generates a policy-builder first view of a policy for display in a graphical user interface (GUI) by processing a syntax tree that is generated from a code second view of the policy. The method receives, through the policy-builder first view, a modification to a portion of the policy. To reflect the modification, the method updates a portion of the syntax tree that corresponds to the portion of the policy that is affected by the modification. Based on the updating of the syntax tree, the method updates the code second view by modifying a portion of the code second view that corresponds to the updated portion of the syntax tree.

Prioritizing crawled data in a document store for reprocess operations. Reprocessing occurs upon a triggering change to configurations. Prioritization is based on the status of the crawled data with respect to an ACL. During reprocessing, the crawled data is reprocessed in an order defined by assigned priority levels.

In some aspects, the disclosure is directed to methods and systems for data storage and retrieval from a computer memory. A computing device may store a first hierarchical data structure having a first sequence of sub-data structures and a second hierarchical data structure having a second sequence of sub-data structures in memory. The computing device may link the first hierarchical data structure and the second hierarchical data structure together. The computing device may link the first hierarchical data structure and the second hierarchical data structure by inserting an identifier of a sub-data structure of the second sequence in the first sequence.

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.

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

Described in detail herein is a method of copying data of one or more virtual machines being hosted by one or more non-virtual machines. The method includes receiving an indication that specifies how to perform a copy of data of one or more virtual machines hosted by one or more virtual machine hosts. The method may include determining whether the one or more virtual machines are managed by a virtual machine manager that manages or facilitates management of the virtual machines. If so, the virtual machine manager is dynamically queried to automatically determine the virtual machines that it manages or that it facilitates management of. If not, a virtual machine host is dynamically queried to automatically determine the virtual machines that it hosts. The data of each virtual machine is then copied according to the specifications of the received indication.

A data processing method, having an index cache structure specified to a transaction in a mobile DBMS environment, comprising: recording only information on whether data is deleted/inserted on the an index cache without changing original index data while an inquiry process is progressed in response to a request to insert or delete data from an inquiry processor; and performing a change on data by changing the original index based on whether data recorded on the index cache upon a transaction commit is deleted.

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

One embodiment sets forth a technique for generating a tree structure within a computer memory for storing sparse data. The technique includes dividing a matrix into a first plurality of equally sized regions. The technique also includes dividing at least one region in the first plurality of regions into a second plurality of regions, where the second plurality of regions includes a first region and one or more second regions that have a substantially equal number of nonzero matrix values and are formed within the first region. The technique further includes creating the tree structure within the computer memory by generating a first plurality of nodes representing the first plurality of regions, generating a second plurality of nodes representing the second plurality of regions, and grouping, under a first node representing the first region, one or more second nodes representing the one or more second regions.

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.